Exploratory research at IRMM 2007 - Final...

EUR 24072 EN - 2009

Exploratory research at IRMM2007 - Final report

Compiled by the scientific committee of IRMM

The mission of the JRC-IRMM is to promote a common and reliable European measurement system in support of EU policies. European Commission Joint Research Centre Institute for Reference Materials and Measurements Contact information Address: A. Herrero Molina E-mail: [email protected] Tel.: +32 (0) 14 571292 Fax: +32 (0) 14 584273 http://irmm.jrc.ec.europa.eu/ http://www.jrc.ec.europa.eu/ Legal Notice Neither the European Commission nor any person acting on behalf of the Commission is responsible for the use which might be made of this publication.

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A great deal of additional information on the European Union is available on the Internet. It can be accessed through the Europa server http://europa.eu/ JRC 55173 EUR 24072 EN ISBN 978-92-79-13939-0 ISSN 1018-5593 DOI 10.2787/1885 Luxembourg: Office for Official Publications of the European Communities © European Communities, 2009 Reproduction is authorised provided the source is acknowledged Printed in Luxembourg

Exploratory research at IRMM 2007

Final report

i

Table of contents Foreword ………………………………………………………………………………………..iii A. Herrero Molina, Director of IRMM….…… Production of uranium particle reference materials …………………………………………A R. Kips, R. Wellum,Y. Aregbe A neutron source in the energy range between 8 and 14 MeV for Van de Graaff accelerators ……………………………………………………………………………………...B G. Giorginis, V. Khryachkov, F.-J. Hambsch, S. Oberstedt, N. Kornilov, G. Lövestam ….…… Measurement of neutron activation cross section curves using moderated neutron fields (NAXSUN) (PROLONGATION) …………………………………………………………..…C G. Lövestam, M. Hult,P. Lindahl, S. Oberstedt,V. Semkova C6D6-EXTENDED : The use of a high efficiency array of C6D6 detectors for absolute capture cross section measurements in the thermal and epi-thermal energy region……….D A. Borella, J. Gonzalez, F. Gunsing, A. Plompen, C. Sage, P. Schillebeeckx, P. Siegler ….…… Quantification in GMO Certified Reference Materials (CRMs): towards a new approach for PCR performance quality control of DNA extracts ……………………………………..E W. Broothaerts, P. Corbisier, S. Trapmann ………. Metal solid phase extraction from natural, saline and waste waters using TiO2 nano-particles: method development ………………………………………………………….F C. Quétel, I. Petrov, E. Vassileva ….…… Investigation of possibilities to quantify allergenic proteins, in particular major peanut allergens in the presence of natural enzyme inhibitors ……………………………………..G A. Muñoz-Piñeiro and R. Kral………. High temperature liquid chromatographic analysis of PAHs in foods …………………….H S. Szilagyi, L. Hollosi, T. Wenzl Detection of allergenic peptides derived from milk hydrolysates by proteomic and immunochemical approaches ………………………………………………………………….I V. Tregoat, L. Monaci, A. Van Hengel

Annexes Annex 1: Guidelines and forms: applications for new projects Annex 2: Guidelines and forms: applications for prolongation of previous projects Annex 3: Selected projects for the year 2007

Foreword

It is with great pleasure that I present to you the fourth report on exploratory research at JRC-IRMM. As you know, since several years, the exploratory research plays a key role at JRC-IRMM in line with the JRC policy that aims to spend up to 6 % of its resources. This path to new knowledge and expertise showed to be of great interest to the institute in particular when shaping its future actions. The fourth call for proposals was launched in June 2006. The Scientific Committee1 of JRC-IRMM was in charge of the two-step evaluation (written applications and auditions) of the proposals, of the selection and the follow-up of those which were granted. Based on several criteria including the relevance to the institute’s mission and activities, the innovative aspects, the quality of the research plan and the integration of resources, ten projects were selected, covering several of the scientific fields in which JRC-IRMM is active. On March 4th 2008, a workshop was held where the results of eight projects were presented to the staff of the institute. Significant results have been obtained which will be of high importance both for the scientific recognition of JRC-IRMM as a research institute and for a better performance of its present and future institutional tasks. The results from nine projects are shown in this report. They will obviously contribute to the development of future competencies and technical capabilities of the institute, enhancing the common goal of all our projects to create "confidence in measurements". The outcome of this fourth year of implementation of the exploratory research system established at the IRMM is without any doubt very positive and strengthens my wishes to continue with it. I wish to thank all IRMM scientists who participated in the various exploratory research projects, and I encourage others to submit proposals in future calls. I would also like to acknowledge the members of our Scientific Committee for their excellent mastering of the whole process. Alejandro Herrero Director of IRMM

1 Guy Bordin, Wim Broothaerts, Philippe Corbisier, Alejandro Herrero Molina, Mikaël Hult, Sari Lehto, Göran Lövestam, Josephine McCourt, Piotr Robouch and Ursula Vincent.

EUROPEAN COMMISSION DIRECTORATE-GENERAL JOINT RESEARCH CENTRE Institute for Reference Materials and Measurements Isotope Measurements unit

Production of Uranium Particles Reference

Materials

Date: 01/07/2008

Authors: Ruth Kips

Revised by: Yetunde Aregbe, Roger Wellum

Approved by: Yetunde Aregbe

TABLE OF CONTENTS

1. SUMMARY........................................................................................................................................... A-2

2. INTRODUCTION ................................................................................................................................ A-3

2.1. Historical Development of International Safeguards........................................................................... A-3 2.2. Analysis of Uranium Particles from Swipe Samples........................................................................... A-4 2.3. Current State-of-the-Art ...................................................................................................................... A-5

3. EXPERIMENTAL ............................................................................................................................... A-6

3.1. The aerosol deposition chamber .......................................................................................................... A-6 3.2. Scanning electron microscopy with energy dispersive X-ray spectrometry........................................ A-7 3.3. Secondary ion mass spectrometry ....................................................................................................... A-8 3.4. Transmission electron microscopy ...................................................................................................... A-8

4. RESULTS.............................................................................................................................................. A-9

4.1. Optimization of the aerosol deposition chamber ................................................................................. A-9 4.2. Effect of various process parameters on the particle morphology..................................................... A-10 4.3. Effect of environmental conditions on particle morphology during storage ..................................... A-13 4.4. Analysis of fluorine in UO2F2 particles as an indicator for particle ageing....................................... A-15 4.4.1. SEM-EDX/WDX analysis ................................................................................................................A-15 4.4.2. Micro-Raman analysis.....................................................................................................................A-17 4.4.3. SIMS analysis ..................................................................................................................................A-20

5. CONCLUSIONS................................................................................................................................. A-25

6. REFERENCES ................................................................................................................................... A-26

Production of Uranium Particles Reference Materials A-2 / 27

1. SUMMARY

In the oversight of the nuclear non-proliferation treaty and as part of the Additional Protocol of the International Atomic Energy Agency, environmental sampling has become an important tool for the detection of non-declared nuclear activities. One extensively developed technique in environmental sampling (ES) makes use of pieces of cotton cloth called swipes to wipe surfaces in and around a nuclear facility. The dust collected on these swipes typically contains micrometer-sized uranium particles with an isotopic composition characteristic for the processes at the inspected facility.

Since its implementation in the 1990s, ES has proven to be a very effective tool in the detection of clandestine activities owing to a number of highly sensitive and selective techniques, including secondary ion mass spectrometry and thermal ionisation mass spectrometry. However, considering the potential consequences of the analyses, these measurements need to be subjected to a rigorous quality management system. In a continuous effort to improve the accuracy and detection efficiency of the uranium isotope ratio measurements, uranium particle reference materials are being developed by different research groups. It was concluded however, that the existing methods for the production of particulate reference materials generally do not reproduce the particles recovered from swipe samples.

For this reason, the aerosol deposition chamber was developed as part of the Exploratory Research at the Institute for Reference Materials and Measurements for the production of reference uranium particles that are representative of the particles collected at enrichment facilities. This method is based on the controlled hydrolysis of milligram amounts of uranium hexafluoride with a certified uranium isotopic composition. The particles produced by the aerosol deposition chamber were characterized by scanning electron microscopy, transmission electron microscopy, μ-Raman spectroscopy and secondary ion mass spectrometry. The particle morphology and composition were found to be dependent on the relative humidity of the air, the exposure to ultraviolet light and the time elapsed after formation. Possible correlations between the relative amount of fluorine and the age of the particles were investigated. These results were the starting point for the first inter-laboratory measurement evaluation program (NUSIMEP) on uranium particles.


2. INTRODUCTION

2.1. Historical Development of International Safeguards

The summer of 1991 was a turning point in the history of nuclear safeguards. In spite of Iraq's ratification of the NPT, IAEA inspectors detected evidence of isotopically altered uranium that did not correspond to any of the declared materials. In addition, traces of plutonium were found together with extremely depleted uranium that could only result from electromagnetic separation, a technique no longer known to be applied anywhere in the world [1]. These findings eventually led to the discovery of Iraq's clandestine uranium enrichment programme and triggered a large-scale research effort to develop inspection methods and equipment that are capable of detecting similar clandestine programmes.

In 1993, the IAEA launched its so-called 93+2 research programme to identify those analytical measurement techniques that are sufficiently selective and sensitive to detect traces of nuclear materials in samples collected in the "environment" of a known or suspected facility. The collection of these techniques was given the name 'environmental sampling' (ES) [1] and Euratom joined to this investigation through the development of a similar programme referred to as High Performance Trace Analysis (HPTA). These programmes are based on the sampling and analysis of elements and isotopes which provide a unique "fingerprint" of anthropogenic processes such as isotope enrichment or neutron irradiation. The material for ES is collected by wiping surfaces with 10 cm x 10 cm pieces of cotton cloth and produces a vast amount of information on the present and past activities of a facility. These so-called swipe samples are preferably taken from surfaces inside or in the vicinity of a known or suspected facility to minimize dilution effects [1].

The IAEA's 93+2 research programme resulted in the publication of INFCIRC/540, also referred to as the Additional Protocol (AP). The IAEA Board of Governors officially approved this Model Protocol Additional to Safeguards Agreements in May 1997 and hereby greatly expanded the IAEA's legal authority to conduct its safeguards activities. The aim of the Additional Protocol was to reshape the IAEA's safeguards regime from a quantitative system focused on accounting for known quantities of materials and monitoring declared activities to a more qualitative system that is able to provide a comprehensive picture of a state's nuclear activities. With the implementation of the AP, the conventional safeguards inspections, which relied mainly on the physical verification of the inventory (PIV) of a facility, were complemented by novel techniques such as ES and satellite and wide-area monitoring that were successfully tested in the 93+2 research programme. For states that had adopted the AP as a complement to their existing safeguard agreements, inspections were no longer limited to declared nuclear materials and installations. Instead, the IAEA became authorized to verify the absence of undeclared nuclear activities in all parts of a state's nuclear fuel cycle, including uranium mines, fuel fabrication plants, enrichment facilities and nuclear waste sites, as well as any other location where nuclear material is or may be present, and this at nearly any time.

The implementation of ES did require the establishment of a baseline environmental signature for each facility [2]. In the early stages of sample collection, swipe sampling field trials were therefore directed to facility locations with a high potential for containing traces of past and current nuclear activities. The measurement results from these swipe samples were used to identify the nuclear baseline signature of the facility. Once the baseline was established, the specific requirements for ES as part of routine safeguards inspections were determined. The first environmental sample taken under the AP agreement was collected in April 1998. Since then, ES has been routinely applied as a sensitive and reliable tool for the verification of the absence of undeclared nuclear activities.


2.2. Analysis of Uranium Particles from Swipe Samples

The strength of HPTA and ES lies in the observation that every nuclear process - no matter how leak-tight - emits small amounts of process material to the environment. As uranium enrichment and reprocessing facilities are considered to be proliferation-sensitive, most of the efforts for the development of ES as part of the 93+2 research programme were spent on these types of installations.

In the case of uranium enrichment facilities, small releases of UF6 produce micrometer-sized uranium particles that settle onto various surfaces within the building. When these surfaces are swiped during environmental sampling inspections, the uranium particles are collected together with thousands of dust particles. It is this uranium fraction that is of interest to safeguard inspectors, as the n(235U)/n(238U) isotope ratio provides a means to determine the uranium enrichment factors at the inspected facility.

However, the accurate measurement of these trace levels of uranium required a dedicated handling and measurement capability. The establishment of such a facility not only implied the development and validation of sampling methods, it also involved the set-up of a class-100 clean laboratory to reduce the risk of cross-contamination during sample handling. In addition, a solid quality assurance system needed to be implemented to eliminate any doubts about the credibility of the results.

This was realized through the creation of the IAEA's Safeguards Analytical Laboratory (SAL) in Austria, where the IAEA's analytical capabilities for the analysis of environmental samples were centralized. SAL was established in 1961 with the aim of contributing to the implementation of the IAEA safeguards programmes and projects within the department of Nuclear Sciences and Applications, Safeguards, Nuclear Safety and Security and Technical Support.

Although the IAEA is well-equipped for bulk and particle analysis, the co-operation with qualified laboratories from IAEA member states further increased the IAEA’s analytical capability for the analysis of environmental samples. This group of national and international laboratories was named the Network of Analytical Laboratories (NWAL) and serves as a back-up in times of peak sample loads. The co-operation between the IAEA and the NWAL also significantly increased the confidence in the accuracy of the results through the parallel measurement of replicate sub-samples. Nowadays, the IAEA and its NWAL process several hundreds of swipe samples each year, the majority of these collected at uranium enrichment facilities.

Even though the analysis of single particles from swipe samples is regarded as a very sensitive tool in the detection of undeclared nuclear activities, the identification of a few micrometer-sized uranium particles enriched in 235U among thousands or millions of other dust particles remains a challenging task that is best described as a “needle-in-the-haystack” problem. For SIMS measurements, the time required to identify and locate the enriched uranium particles was considerably decreased by SIMS software tools such as PSearch® (Charles Evans & Associates) that allow the detection of highly enriched uranium particles from their signal intensities on the 235U and 238U ion images [3].

Particles for TIMS analysis are selected by irradiating the sample with neutrons in a nuclear reactor. The number of fission tracks that is produced by the uranium particles indicates the level of 235U enrichment. This technique is therefore referred to as fission-track thermal ionisation mass spectrometry (FT-TIMS).

Even though the analytical techniques applied for the detection and measurement of uranium particles from environmental samples are undoubtedly state-of-the-art in terms of sensitivity and selectivity, newer and more powerful methods are continuously under development. The NWAL supports the IAEA in this task by performing research on particle sample preparation and analysis techniques, as well as through the development of reference materials for environmental sampling. It is in this context that the IRMM has developed a method


to produce particulate uranium reference materials for ES. The method, referred to as the aerosol deposition chamber, aims to produce uranium particles that are similar in morphology and composition to those recovered from swipe samples taken at enrichment facilities. The production and characterization of the uranium particles produced by the aerosol deposition chamber were therefore the objectives of this Exploratory Research.

2.3. Current State-of-the-Art

The development of reference or standard particles for environmental sampling basically serves two goals: firstly, the reference particles can be distributed among the laboratories in an internal quality control exercise as a performance indicator for measurement accuracy, detection efficiency and precision, in addition to specific particle analysis related capabilities such as the efficiency of the particle selection. Secondly, particulate reference materials can be added to a batch of environmental swipe samples as a blind quality control sample [4].

When used as an internal quality control sample, the measurement of reference materials closely resembling the material under analysis generally provides a very realistic image of the measurement capability. In addition, these types of samples are preferred as blind quality control samples as their characteristics are very similar to real-life samples. It is therefore very useful to develop particulate reference materials that mimic most of the swipe sample characteristics. However, the preparation of such particulate reference materials not only implies the control and certification of the elemental and isotopic properties, but also of the morphology, size and number of particles.

In the past, standard particles with varying characteristics have been developed by different research groups. These methods range from the nebulisation of a uranyl nitrate solution and its subsequent dehydration and calcination to the blending of uranium oxides with matrix glass powder. However, the existing methods for the production of particulate reference materials involve many steps and generally do not reproduce the morphology, molecular structure and composition of the particles recovered from swipe samples.

A new particle production method referred to as the aerosol deposition chamber was therefore developed at IRMM and is based on the controlled hydrolysis of uranium hexafluoride.


3. EXPERIMENTAL

3.1. The aerosol deposition chamber

At the IRMM, the aerosol deposition chamber was developed to produce uranium oxyfluoride reference particles from the controlled hydrolysis of UF6 (Fig. 1) [5]. In this chamber, milligram amounts of UF6 are released in static air under controlled temperature and humidity conditions.

UF6 + 2 H2O UO2F2 +4 HFUF6 + 2 H2O UO2F2 +4 HF

Fig. 1: Aerosol deposition chamber for the preparation of UO2F2 particles.

With the aim of producing uranium reference particles, the aerosol deposition chamber uses a UF6 material certified for its uranium isotope ratios with very low uncertainty. Most of these UF6 reference materials used for the aerosol deposition chamber were certified in-house, either by gas mass spectrometry or by thermal ionisation mass spectrometry. The hydrolysis of these UF6 reference materials was assumed to produce UO2F2 particles having the same well-defined uranium isotope ratios. This was confirmed by Cameca IMS 4f SIMS measurements performed at the Institute for Transuranium Elements (EC-JRC-ITU, Karlsruhe, Germany), where the average values of the uranium isotope ratios of individual particles were compared to the certified values of the bulk UF6 reference material (CRM U200, DOE/NBL, USA) from which the particles were produced. The 234U/238U, 235U/238U and 236U/238U isotope ratios for the particles reported in Table 1 are the average values of three uranium particles characterized individually by SIMS in the ion microprobe mode, using a 8.5 keV O2

+ primary ion beam at current of 2 nA and a spot-size of a few micrometers.

Table 1: Comparison of the certified values for the uranium isotope ratios of a UF6 reference material (CRM U200) and the particles produced by the aerosol deposition chamber (average of 3 particles). The difference is expressed in the bias (percent error). The measured value for mass 236 has been corrected for the contribution of 235UH+.

UF6 CRM U200 Particles Mass

Certified value

RSD (%) Measured value

RSD (%)

Bias (%)

234U/238U 1.56432 x 10-3 0.24 1.549 x 10-3 2.0 0.98 235U/238U 2.5126 x 10-1 0.040 2.513 x 10-1 1.1 0.016 (236U/238U)corr 2.65659 x 10-3 0.28 2.687 x 10-3 2.4 1.03


The UF6 reference materials used for the production of uranium particles generally had a percentage of 235U varying between 0.16713(28) % and 20.013(20) %. In addition to these commercially available reference materials, the in-house production and verification of the UF6 reference materials holds forth the prospect of producing uranium particles with specified custom-made values of their isotope ratios. These materials are preferred for use as external quality control samples as they have an isotopic composition unknown to the laboratories.

Since UF6 is known to react with most metals to form a fluoride of the metal, the UF6 reference material is stored in an ampoule made of Monel (65 % nickel and 30 % cupper alloy containing small percentages of iron, silicon, manganese, carbon and sometimes aluminium). A small amount of a selected UF6 reference material was distilled into a glass vial of ca. 14 cm3. The set-up of the distillation unit is shown in Figure 2. The distillation unit was pumped down to a vacuum in the range of 10-6 mbar (10-4 Pa) before the UF6 was transferred to the glass vial.

Fig. 2: The distillation unit for the transfer of milligram amounts of a certified UF6 reference material to a glass vial at the other end of the unit.

After transfer, the glass vial containing the gaseous UF6 was flame-sealed and placed into the upper part of the aerosol deposition chamber. The chamber consists of a cylindrical stainless-steel reaction chamber (Ø 10 cm x 20 cm) with a lid at each end in Plexiglas.

A mechanical breaking mechanism was implemented in the aerosol deposition chamber to release the UF6 (Fig. 3). The water in the chamber’s atmosphere subsequently initiated the UF6 hydrolysis, which led to the formation of UO2F2 particles.

Through gravitational settling, the UO2F2 particles were collected on graphite planchets at the base of the chamber. After a fixed collection time between 16 and 90 hours, the planchets were removed from the chamber and could be directly inserted in the various measurement instruments.

3.2. Scanning electron microscopy with energy dispersive X-ray spectrometry

The particle morphology, composition and distribution on the planchets were examined by a FEI Quanta 200 3D dual beam scanning electron microscope at the IRMM. This microscope is

UF6 RM ampoule

Glass vial


equipped with a tungsten filament and an Oxford INCA Si(Li) EDX detector with an energy resolution of around 130 eV at 5.9 keV. The electron beam energy was set to 20 keV for secondary (SEI) and backscattered (BEI) electron imaging. For the EDX measurements on fluorine with the X-ray Kα line at 0.677 keV, the acceleration voltage was lowered to 10 kV to optimize the over-voltage ratio and interaction volume.

3.3. Secondary ion mass spectrometry

The Cameca IMS 4f and 6f SIMS instruments used at EC-JRC-ITU are both equipped with a caesium and O2

+/Ar+ duoplasmatron ion source for the detection of respectively electronegative and electropositive ions. The acceleration voltage of the primary ion beam was set to 15 kV using a primary ion dose rate of 1-5 nA/cm2. Samples were screened to locate the uranium particles in the IMS mode. For this, a large area of 100 μm × 100 μm was scanned for each mass of interest. Selected particles were subsequently analyzed in the IMP mode with a current between 1 nA and 2 nA in a focused spot of a few micrometers. For the measurement of the uranium isotopes, a resolution of 1000 was found to be sufficient. At this resolution, a high signal intensity on m/z 235 and m/z 238 and flat-top peaks were obtained, which significantly improved the accuracy of the measurement.

At QinetiQ (Malvern,UK) a similar Cameca IMS 4f magnetic sector instrument was used for the analysis of fluorine in single uranium particles. An 8 kV O2

+ primary beam energy was applied at a current of 2 nA in a focused spot with an estimated diameter of 10 μm. This SIMS instrument was used for the collection of mass spectra spanning 300 amu, scanned in steps of 0.1 amu with 0.1 s dwell time. For mapping, the primary ion beam was defocused and the secondary ions were detected by a resistive anode encoder (RAE). PXT PSearch® software was used for the fast location of uranium particles.

3.4. Transmission electron microscopy

In TEM, the electrons produced from a thermionic or FEG source are accelerated by a high voltage varying from 100 kV to more than 600 kV, depending on the microscope used. A combination of magnetic lenses focuses this electron beam onto a thin sample of generally not more than 100 nm. For these thin samples, the electrons pass through the sample, either unscattered or scattered only once or twice through a relatively small angle. The transmitted electrons are subsequently collected underneath the sample where the image is formed, magnified and directed to appear either on a fluorescent screen or to be detected by a CCD camera.

The TEM is primarily designed for imaging (bright field), with a resolution and magnification superior to SEM. The high magnification and lateral resolution of the TEM allowed for the analysis of the uranium particle morphology on the nanoscale. Due to the restrictions on sample thickness however, only the smallest particles between 20 nm and 300 nm were analyzed, where the internal crystal structure was the most visible near the edges of the particles. The surface layer surrounding the particles was sufficiently thin for TEM imaging, but was often not resistant to the high energy primary electron beam. Alterations to the particle morphology in general were also observed in non-spherical uranium particles.

The sample preparation on the other hand, was quite straight-forward as the particle samples were prepared by depositing uranium particles directly onto holey carbon films on a 300 mesh copper grid (Bal-Tec). These holey carbon films had a diameter of 3.05 mm and a thickness in the order of 10-20 nm. The particles positioned near the edges of a hole in the carbon film were preferred for the analysis of the particle's internal morphology, density variations and crystal structure, as the sample was generally thinner in those areas.

The uranium particle samples were measured by TEM at the University of Antwerp (EMAT) and at QinetiQ, Malvern (UK).


4. RESULTS

4.1. Optimization of the aerosol deposition chamber

The general design of the aerosol deposition chamber is very straight-forward and could be realized with a minimum of costs. However, in order to optimize the control of certain process parameters, such as the particle collection time and the temperature and relative humidity of the air in the chamber, specific adjustments were made to the chamber and the original device composed of a stainless-steel cylindrical chamber was replaced by a slightly larger chamber of about 3 l volume, equipped with a built-in Rotronic hygrometer for measuring the temperature and humidity.

The temperature of the air in this new version of the aerosol deposition chamber was adjusted by changing the temperature of the water that runs on the outside of the chamber through a copper coil which is fed from a thermostatically-controlled water bath (Fig. 3). Additional functionalities include a gas-inlet system to replace the atmospheric air by other gases such as nitrogen. This feature is potentially useful in the study of the effects of (the lack of) nucleation centres on particle morphology.

The design of the chamber was made even more flexible by implementing all functionalities in the lids of the chamber: the breaking mechanism was incorporated in the top lid, consisting of a pin to break the glass vial and two clamps to hold the vial in position. The lid at the base of the chamber was used for the collection of the glass shards that resulted from breaking the vial.

In addition, the aerosol deposition chamber was equipped with a retractable platform carrying up to 6 carbon planchets at the base of the chamber. By inserting the planchets on this platform only shortly after the glass vial is broken, the majority of the glass shards are collected in a reservoir at the base of the chamber instead of being deposited on the planchets together with the particles. For the preparation of quality control samples, this feature is very useful, as a large amount of glass shards on the planchets could reveal the origin of the samples. This platform also allows the collection of particles for specific time intervals, as opposed to time-integrated particle collection.

Each time the UF6 reference material was changed, the whole chamber was decontaminated by a rinsing procedure using nitric acid and a mixture of hydrogen peroxide and sodium carbonate to avoid cross-contamination from the previous material.


Fig. 3: The optimized aerosol deposition chamber, including a new breaking mechanism (picture insert), a retractable platform for the graphite planchets, a coil surrounding the chamber for temperature control, a gas inlet connection and a temperature and humidity read-out device.

4.2. Effect of various process parameters on the particle morphology

The particles produced by the aerosol deposition chamber were thoroughly characterized by SEM, SIMS and TEM to determine the particle formation processes. The influence of process parameters such as the temperature and humidity of the air was investigated and the results are described in this section.

To ascertain the effect of the relative humidity of the air inside the aerosol deposition chamber, experiments were carried out at 70 %, 43 % and 15 % relative humidity with the aim of comparing the particle morphology at these different levels of humidity using SEM. The variations in relative humidity were obtained by either LiCl salt solutions or silica gel, while the air was kept at room temperature.

The release of UF6 in air with a relative humidity of 15 % produced chainlike agglomerates of varying size which grew as large as 100 μm in greatest dimension. SEM images showed these agglomerates were composed of discrete particles generally less than 1 μm and this size range is in accordance with the findings of Pickrell [6]. The individual particles comprising these agglomerates ranged between 30 nm and 150 nm, as measured by TEM.

This chain-like morphology was also observed for particles from environmental swipe samples taken at enrichment facilities. In Figure 4 the morphology of the uranium particles produced by the aerosol deposition chamber at 15 % relative humidity is compared to the chainlike agglomerates recovered from swipe samples.

Although the mechanisms of agglomeration are not fully understood, it is assumed that these chain-like agglomerates were formed by collisions of submicron uranium particles in the air that eventually settled through gravity. The agglomeration generally seemed to follow a line pattern, which might be caused by the static charge that is built up in the dry atmosphere of the chamber.


Fig. 4: JEOL 6310/Philips XL 30 SEM images of agglomerated uranium

particles produced by the aerosol deposition chamber at 15 % relative humidity (left) and agglomerated particles recovered from swipe samples (right image obtained from CEA).

When the relative humidity of the air in the chamber was increased to approximately 43 %,

the chain-like agglomerates were no longer observed. The agglomerated particles were generally not larger than 10 µm and showed a very irregular structure (Fig. 5). However, it is assumed that factors other than the humidity determined the particle morphology in this intermediate humidity range, as experiments carried out at a relative humidity either slightly above or below 43 % resulted in respectively chain-like agglomerates characteristic for low humidity conditions or discrete spheroids that are usually formed in a humid atmosphere.

Fig. 5: JEOL 6310 SEM image at 1000× magnification of uranium particles

produced by the aerosol deposition chamber at 43 % relative humidity.

The experiments carried out in a high humidity of 70 % produced uranium particles of

around 1 μm with only little agglomeration (Fig.6). The morphology of these particles was generally described as spherical, although particles with a more irregular shape were found as well. SEM imaging also detected density difference between particles from the same sample (Fig. 6).

As UO2F2 is very hygroscopic, the more spherical shape of these uranium particles is assumed to result from the absorption of water. This was also concluded by Carter [7] who stated that in high humidity environments of 70 % or higher, the uranium particles are generally


spherical with typical sizes ranging from 1 μm to 2 μm which eventually become quasi-solutions. Figure 7 shows a SEM image of a cluster of 2 uranium particles found at enrichment facilities. These particles are compared to the particles produced by the aerosol deposition chamber. For both the 'real-life' particles and the particles produced by the chamber, a thin surface layer was detected covering the particle surface.

Fig. 6: Philips XL 30 SEM image of uranium particles with varying density

produced in 70 % relative humidity using the aerosol deposition chamber.

Fig. 7: Philips XL 30 SEM images of uranium particles produced in 70 % relative humidity using the aerosol deposition chamber (left) and uranium particles recovered from swipe samples (right- image CEA). In both cases a thin surface layer surrounding the individual uranium particles is visible.

The effect of the temperature of the air was also investigated for the particles produced in the aerosol deposition chamber (Fig. 8). By adjusting the temperature of the water bath that feeds the cupper coil around the chamber the temperature of the air was varied. The water bath was set to temperatures close to the minimum and maximum level, resulting in respective air temperatures of 10 °C and 42 °C.

For the experiments performed at a temperature of approximately 10 °C, the dew point principle limited the minimum humidity to about 55 %. As expected, the particles formed at this humidity were mainly discrete spheroids showing little agglomeration, although it should be mentioned that several of these spheroids were larger than 2 μm, as they were formed through the coalescence of 2 or more single spheroids. In addition, the spheroids often showed an irregular surface layer much thinner than the core material. This surface layer is more likely to be caused by surface dissolution effects resulting from the high humidity of the air, rather than the low temperature at which the particles were produced.


When releasing UF6 in dry air of ca. 42 °C, large particle chains of several tens of microns in greatest dimension were detected on the planchet. These chain-like agglomerates were composed of submicron uranium particles combined with glass pieces of up to 10 μm. The morphology of the agglomerates was found to be in accordance with the morphology detected at room temperature.

These experiments showed that moderate changes in air temperature did not seem to significantly affect the particle morphology, although an increase in average particle size was observed for the particles produced in high humidity at low temperature.

Fig. 8: SEM images of uranium particles produced by the aerosol deposition chamber under different temperature and humidity conditions.

4.3. Effect of environmental conditions on particle morphology during storage

The experiments described in Section 4.2 on the hydrolysis of UF6 in both humid and dry atmospheres clearly demonstrated the effect of the relative humidity of the air on particle morphology. The temperature and humidity conditions inside the aerosol deposition chamber were therefore carefully controlled for the entire duration of the experiment. Once the particles were removed from the chamber however, they were exposed to the ambient moisture in the storage room and this altered the particle morphology, as demonstrated in the previous section.

In order to control the temperature and humidity conditions during storage, a climate chamber with programmable humidity and temperature values was used (Excal 220, Climats). The temperature inside this climate chamber was variable between 10 °C – 90 °C and the humidity between 10 % - 98 %. Experiments were carried out with the aim of determining the effect of these environmental parameters on particle morphology during storage. This would help to determine the stability of the particle morphology over time, which is also useful with respect to determining the optimal long-term storage conditions of uranium particulate reference materials.

The selected temperature and humidity conditions in the climate chamber were realistic for certain climate conditions around the world. A warm and very humid environment was simulated by setting the temperature to 35 °C and the humidity to 90 %. This was considered to be the most


extreme case with the highest chances of particle morphology alterations. At the lower end of the temperature range, the humidity was limited by the dew point principle and this implied that at 10 °C a relative humidity of 60 % was the lowest attainable value. Particle samples produced in both high humidity (~ 70 %) and low humidity (< 15 %) conditions were prepared for storage in the climate chamber.

The morphology of the particles was compared by SEM imaging before and after storage in the climate chamber. For the particles produced in high humidity and temperature conditions, the SEM images showed fading of the contours of the discrete uranium spheroids in addition to the formation of a diffuse uranium film that covered a large area of the graphite surface (Fig. 9). This film is known to obstruct the analysis of individual particles and may lead to isotopic mixing between particles with a different uranium isotopic composition. This mixing effect has also been reported by Carter [7], who stated that in very moist atmospheres, mixing may occur through surface solubility effects and the agglomeration of associated particles into a larger UO2F2 particle.

Fig. 9: JEOL 6310 SEM images in secondary (left) and backscattered (right) electron mode of UO2F2 particles produced in high humidity conditions and stored in the climate chamber for 215 hours at 35 °C and 90 % relative humidity. The back-scattered image clearly shows faded uranium spheroids surrounded by a diffuse uranium layer.

The SEM image in Figure 10 shows submicron uranium particles produced in air with a

relative humidity of around 15 %, which formed chain-like agglomerates up to 20 μm in largest dimension. Although the original chain-like morphology could still be determined for this sample, the contours of the particles comprising the agglomerates faded considerably as the particles 'swelled'. The SEM image in Figure 10 which was recorded 3 days after preparation visualizes how the agglomerates are gradually transformed into discrete spheroids.


Fig. 10: JEOL 6300 SEM image of a UO2F2 particle sample prepared in dry air showing fading of the chain-like agglomerate structure.

Samples for TEM imaging were prepared by directly depositing UO2F2 particles on holey

carbon films with a 300 mesh copper grid (Bal-Tec). The TEM images in Figure 11 illustrate how the particles in these chain-like agglomerates fuse to form larger agglomerates. These samples were stored in a fume hood under ambient conditions in air with a relative humidity between 40 % and 70 %. As UO2F2 is known to be highly hygroscopic, the absorption of atmospheric moisture is assumed to be at the basis of this increase in particle size and the fusion of several individual particles to larger agglomerates.

Fig. 11: TEM image of particle chains comprised of UO2F2 particles in the 50-150 nm diameter size range that have fused to form larger agglomerates.

4.4. Analysis of fluorine in UO2F2 particles as an indicator for particle ageing

As swipe samples from enrichment facilities typically contain uranium particles either with or without a measurable amount of fluorine, the question was raised whether the analysis of fluorine could complement the information on the uranium isotope ratios. The measurement of the amount of fluorine in these uranium-bearing particles could contribute to the interpretation of the analytical results by providing information on the history of the particle, resulting in a more accurate and reliable picture of the past and recent activities at a certain facility.

We determined the amount of fluorine in uranium oxyfluoride particles produced by the aerosol deposition chamber. With the aim of finding a correlation between the age of a particle and the amount of fluorine, particles were characterized by SEM-EDX/WDX, SIMS and μ-Raman spectroscopy, taking into account the influence of certain environmental parameters, such as the exposure to high temperatures and UV-light.

4.4.1. SEM-EDX/WDX analysis The SEM-EDX spectra were used as a first indication for the amount of fluorine in single

uranium oxyfluoride particles produced by the aerosol deposition chamber. The relative amount of fluorine in the particles produced by the aerosol deposition chamber was characterized using a JEOL 6310 SEM-EDX instrument (SCK•CEN, Mol, Belgium) and the scanning electron microscope available at IRMM, equipped with an energy- and wavelength-dispersive spectrometer (FEI Quanta 200 3D, EC-JRC-IRMM, Geel, Belgium). The electron beam current was set at 1 nA, using an electron acceleration voltage of 20 kV.


In Figure 12, the EDX spectrum of clusters of particles is depicted. Uranium (3.07 keV, 3.34 keV), oxygen (525 eV) and fluorine (677 eV) were found to be the main particle constituents and this is similar to the particles found in swipe samples.

Fig. 12: FEI Quanta 200 3D SEM-EDX spectrum of clusters of uranium particles showing uranium, oxygen and fluorine as main particle components. The high intensity peak around 280 eV (out of scale) is attributed to carbon from the graphite planchet. Sodium is present as a contaminant. The Mα and Mβ lines of uranium were remeasured with a higher spectral resolution using WDS. The inserted SEM image shows the outer contours of the X-ray interaction volume at 20 kV for the analyzed particle clusters.

The high intensity carbon peak at 277 eV was produced by the graphite planchet, which is part of the X-ray interaction volume, as shown by the inserted SEM image in Figure 12. The sodium peak on the other hand was present as a contaminant.

The EDX spectrum of the uranium Mα and Mβ peaks was compared to the high resolution WDX spectrum recorded with a PET crystal. Although the electron acceleration voltage was kept at 20 keV, the current intensity was increased to approximately 5 nA for these WDX measurements. The spectrum was recorded for a preset time of 150 s with a dead time of around 50 %. This spectrum showed two distinct uranium peaks at 3.07 keV and 3.34 keV. This combined SEM-EDX/WDX spectrum therefore demonstrated the ability of the system to detect fluorine and uranium in a single particle with a high spectral resolution.


4.4.2. Micro-Raman analysis Micro-Raman spectroscopic measurements make a valuable contribution to the

SEM-EDX/WDX and SIMS analysis by providing information on the molecular structure of micrometer-sized particles. Using µ-Raman spectroscopy, changes in the chemical structure of the uranium particles can be studied as well.

In spite of the information µ-Raman analysis can provide, only few results have been reported in the literature on the hydrolysis products of UF6 using this technique. Although Bostick and Armstrong did mention the presence of an intense signal at 868 cm-1 in the Raman spectra of relatively large crystals of α-phase UO2F2·1.5H2O [8, 9], the μ-Raman signals could often not be distinguished from the background due to the very small particle size of the fallout material. Furthermore, the interpretation of the Raman spectra is not straight-forward and requires the availability of standards or references from literature.

Fig. 13: FEI Quanta 200 3D SEM image at 1000× magnification showing one quadrant of a graphite planchet containing uranium particle agglomerates. Structures in the graphite surface and glass pieces were used for particle relocation on the optical microscope images for Raman measurements.

For the µ-Raman measurements described in this section, the Renishaw inVia µ-Raman instrument at Antwerp University was used to characterize the particles produced by the aerosol deposition chamber. The location of the micrometer-sized uranium particles on the graphite surface turned out to be one of the major challenges for the mirco-Raman analysis of these samples. Images of the samples were obtained by an optical microscope that is part of the micro-Raman instrument. The depth of field and the maximum magnification that can be achieved with the optical microscope are much lower compared to the electron microscope images. In addition, no compositional contrast can be obtained. In order to overcome these issues, samples with a high particle concentration were analyzed at the maximum magnification of 1000×. To facilitate particle relocation, the graphite planchets were marked with a cross, dividing the graphite surface into 4 quadrants (Fig. 13). By comparing the images of the optical microscope with the images obtained from the SEM, the uranium particles could be relocated to a certain extent. Glass pieces and characteristic structures in the graphite surface served as an additional reference to relocate the particles on the optical microscope images.


The graphite planchets containing the uranium particles were directly inserted in the instrument and for each sample between 6 and 16 particles were analyzed individually. Both the 785 nm and 514 nm lasers were used with a spot size of approximately 1 µm. The instrument was operated in standard confocality mode and Raman spectra were recorded between 1200 cm-1 and 200 cm-1 to cut off the high intensity carbon peaks around 1300 cm-1 and 1600 cm-1 and the drop in intensity around 100 cm-1 due to the filter blocking the incident laser beam. The exposure time to record one spectrum was set to 20 s. Spectra were accumulated to improve the signal-to-noise ratio.

865 cm-1

1000

2500

4000

5500

7000

200 400 600 800 1000 1200

Raman shift (cm-1)

Cou

nts

Fig. 14: Micro-Raman spectrum of a single uranium particle produced by the aerosol deposition chamber. The peak at 868 cm-1 is characteristic for UO2F2.

A typical spectrum of the particles produced by the aerosol deposition chamber is depicted in Figure 14. This spectrum was recorded using the 785 nm laser on particle agglomerates produced in air with a relative humidity of 15 % (cf. Fig. 4). A total of 8 particles was analyzed on this sample, all showing a distinct peak around 868 cm-1, attributed to the symmetric stretching frequency of the uranyl ion in UO2F2.

Previous studies showed that UO2F2 is converted to U3O8 by exposure to high temperatures. The thermal decomposition of UO2F2 to U3O8 was found to occur at temperatures exceeding 300 ºC and is assumed to proceed as follows [7, 10]:

4UO2F2 U3O8 + UF4 + 2F2

The effect of high temperature on UO2F2 decomposition was studied in particle samples produced by the aerosol deposition chamber that were heated in a furnace at 350 ºC for a period of 4 to 6 hours. In total, 50 annealed particles were analyzed.


242 cm-1

412 cm-1

482 cm-1

866 cm-1803 cm-1

0

1000

2000

3000

4000

100 300 500 700 900 1100

Raman shift (cm-1)

Cou

nts

U3O8 reference heated sample

Fig. 15: Micro-Raman spectrum of a uranium particle heated at 350 ºC for 6 hours (red) compared to the spectrum of a U3O8 reference sample. In addition, the spectrum shows a very weak peak at 866 cm-1 attributed to UO2

2+ in UO2F2.

Comparison with a U3O8 reference sample showed that in 85 % of the annealed particles distinct U3O8 bands were detected, allowing a typical accuracy of ± 5 cm-1. The effect of high temperature exposure on UO2F2 decomposition was therefore clearly demonstrated by these measurements.

Then again, in over 90 % of the analyzed particles a symmetric uranyl stretching frequency attributed to UO2F2 was detected around 866 cm-1 in addition to the U3O8 features. The large variations that were observed in the intensity of the UO2F2 peak were assumed to result from variations in the particle size and in the proportional amount of UO2F2 relative to U3O8.


4.4.3. SIMS analysis SIMS measurements carried out at QinetiQ (Malvern, UK) aimed to compare the relative

amount of fluorine in UO2F2 particles aged in laboratory and UV-illuminated ambients. SIMS analysis however, allowed the detection of both elemental and molecular compounds. The high sensitivity of the SIMS instrument facilitated the semi-quantitative determination of the relative amount of fluorine in these UO2F2 particles while maintaining a spot size of a few micrometers.

SIMS ion-probe measurements were carried out on individual particles using an 8.5 kV O2

+ primary ion beam at a current of 2 nA in a focused spot, with an estimated diameter of 10 μm. UO2F2 particle samples were prepared from the controlled hydrolysis of UF6 in air with a relative humidity of approximately 70 % using the aerosol deposition chamber. A total of 12 UO2F2 particle samples was analyzed, including 2 particle samples that were heat-treated and 3 samples that were exposed to several weeks of UV-light. In addition to these UO2F2 particle samples, one UF4 sample stored in a laboratory environment for over 2 years was added as a reference level for fluorine and was used to test both the repeatability of the SIMS UF4 spectra and their quantitative distinctiveness from UO2F2. The samples and their characteristics are summarized in Table 2. Sample 3 was re-measured after storage in a vacuum dessicator and this measurement was registered as sample 5.

Sample Type Ageing Storage Conditions

1 UF4 29 months Closed unsealed box

2 UO2F2 2 weeks Vacuum desiccator, no light

3 UO2F2 2 months 2 weeks in open box, no light

6 weeks vacuum desiccator, no light

4 UO2F2 2 months 2 weeks in open box

6 weeks vacuum desiccator, no light

5 UO2F2 3 months Repeat of sample 3

Additional 1 month vacuum desiccator, no light

6 UO2F2 11 months Closed transparent box in fume hood

7 UO2F2 16 months Closed but unsealed transparent box

8 UO2F2 16 months Closed but unsealed transparent box

9 UO2F2 3 weeks UV exp Open box

10 UO2F2 4 weeks UV exp Open box

11 UO2F2 3 months UV exp Open box

12 UO2F2 4 months

65 °C for ~1 hour Heated in oven at 65 °C followed by 4 months

storage

13 UO2F2 350 °C for 6 hours Heated in oven at 350 °C for 6 hours

Table 2: SIMS ion-microprobe sample list with 1 UF4 and 12 UO2F2 particle samples.


The average values for the peak heights were calculated from the measurement of 4 to 7 individual particles on each sample. The data were obtained by cycling the masses 238 (U), 239 (UH), 254 (UO), 257 (UF), 270 (UO2), 273 (UOF) and 276 (UF2) 10 times each to reveal any ratio variations with sputtering. The mean values of the fluorine-containing uranium ions were obtained from the summed counts of 8 cycles, i.e. the interpolated values of the 10 cycles collected. The intensities of these fluorine-containing uranium compounds were then plotted relative to the peak height ratio on m/z 238, attributed to the 238U+ signal (Fig. 16). The summed counts collected on mass 238 varied from 11 000 to 1 200 000 counts.

To minimize the contribution of 235UOF and 235UF2 ions to the signal intensity at respectively m/z 270 (238UO2) and 273 (238UOF), the n(235U)/n(238U) ratio of the UF6 used for the hydrolysis was limited to 0.0016742(28).

UV

4w

ks

16 m

ths

2 m

ths

2 m

ths

UF 4

29

mth

s

11 m

ths

16 m

ths

3 m

ths

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°C

2 w

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3 w

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C

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0 2 4 6 8 10 12 14

Sample

Rel

ativ

e In

tens

ity

257 UF

276 UF2

273 UOF

254 UO

270 UO2

Fig. 16: Cameca 4f SIMS ion microprobe measurements on m/z 254, 257, 273 and 276 plotted relative to the intensity of m/z 238 (log scale) for the samples listed in Table 2.

A general trend in this spectrum is the low variability in the uranium oxide signal. The relative peak height ratio at m/z 254 varied not more than a factor 3 for all samples, independent of the age or the storage conditions, and this confirmed the SIMS measurement repeatability. The relative uranium oxide signals were inherently strong, up to 3 times as strong as the uranium signal at m/z 238, due to the oxygen primary ion bombardment. For reasons of clarity, the relative peak intensity of the signal at mass 270 (UO2) was omitted from the plot in Figure 16 as it generally tracked the uranium oxide signal, even though with a much lower signal intensity. The UH+ signal at m/z 239 was also excluded from the graph as the relative peak heights were generally stable, varying between 0.0017 and 0.0057 and this independent of the relative amount of fluorine.

The fluorine-containing uranium compounds on the other hand showed significant differences between storage conditions. Analogous to the SEM-EDX and micro-Raman measurements, the results of these SIMS measurements are discussed in separate sections for the effects of prolonged storage, exposure to UV-light and high temperatures.

For the SIMS measurements performed on UO2F2 particle samples not older than 3 months (sample 2-5), the average 257(UF)/238U ratio varied between 0.12 ± 0.11 (sample 3) and


0.20 ± 0.12 (sample 4). The standard deviation on this ratio, printed in bold in Figure 16, shows a large variability in the 257(UF)/238U ratio measurements. This wide range in values resulted mainly from the large variations in the intensity on m/z 257 between particles from the same sample. In general, these variations far exceeded the cycle-to-cycle variations resulting from the ion bombardment and the exposure to high vacuum.

The smallest error bars were obtained from samples showing a general uniform uranium background, instead of distinct particles (Fig. 17). This is also the case for sample 5, where the uranium film that was formed on the sample's surface homogenized the particle composition and reduced the effects of particle morphology on the SIMS ionisation and detection efficiency. The ion images recorded during SIMS depth profiling on an area of 250 µm show that this uranium film is relatively thins and sputters away quickly to show particles, the largest of which survive the longest (Fig. 18). The process and storage conditions that have led to the formation of this uranium film are still under investigation. The highly hygroscopic character of the UO2F2 particles might explain this phenomenon.

Fig. 17: Cameca 4f SIMS 150 µm RAE image at m/z 238 showing a general background of uranium (uranium film) in addition to the uranium particle in the centre (bright red).

Fig. 18: Cameca 4f SIMS (QinetiQ) 250 µm RAE images on m/z 238 at different time intervals during depth profiling. The uranium film covering the surface is gradually sputtered away, which makes the uranium particles to appear more clearly in the ion image.

On average however, the values for the 257(UF)/238U ratio of samples 2-5 were within the same range, with only a relatively small deviation from the UF4 reference level at 0.36 ± 0.13. This implied that the SIMS measurements were not able to differentiate the samples stored


between 2 weeks and 3 months, based on their relative peak height ratios of the fluorine-bearing uranium compounds.

Then again, clear signs of particle ageing were detected in the particle samples stored between 11 and 16 months (sample 6-8). For the samples 6-8, the average 257(UF)/238U ratio decreased by one order of magnitude compared to the particle samples stored for a period between 2 weeks and 3 months. It should be noted however that within this group of aged particles the 257(UF)/238U ratio for the sample that was stored for 11 months (sample 6) was significantly lower compared to the samples that were stored for 16 months. This difference in relative amount of fluorine might be related to the difference in storage conditions between samples.

The effect of UV-light on the amount of fluorine was also investigated using SIMS relative peak height measurements. While the samples measured shortly after preparation were protected from light to eliminate the influence of UV-light on UO2F2 decomposition, 3 particle samples (sample 9-11) were exposed to continuous UV-radiation for respectively 3 weeks, 4 weeks and 3 months.

When comparing these UV-exposed samples to the samples that were measured not more than 3 months after preparation (sample 2-5), a significant decrease in the relative peak heights of the fluorine-containing uranium compounds was observed. For the samples that were exposed to UV-light for 3 to 4 weeks (sample 9-10), the 257(UF)/238U ratio decreased by one order of magnitude, to a level comparable to the aged UO2F2 samples (sample 6-8) discussed in the previous section. For sample 11, which was continuously exposed to UV-radiation for 3 months, the UO2F2 decomposition was even more pronounced: the 257(UF)/238U ratio dropped over 2 orders of magnitude compared to the fresh UO2F2 particles, to a value of 0.00079 ± 0.000085, which is the lowest average 257(UF)/238U ratio of all 12 samples. These measurements clearly demonstrated the effect of UV-light on UO2F2 decomposition, accelerating the natural ageing process of uranium oxyfluoride particles and its accompanied loss of fluorine. It should be pointed out however, that even after a continuous exposure to UV-light for a period of 3 months, the residual amount of fluorine was still detectable by SIMS and this can be of potential use in the context of the analysis of environmental swipe samples.

In general, the ageing of UO2F2 under UV-exposure proceeded much faster than in normal laboratory conditions, although the same general trends were observed: analogous to the particles that were not exposed to UV-light, the SIMS relative peak height measurements could generally not differentiate small variations in ageing time. A prolonged UV-exposure of 3 months on the other hand, showed a distinct decrease in the relative amount of fluorine and this was also observed for the particles stored in normal laboratory conditions for at least 11 months.

Uranium oxyfluoride particles recovered from swipe samples can get exposed to high temperatures through the exposure to sunlight or during sample preparation, where the graphite planchet is often heated to approximately 100 °C to burn off residual organics.

Two UO2F2 particle samples (sample 12-13) prepared by the aerosol deposition chamber were therefore heated to respectively 65 °C and 350 °C and the relative peak heights of their uranium fluorine compounds were determined (Fig. 16). Sample 12 was heated to approximately 65 °C and then stored for 4 months prior to analysis. Although a large standard deviation was obtained on the average value for the 257(UF)/238U ratio, the relative amount of fluorine showed a considerable decrease compared to samples 2-5, which were measured not more than 3 months after preparation. The heating that was applied in addition to the storage time caused the relative amount of fluorine to decrease to a level that was comparable to samples stored between 11 and 16 months.

By applying a more severe heat-treatment of 350 °C for 6 hours, the average 257(UF)/238U ratio decreased to 0.0018 ± 0.00031. This type of heat-treatment substantially accelerates the conversion of UO2F2 to U3O8, although a small peak around 866 cm-1 could still be detected in the Raman spectrum. The SIMS measurements on sample 13 were therefore in full agreement


with the Raman observations as fluorine was still detected in this sample, albeit at a very low level.

The 276(UF2) and 273(UOF) relative peak height ratios were not explicitly discussed in this section as they generally tracked the 257(UF) signal. The conclusions that were made for the 257(UF)/238U ratio therefore also apply for the 276(UF2)/238U and 273(UOF)/238U ratio peak height ratios even though the effects of ageing were more pronounced for the 276(UF2)/238U ratio due to the additional fluorine in 276(UF2). The 273(UOF)/238U ratio was at least as strong as the 257(UF)/238U ratio, as expected from the use of a primary O2

+ ion beam.


5. CONCLUSIONS

The aerosol deposition chamber developed at the IRMM for the production of uranium reference particles successfully produced UO2F2 particles with well-defined uranium isotope ratios. By starting from uranium hexafluoride, the composition and chemical structure of the particles produced by the chamber was found to be similar to the particles found at enrichment facilities. The experiments carried out using the aerosol deposition chamber at varying humidity demonstrated that the particles formed at 15 % relative humidity have a substantially different morphology from the particles produced at 60 %, and this confirmed the findings of Pickrell, reported in the early 1980s. Although the morphology of the particles produced was related to the humidity of the air inside the chamber, the different particle morphologies were comparable to those of the particles sampled at enrichment facilities. In addition, the size range of the particles produced is also in good agreement with the particles recovered from swipe samples.

The application of SEM-EDX, μ-Raman and SIMS for the analysis of particles with a diameter of 1 μm or less was not at all straight-forward. The combination of these techniques however provided a detailed picture of the chemical composition of the uranium oxyfluoride particles produced by the aerosol deposition chamber and their decomposition over time. µ-Raman, SEM-EDX and SIMS measurements were used to verify how the particle ageing process is influenced by the storage time and the exposure to heat and ultraviolet light. The amount of fluorine in oxyfluoride particles was evaluated and served as an indicator for the particle age. Although large variations were observed in the relative amount of fluorine within particles from the same sample, general trends in particle ageing were identified. The effect of the exposure to high temperatures and ultraviolet light on UO2F2 decomposition was expressed in a decrease in the amount of fluorine and could be demonstrated by all three techniques.

The experiments carried out in the climate chamber on particles produced by the aerosol deposition chamber clearly demonstrated the effect of storage conditions on particle morphology. The storage of discrete uranium spheroids in an atmosphere of 90 % relative humidity at 35 ºC caused severe fading of the particle contours in addition to the formation of a uranium film that covered a large area of the planchet surface. For the chain-like agglomerates prepared in dry air, these particle morphology changes were even more pronounced, as the chain-like agglomerate structure could no longer be detected after 600 hours in an atmosphere of 35 ºC and 60 % humidity. At moderate temperature and humidity levels however, no evidence of morphological changes was detected for the uranium spheroids produced in high humidity conditions. The chain-like agglomerates on the other hand, seemed to be more sensitive to atmospheric moisture, as SEM and TEM images from particle samples stored in a normal lab environment showed the fusion of submicron particles into larger UO2F2 particles.

The results obtained from this Exploratory Research resulted in 2 peer-reviewed publications [11, 12], the 2007 IRMM excellence award for best young scientist, and a successful PhD defence at the University of Antwerp in February 2008 [13].

This Exploratory Research project has been extended to further optimise the aerosol deposition chamber and investigate the long-term stability of these uranium particles. Additional research on the correlation of fluorine to the age of the particles will be carried out. IRMM will continue its collaboration with the University of Antwerp en ITU on the characterisation of the particle morphology and composition. A large part of the Exploratory Research will focus on the development of double deposition particles, prepared from the subsequent hydrolysis of 2 different UF6 materials. This will allow us to study the effect of isotopic mixing.

The new SEM installed at IRMM in June 2008 is equipped with a micro-manipulator that will be used to transfer particles from a carbon planchet onto a TIMS filament. In this way, the isotopic composition of individual particles can be measured with high accuracy using the Triton TIMS instrument at IRMM.


Finally, the transfer of particles from swipes by the vacuum impactor technique will be studied. The characterization of particles from the Urenco enrichment facility will allow us to compare the morphology of real-life particles to the particles produced by the aerosol deposition chamber.

6. REFERENCES

[1] D. L. Donohue, Key tools for nuclear safeguards inspections: advances in environmental sampling strengthen safeguards, IAEA Bulletin, 44 (2002) pp. 17-23.

[2] E. Kuhn, D. Fischer, M. Ryjinski and M. Taylor, Recent progress in the IAEA's environmental sampling for safeguards, ESARDA Symposium on Safeguards and Nuclear Material Management (1999) Seville, Spain.

[3] P. M. L. Hedberg, K. Ingeneri, M. Watanabe and Y. Kuno, Isotopic measurements of U particles by secondary ion mass spectrometry (SIMS), Institute of Nuclear Materials Management Annual Meeting (2005) Phoenix, AZ USA.

[4] P. Zahradnik, D. Donohue, R. Perrin, H. Lindauer and D. Klose, The preparation and use of environmental reference samples by the IAEA, ESARDA Symposium on Safeguards and Nuclear Material Management (1999) Seville, Spain.

[5] R. Kips, A. Leenaers, G. Tamborini. S. Van den Berghe, R. Wellum. P.D.P. Taylor, Characterization of uranium particles produced by hydrolysis of UF6 using SEM and SIMS, Microscopy & Microanalysis, 13 (2007) pp. 156-164.

[6] P. W. Pickrell, Characterization of the solid, airborne materials created by the interaction of UF6 with atmospheric moisture in a contained volume, K/PS-144-DE82 015436, Union Carbide Corporation, Nuclear Division, Oak Ridge Gaseous Diffusion Plant, (1982).

[7] J. A. Carter and D. M. Hembree, Formation and characterization of UO2F2 particles as a result of UF6 hydrolysis, Task A.200.3, K/NSP-777, Oak Ridge Gaseous Diffusion Plant, (1998).

[8] W. D. Bostick, W. H. McCulla and P. W. Pickrell, Sampling, characterization and remote sensing of aerosols formed in the atmospheric hydrolysis of uranium hexafluoride, Journal of Environmental Science and Health, A20 (1985) pp. 369-393.

[9] D. P. Armstrong, R. J. Jarabek and W. H. Fletcher, Micro-Raman spectroscopy of selected solid UxOyFz compounds, Applied Spectroscopy, 43 (1989) pp. 461-468.

[10] J. J. Katz and E. Rabinowitch, The chemistry of uranium: The element, its binary and related compounds, Dover Publications (1961) New York.

[11] R. Kips, R. Wellum, Fluorine as a safeguards tool for age dating of uranium oxyfluoride

particles?, ESARDA Bulletin, (2008) in press.

[12] R. Kips, A. J. Pidduck, M. R. Houlton, A. Leenaers, J. D. Mace, O. Marie, F. Pointurier, E. A. Stefaniak, P. D. P. Taylor, S. Van den Berghe, P. Van Espen, R. Van Grieken, R. Wellum, Determination of fluorine in uranium oxyfluoride particles as an indicator of particle age, submitted to Spectrochimica Acta part B


[13] R. Kips, PhD. thesis: Development of uranium reference particles for nuclear safeguards and non-proliferation control, Department of Chemistry, Antwerp University, (2008).

EUROPEAN COMMISSION JOINT RESEARCH CENTRE Institute for Reference Materials and Measurements Neutron physics

NINES (NItrogen NEutron Source): A monoenergetic neutron source in the energy

range 8-14 MeV

Date: 13/06/2008

Authors: G. Giorginis, N. Kornilov, M. Kievets, V. Khryachkov, F.-J. Hambsch, S. Oberstedt, G. Lövestam

Revised by: P. Rullhusen

Approved by: P. Rullhusen

TABLE OF CONTENTS

1. SUMMARY ..................................................................................................................................... B-2

2. INTRODUCTION........................................................................................................................... B-3

3. EXPERIMENTAL METHOD....................................................................................................... B-3

4. PSD AND TOF SPECTRA............................................................................................................. B-5

5. ENERGY SPECTRA...................................................................................................................... B-8

6. CROSS SECTIONS ...................................................................................................................... B-12

7. NEUTRON SOURCES................................................................................................................. B-14

8. CONCLUSION ............................................................................................................................. B-15

9. REFERENCES.............................................................................................................................. B-16

NINES (NItrogen NEutron Source): A monoenergetic neutron source in the energy range 8-14 MeV B-2/16

1. SUMMARY

The 14N(d,n0)15O and 15N(d,n0)16O reactions were studied at IRMM as possible neutron sources in the energy range 8-14 MeV. The time-of-flight and pulse shape discrimination techniques were used for the spectrometry of neutrons produced by bombarding a nitrogen gas target with a pulsed deuteron beam. Ground state neutrons, which are of interest, were clearly separated from excited state neutrons and gamma ray background was effectively suppressed. The well known D(d,n)3He reaction was measured under the same conditions for comparison and normalisation. Neutron background from implanted deuteron atoms was high with a heavily used tantalum beam stop but it was minimised by replacing the old beam stop with a fresh one. The IRMM measurements confirmed the low neutron yield of the nitrogen reactions of older publications, where a limited usefulness of these reactions as neutron sources was suggested. There are nuclear data measurements however where a low neutron yield can be compensated by optimising other experimental parameters such as increasing the number of target atoms. Typical cases are measurements of the 16O(n,α)13C and 12C(n,α)9Be cross sections by using gas oxygen and carbon targets. The number of atoms in gas targets can be by a factor of 100 larger than in the normally used thin solid targets as has been demonstrated at IRMM.


2. INTRODUCTION

There is a strongly expanding importance of fast neutrons in a number of applications such as accurate cross section measurements for nuclear safety, nuclear reaction standards, radiation dosimetry, and radiation therapy. Monoenergetic neutron sources are used in most of the cases. For this purpose hydrogen isotopes and other light elements are bombarded with accelerated hydrogen ions. Up to 5 MV electrostatic accelerators routinely produce monoenergetic neutrons by using the reactions: 7Li(p,n)7Be, T(p,n)3He, D(d,n)3He for energies up to 8 MeV and T(d,n)4He for the energy region 14-20 MeV. However there is no monoenergetic neutron source in the energy range 8-14 MeV up to now. The reactions 14N(d,n0)15O with Q=5.073 MeV and 15N(d,n0)16O with Q=9.903 MeV could be used to fill this energy gap. Some investigations were performed already fifty years ago [1,2]. The published cross sections of these reactions were quite low, giving low neutron fluxes and, thus considered being unsuitable as neutron sources. There are nuclear data measurements however where a low neutron flux can be balanced by varying other experimental parameters such as increasing the number of target atoms. Typical cases are measurements of the 16O(n,α)13C and 12C(n,α)9Be cross sections by using gas oxygen and carbon targets. The number of atoms in gas targets can be by a factor of 100 larger than in the normally used solid targets as has been demonstrated at IRMM [3]. On the other hand new accelerator designs will hopefully lead to higher intensities of charged particle beams so that higher neutron fluxes than presently available can be obtained.

The aim of the current exploratory research project was to study the feasibility of 14N(d,n0)15O and 15N(d,n0)16O reactions as neutron sources in the energy gap 8-14 MeV by using state-of-the art neutron spectrometry at the IRMM Van de Graaf accelerator. The technique, measurements, analysis of recorded data, results, and conclusions are presented in this report.

3. EXPERIMENTAL METHOD

A pulsed deuteron beam with a frequency of 1.25 MHz or equivalently 800 ns pulse length and 1.5-2 ns pulse width was produced at the IRMM Van de Graaff accelerator and directed to a gas target installe at the 0o beam line. The 4 cm long gas cell had a tantalum beam stop, a molybdenum entrance window of 5 μm thickness, and was filled with 20 kPa (0.2 bar) nitrogen or deuterium gas. The incident deuteron energy was corrected for the energy loss traversing the molybdenum foil and one-half of the target gas length.

A NE213 equivalent liquid scintillator (LS301, 101.6 mm diameter, 50.8 mm thickness, produced by SCIONIX) coupled to a XP4312/B photomultiplier and installed at 0o relative to the deuteron beam was used as neutron detector. This type of detector is characterised by a fast response to nuclear radiation, which makes it suitable for high resolution time measurements. Furthermore the NE213 response as function of time has significantly different shapes for neutrons and gamma rays, which allows for discrimination. Both properties were utilised in order to measure the energy spectra of neutrons from the 14N(d,n)15O and 15N(d,n)16O reactions by the time-of-flight (TOF) method and effectively suppress the accompanying gamma ray background by the pulse-shape discrimination (PSD) technique.

The principle of theTOF measurement is schematically illustrated in Fig. 1. The flight time Tn of a neutron travelling the distance L between its creation (gas target) and the


detector (NE213) was measured. The beginning of Tn was determined by the deuteron beam pulse associated with the neutron emission. A pick-up electrode at the gas target (not shown) was used to measure this pulse. The end of Tn was determined by the neutron signal from the NE213 scintillator produced upon interaction with the arrived neutron. In the current study the neutrons were fast and had velocities between 10% and 20% of the speed of light c=3x1010 cm/s. For this reason the relativistic equation in Fig. 1 was used in order to obtain the neutron energy En from the time-of-flight Tn.

14N, 15N, D gas, p=20 kPa

pulsed d beam n

L=413.5 cm

Tn

n detector

Mo (5 µm)Ta (0.5 mm)

pick-up neutron

f=1/τ=1.25 MHz

τ=800 ns, Δτ=1.5-2 ns

NE213

⎟⎟⎟⎟⎟⎟

⎠

⎞

⎜⎜⎜⎜⎜⎜

⎝

⎛

−

⎟⎟⎠

⎞⎜⎜⎝

⎛−

=

⎟⎟⎟⎟⎟

⎠

⎞

⎜⎜⎜⎜⎜

⎝

⎛

−

⎟⎠⎞

⎜⎝⎛−

= 1

1

11

1

12

2

2

2

n

n

n

nn

cTL

cm

c

cmEυ

Fig. 1: Schematics of the time-of-flight method

The block diagramme of the experimental setup is shown in Fig. 2. Details can be found elsewhere [4]. Here the description is restricted to minimum which is needed to understand the measured spectra. The signal from the pick-up electrode, which occurred first, was delayed by a time Td (500 ns) and used as the stop pulse of the TOF measurement. The current signal from the photomultiplier anode (PM) of the neutron detector, which occurred a time Tn after the pick-up signal, was used as the start pulse. This reversed start/stop scheme reduces dead time in the TAC. The count rate of the NE213 signals was much lower than the frequency of the pick-up signals. Using the latter as start pulses would keep the TAC most of the time busy with false events (pick-up pulses without associated neutron signals) with the result of an increased dead time. This would allow only a small number of the true events (pick-up pulses with associated neutron signals) to be recorded. The time scale is inverted with the reversed start/stop scheme because what is measured is not directly the flight time Tn but its complement Td–Tn relative to the delay time Td (see bottom of Fig. 2).

A small part of the anode current was used for the neutron-gamma discrimination. After integration in the charge sensitive preamplifier (Q) the signal passed the chain of electronic units of the pulse-shape-discrimination (DLA, PSA, TAC) and produced a signal (PSD) with amplitude corresponding to the decay time of the scintillator, which is characteristic of the detected radiation. One DLA output signal was used for pulse height (PH) measurements.

A calibrated 252Cf source was placed at the position of the gas target before and after measurements with the accelerator in order to determine the neutron efficiency of the NE213 detector. The 252Cf source was installed in a fission ionisation chamber (IC) with a very thin stainless steel wall. Fission fragments and neutrons are produced by


spontaneous fission of 252Cf and the number of neutrons per fission as function of neutron energy is well known. In the efficiency measurements the electronic chain of the pick-up signal up to the input of the delay module (500 ns) was replaced by the electronic chain of the fission signal, so that operation of the experimental set up with the 252Cf source was the same as with the pulsed deuteron beam.

pick-up electrode

252Cf IC

NE213 PMAnode

10 kΩ

50 Ω

50 Ω

PA

PA FA

FA

Q

CFD

CFD

CFD CFD

CFD

TAC

TAC

ADC

ADCPSADLA

DG

SC

delay 500 ns

STOP

STARTTOF

PSD

ADC

BIPUNIP

PH

TnTd

pick-up neutron pick-upTd -Tn

t

u

Fig. 2: Block diagramme of the experimental setup. Abbreviations have the following meanings: PA=preamplifier, FA=fast amplifier, CFD=constant fraction discriminator, IC=ionisation chamber, PM=photomultiplier, SC=short cable, TAC=time-to-amplitude converter, ADC=analog-to-digital converter, DLA=delay line amplifier, UNIP=unipolar, BIP=bipolar, PSA=pulse shape analysis, TOF=time of flight, PSD=pulse shape discriminationl, PH=pulse height, DG=delay generator

The data from the three ADC's were collected event by event in the so called list mode by the LISA data acquisition software [5]. Each event was stored on hard disk with triple information (TOF, PSD, and PH). The stored data were replayed later for off-line analysis.

4. PSD AND TOF SPECTRA

Production of neutrons is usually accompanied by unwanted gamma ray background. This was the case during measurements of the 14N(d,n)15O and 15N(d,n)16O reactions. Gamma rays were promptly emitted simultaneously with neutrons upon impinging of the deuteron beam on the gas target. Both radiations were identified and analysed by the PSD system as described in the previous section. Fig. 3 shows a typical two-dimensional spectrum of pulse height (PH) versus PSD amplitude obtained from a measurement with


the 252Cf source. The PSD amplitude is a measure of the rise time of the integrated scintillation light and is different for neutrons and gamma rays. By putting windows on the two spectrum groups neutrons were separated from gamma rays and TOF spectra were produced for both radiations.

350 360 370 380 390 400 410

100

200

300

400

500

600252Cf neutron source

neutrons

gamma rays

PSD amplitude (channel)

Pul

se h

eigh

t (ch

anne

l)

Fig. 3: Two dimensional pulse height versus PSD amplitude spectrum of the 252Cf neutron source

Figs. 4 and 5 show TOF spectra obtained for 14N(d,n)15O and 15N(d,n)16O with a deuteron energy Ed=5.09 MeV and Fig. 6 for D(d,n)3He with Ed=5.0 MeV. Although unwanted, the prompt gamma rays offer a unique signature for the determination of the flight time Tn of the neutrons. The gamma rays travel with the speed of light c=3x1010 cm/sec the same distance L as the neutrons so that their flight time Tg is simply equal to L/c (=13.78 ns in the current case). The gamma ray signals propagate through the same electronic chains and therefore bear the same delays as the neutron signals. For this reason the flight time of the neutrons is determined by the distance between the neutron and the gamma ray lines with peak positions at Td-Tn and Td-Tg, respectively. The conversion of the time scale from channels into time units (ns) was performed as described in [4].

The line in the neutron spectrum at the position of the prompt gamma ray peak is not due to neutrons but to unresolved gamma rays from the overlapping region of the PSD spectrum (see Fig. 3). It does not influence the neutron spectrum due to the large separation distance from the nearest neutron line. The lines in the gamma ray spectrum are likewise not due to gamma rays but to unresolved neutrons. Their intensities are low compared to the corresponding resolved neutron lines. A full identification of the neutron lines is given in the next section.


1000 1100 1200 1300 1400 1500 1600 1700101

102

103

104

105

106

82.39 ns

Td-TgTd-Tn

prompt gammas

14N(d,n0)

IRMM Dec2007d+natN, Ed=5.09 MeV

Cou

nts

(rel

. uni

ts)

Time (channel)

neutrons gammas

Fig. 4: Time-of-flight spectrum of neutrons and gamma rays emitted by the d+natN reaction for a deuteron energy of 5.09 MeV

1000 1100 1200 1300 1400 1500 1600 1700101

102

103

104

105

106

65.31 nsTd-Tn Td-Tg

15N(d,n0)

prompt gammas

IRMM Dec2007d+15N, Ed=5.09 MeV

Cou

nts

(rel

. uni

ts)

Time (channel)

-neutrons -gammas

Fig. 5: Time-of-flight spectrum of neutrons and gamma rays emitted by the d+15N reaction for a deuteron energy of 5.09 MeV


1000 1100 1200 1300 1400 1500 1600 1700101

102

103

104

105

106

93.53 nsTd-TgTd-Tn

D(d,n)

prompt gammas

IRMM Dec2007d+D, Ed=5.0 MeV

Cou

nts

(rel

. uni

ts)

Time (channel)

neutrons gammas

Fig. 6: Time-of-flight spectrum of neutrons and gamma rays emitted by the d+D reaction for a deuteron energy of 5.0 MeV

5. ENERGY SPECTRA

Neutron energy spectra for 14N(d,n)15O and 15N(d,n)16O with a deuteron energy Ed=5.09 MeV are shown in Figs. 7-8 and for D(d,n)3He with Ed=5.0 MeV in Fig. 9. They were obtained from the neutron TOF spectra shown in Figs. 4-6. All identified signatures for the 14N(d,n)15O and 15N(d,n)16O reactions can be seen in Figs. 7-8. Figs. 10-12 are the same as Figs. 7-9 but in linear yield scale and focussing on the 14N(d,n0)15O, 15N(d, n0)16O, and D(d,n)3He lines of interest, respectively. Neutron background from structural materials is also shown in Figs. 7-12. The energy spectra of background neutrons were measured with the gas target under high vacuum before and after the N(d,n) and D(d,n) measurements. The tantalum beam stop had been utilised in previous measurements, where D(d,n) was used as neutron source. A background reduction was observed when a fresh tantalum beam stop was used. This is demonstrated in Fig. 13 showing background spectra for a deuteron energy of 5.09 MeV. The background in the energy range between the ground state and first excited state 14N(d,n)15O neutrons was reduced by an order of magnitude with the fresh beam stop. It seems that the source of neutron background is implanted deuteron in the tantalum beam stop, which was accumulated with time. The advantage of using fresh beam stops is obvious. Another way to reduce background due to implanted deuterons would be the use of a thin foil instead of a thick beam stop. A foil with a thickness less than the deuteron range in the foil material would allow the deuteron projectiles to pass through the foil and be flushed away by the cooling medium of the gas target (pressurised air or water).


0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18105

106

107

108

109

1010

1011

16O(d,n1)16O(d,n0) D(d,n)

Background

d+natN, Ed=5.09 MeV IRMM Dec2007

14N(d,n7)

14N(d,n0)

14N(d,n4+n5)

14N(d,n3)

14N(d,n1+n2)

12C(d,n0)

Neutron energy (MeV)

Neu

tron

coun

ts (r

el. u

nits

)

Gas target chamber: 20 kPa natN high vacuum

window: 5 μm Mobeam stop: used Ta

Fig. 7: Energy spectrum of 14N(d,n)15O neutrons for a deuteron energy of 5.09 MeV

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18105

106

107

108

109

1010

1011 d+15N, Ed=5.09 MeV IRMM Dec2007

Gas target chamber: 20 kPa 15N high vacuum

window: 5 μm Mobeam stop: used Ta15N(d,n3)

15N(d,n1+2)

15N(d,n4+5)

15N(d,n0)


Neu

tron

coun

ts (r

el. u

nits

)

Fig. 8: Energy spectrum of 15N(d,n)16O neutrons for a deuteron energy of 5.09 MeV


0 2 4 6 8 10 12 14 16 18105

106

107

108

109

1010

1011

Background

Gas target chamber: 20 kPa D high vacuum


IRMM Dec2007d+D, Ed=5.0MeV

D(d,n)

14N(d,n0)


Neu

tron

coun

ts (r

el. u

nits

)

Fig. 9: Energy spectrum of D(d,n)3He neutrons for a deuteron energy of 5.0 MeV

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

5.0x107

1.0x108

1.5x108

2.0x108 d+natN, Ed=5.09 MeV

Gas target chamber: 20 kPa natN high vacuum


IRMM Dec2007

14N(d,n0)


Neu

tron

coun

ts (r

el. u

nits

)

Fig.10: Same as Fig. 7 but in linear scale and focussing on the 14N(d,n0)

15O line


0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

5.0x107

1.0x108

1.5x108

2.0x108

2.5x108

3.0x108 IRMM Dec2007d+15N, Ed=5.09 MeVGas target chamber:

20 kPa 15N high vacuum


15N(d,n0)


Neu

tron

coun

ts (r

el. u

nits

)

Fig.11: Same as Fig. 8 but in linear scale and focussing on the 15N(d,n0)

16O line

0 2 4 6 8 10 12 14 16 18

2.0x109

4.0x109

6.0x109

8.0x109

1.0x1010

1.2x1010

IRMM Dec2007

Gas target chamber: 20 kPa D high vacuum


D(d,n)


Neu

tron

coun

ts (r

el. u

nits

)

d+D, Ed=5.0MeV

Fig.12: Same as Fig. 9 but in linear scale and focussing on the D(d,n) line


0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18105

106

107

108

109

Gas target chamber:

HV, before D&N measurms, Dec2007 HV, after D&N measurms, Dec2007

beam stop: used Ta, window: 5 μm Mo

HV, before D&N measurms, Jul2007 beam stop: fresh Ta, window: 5 μm Mo

(HV=high vacuum, D&N=deuteron and nitrogen measurms=measurements)

IRMM d+Mo&Ta, Ed=5.0 MeV (Dec2007) & 5.09 MeV (Jul2007)


Neu

tron

coun

ts (r

el. u

nits

)

Fig. 13: Energy spectra of background neutrons for a deuteron energy of 5.09 MeV from different measurements with a used and a fresh tantalum beam stop

6. CROSS SECTIONS

The aim of the present work was to investigate the neutron spectra of the 14N(d,n)15O and 15N(d,n)16O reactions and measure their cross sections in the energy region of interest (8-14 MeV neutron energy). Measurements were performed at 2.47, 3.56, and 4.71 MeV effective deuteron energies (energies in the middle of the gas target). Ground state neutrons emitted at 0o had energies of 7.52, 8.63, and 9.78 MeV for 14N(d,n0)15O and 12.27, 13.40, and 14.58 MeV for 15N(d,n0)16O, respectively. The background corrected neutron yields of 14N(d,n0)15O (Fig. 10) and 15N(d,n0)16O (Fig. 11) were normalised to the deuteron beam charge (integrated beam current) and compared to the neutron yields of D(d,n)3He measured at the same deuteron energies. In this way the cross section of the nitrogen reactions were obtained from the known cross section of the deuteron reaction. The results for the 14N(d,n0)15O cross section are shown in Fig. 14 together with old experimental data [1,2,6,7]. Fig. 15 shows results for 15N(d,n0)16O in comparison with data from [1]. The IRMM cross sections deviate by a factor less than two from older values [1] and confirm the small neutron yields of the nitrogen reactions.


0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.50

1

2

3

4

5

6 IRMM 2007 Weil 1958 Morita 1958 Nonaka 1957

14N(d,n0)15O

Cro

ss s

ectio

n (m

b/sr

) at θ

=0o

Deuteron energy (MeV)

Fig. 14: Cross section of 14N(d,n0)15O for θ=0o measured at the IRMM Van de

Graaff accelerator by using natN and D gas fillings and the TOF technique in comparison with other measurements

0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5

0

1

2

3

4

5

6

7

IRMM Dec2007 Weil 1958

Cro

ss s

ectio

n (m

b/sr

) at θ

=0o

Deuteron energy (MeV)

15N(d,n0)16O

Fig. 15: Cross section of 15N(d,n0)16O for θ=0o measured at the IRMM Van

de Graaff accelerator by using 15N and D gas fillings and the TOF technique in comparison with another measurement


7. NEUTRON SOURCES

The suitability of a neutron reaction as monoenergetic neutron source depends on the distance of the neutron group of interest from other neutron groups and on the magnitude of the cross section for the production of this neutron group. Both should be as large as possible. The first excited state is very well separated from the ground state in both 15O and 16O (5.27 and 6.06 MeV spacings, respectively) so that ground state neutrons produced by the 14N(d,n)15O and 15N(d,n)16O reactions are well separated from excited state neutrons (Figs. 7-8). Thus, the first criterion is fulfilled. The mean cross sections of 14N(d,n0)15O and 15N(d,n0)16O are <σ14>=2.95 and <σ15>=3.15 mb/sr, respectively, for deuteron energies 1-5.3 MeV [1]. The corresponding value of D(d,n)3He is <σD>=54 mb/sr so that <σD>/<σ14>=18 and <σD>/<σ15>=17. The second criterion is only weakly fulfilled. That means that the nitrogen reactions are not useful for routine neutron production as is the case, for example, for the D(d,n) reaction, but as mentioned above, there are applications where the low neutron yield can be compensated by optimising other parameters. Examples are cross section measurements of neutron reactions producing charged particles, such as 16O(n,α)13C, 12C(n,α)9Be, and 10B(n,α)7Li. When gas targets, such as CO2, CH4, and BF3, respectively, are used then the number of target atoms can be 100 times larger than those with solid targets. This would balance the low neutron yield of the nitrogen neutron sources. The neutron yields of the nitrogen reactions were calculated in relation to that of the D(d,n) reaction by using the cross section ratios σ14/σD and σ15/σD and the nitrogen cross sections σ14 and σ15 from [1], assuming the number of nitrogen atoms to be identical to the number of deuteron atoms in a 2 mg/cm2 TiD solid target, and a deuteron beam current of 1 µA in both cases. They cover the neutron energy range 8-15 MeV and are shown in Fig. 16 which is the map of monoenergetic neutron sources at the IRMM Van de Graaff accelerator. Hence, for certain applications the previous energy gap 8-14 MeV can be now closed by using the nitrogen reactions investigated in this project as neutron sources, although they are less useful for routine neutron production.


0 2 4 6 8 10 12 14 16 18 20 22105

106

107

108

Energy gap

15N(d,n)16O, Ed=0.9-5.3 MeV, θ=0o14N(d,n)15O, Ed=2.9-5.3 MeV, θ=0o

Monoenergetic neutron sources at the IRMM VdG (calculation)

T(d,n)4He, Ed=1-3.7 MeV, θ=0o

T(d,n)4He, Ed=1-6 MeV, θ=90o

D(d,n)3He, Ed=1-6 MeV, θ=0o

T(p,n)3He, Ep=1.02-6 MeV, θ=0o

Neu

tron

Yie

ld (n

/sr.μ

C)

Neutron Energy (MeV)

7Li(p,n)7Be, Ep=1.9-3.7 MeV, θ=0o

Fig. 16: Neutron yield versus neutron energy obtained for the reactions 7Li(p,n), T(p,n), D(d,n), and T(d,n) by bombarding 2 mg/cm2 LiF, TiT or TiD samples with 1µA proton or deuteron beams. The 14N(d,n0) and 15N(d,n0) yields were obtained by comparison to the D(d,n) yield for the same number of target nitrogen and deuteron atoms and beam current.

8. CONCLUSION

The energy spectra of the nitrogen reactions were measured and the cross sections of the ground state neutron groups determined by using state-of-the art neutron spectrometry at IRMM. The present study confirmed the low neutron yields of these reactions reported in earlier publications. These findings suggest that the nitrogen reactions are not useful for routine production of monoenergetic neutrons, but they can be used in several applications where other parameters can be optimised to compensate the low neutron yields. Such applications are cross section measurements of charged particle emitting neutron reactions on light elements which are very important in nuclear safety calculations. Gas targets can be used in these cases which contain a hundred times more atoms than the routinely utilised thin solid targets. This is a balance for the low neutron yield of the nitrogen neutron sources.

There are no plans for a follow-up of the current investigation as exploratory reseach. It would be interesting however to continue this study within the normal research programme of IRMM in order to measure angular distributions of the nitrogen reactions. This could reveal an angle (or range of angles) of emission at which the cross section is


larger than at presently zero degrees. Such measurements require long beam times which are not available within the one year duration of exploratory research projects.

9. REFERENCES

[1] J.L. Weil and K.W. Jones, Phys. Rev. 112 (1958) 1975

[2] Theo Retz-Schmidt and Jesse .L. Weil, Phys. Rev. 119 (1960) 1079

[3] G. Giorginis, V. Khryachkov, V. Corcalciuc, M. Kievets, "The cross section of the 16O(n,α)13C reaction in the MeV energy range", in Proceedings of the International Conference on Nuclear Data for Science and Technology, April 22-27, 2007, Nice, France, editors O.Bersillon, F.Gunsing, E.Bauge, R.Jacqmin, and S.Leray, EDP Sciences, 2008.

[4] N.V. Kornilov, F.-J. Hambsch, I. Fabry, S. Oberstedt, S. P. Simakov, IRMM internal report GE/NP/01/2007/02/14

[5] A. Oberstedt, F.-J. Hambsch, Nucl. Instr. Meth. A340 (1994) 379

[6] Nonaka, Morita, Kawai, Ischimatsu, Takeshita, Nakajima, and Takano, J. Phys. Soc. Japan 12 (1957) 841

[7] S. Morita, J. Phys. Soc. Japan 13 (1958) 126


Measurement of neutron activation cross section curves using moderated neutron

fields (NAXSUN-II)

G. Lövestam1, E. Birgersson1, J. Gasparro1, M. Hult1, P. Lindahl1, S. Oberstedt1 and H. Tagziria2

1EC-JRC-Institute for Reference Materials and Measurements (IRMM), Retieseweg 111, B-2440 Geel, Belgium

2EC-JRC-Institute for the Protection and the Security of the Citizen (IPSC), Via E. Fermi 1, I-21020 Ispra (VA), Italy

Date: 21/05/2008

Authors: G. Lövestam, M. Hult

Revised by: G. Lövestam, E. Birgersson, J. Gasparro, M. Hult, S. Oberstedt, P. Rullhusen, H. Tagziria, P. Taylor and U. Wätjen

Approved by: P. Rullhusen and P. Taylor

TABLE OF CONTENTS

1. SUMMARY ............................................................................................................C-2

2. INTRODUCTION...................................................................................................C-3

3. METHODS..............................................................................................................C-3

4. EXPERIMENTAL ..................................................................................................C-6

5. RESULTS..............................................................................................................C-15

6. DISCUSSION .......................................................................................................C-22

7. CONCLUSION .....................................................................................................C-24

8. REFERENCES......................................................................................................C-24

Measurement of neutron activation cross section curves using moderated neutron fields (NAXSUN-II) C-2 / 26

1. SUMMARY

A technique for measuring threshold neutron excitation functions using moderated neutron beams is explored. Samples were activated with a set of wide energy neutron fields created by means of the IRMM Van de Graaff (VdG) accelerator and the T(d,n)3He nuclear reaction. The initial mono-energetic neutron spectrum was moderated to broader energy ranges using polyethylene spheres. Measured activities were determined using low background gamma-ray spectrometry and the excitation curves were calculated using spectrum unfolding. The technique was successfully demonstrated on the measurement of the excitation function curves from threshold up to about 17.0 MeV for the 113In(n,n')113mIn and the 115In(n,n')115mIn reactions.


2. INTRODUCTION

Accurate neutron activation cross section data are important in many fields of science. Practical examples are within geology and bore-hole logging, for dosimetry and environmental protection, at fission and fusion reactor installations, and for various research activities. A typical example is the need to provide more and precise estimates of past and future radiation damages to reactor vessels as required by regulatory bodies for granting life-time extension for nuclear power reactors that have reached their designed life-time. These estimates require measurements of the neutron spectra in the reactor which normally is done by foil activation measurements outside the reactor tank.

Several international evaluated activation cross section data libraries have been established which include data measured using more or less mono-energetic neutron beams as the neutron cross section varies with the neutron energy. Excitation functions are modelled by fitting the measured data to nuclear models or, when no or only few data exists, from pure calculations. However, many neutron activation cross section data entered in the data libraries, as well as different modellings of cross section data, show large discrepancies [1]. Furthermore, for a large number of isotopes none, or data from only a few measurements exist. The IAEA Reference neutron activation library [2] lists the 255 activation reactions most used of which about 100 have 5 or less measured data. This indeed reflects the tedious and time-consuming work of measering and evaluating neutron activation cross section data.

At the IRMM, a considerable number of measurements have been performed using quasi mono-energetic neutron beams, see for example Ref. [3]. In this study we explore an alternative technique of using well-defined, wide energy neutron beams for measuring full neutron excitation functions directly. A similar approach, however only applicable to neutrons with energies below 7 MeV, was previously reported by IRMM [4]. Wide energy neutron beams have also been applied for higher neutron energy cross section measurements but in a region where the neutron spectrum is not well known and, thus resulting in high uncertainties [5-6].

3. METHODS

The method is based on the irradiation of a number of identical disks including the isotope of interest using a series of well known but differently moderated neutron fields. The activations of the disks induced by the neutron fields are measured using gamma-ray spectrometry, often in a low-background set-up [7] as the moderated neutron beams may render low activities in the disks. Following the gamma-ray measurements the excitation function is calculated using a spectrum unfolding procedure.

For an activated disk the number of counts, C, in a peak in the acquired gamma spectrum equals:

( ) ( )max1 1 1 ( ) ( )a c m

th

Et t tA a

E

mI NC P e e e j E E dEM

λ λ λγ ε σ

λ− − −= ⋅ − ⋅ − ⋅ ⋅ Φ∫ (1)


where σ(E) is the sought neutron activation cross section data, Φ(E) is the neutron fluence rate per μC ion beam charge [neutrons · cm-2 · μC-1], Emax is the maximum energy in the neutron spectrum and Eth is the threshold energy for the activation reaction. Pγ is the gamma-ray emission probability, ε the full energy peak efficiency for the HPGe-detector, m the mass of the disk, ΙΑ the natural isotopic abundance of the studied isotope, Na Avogadro’s constant, M the atomic weight, λ the decay constant, ta, tc and tm the neutron irradiation (or activation) time, the decay time between irradiation and start of the gamma-ray measurement, and the gamma-ray measuring time respectively, and j the total ion beam charge [μC]. If the neutron fluence rate is known, the only unknown parameter in Eq. (1) is the cross section, σ(Ε), which is to be determined. Eq. (1) can hence be written as:

max

( ) ( )th

E

E

C ab E E dEσ= ⋅ Φ∫ (2)

where

λεγ

1M

NmIPa aA=

( ) ( ) jeeeb mca ttt⋅−⋅−=

−−− λλλ11

To determine a complete cross section data curve, a number of identical disks are irradiated in different neutron fields and Eq. (2) is expanded to:

cmi

ikikk ninkbaC ,1;,1 ==Φ= ∑ σ (3)

Here, Φ and σ are the discrete functions of the neutron fluence and the activation cross section respectively, nm is the number of irradiated disks and nc is the number of bins in the neutron spectra and the final excitation function curve. bk equals:

( ) ( ) kttt

k jeeeb kmkcka ⋅−⋅−= −−− λλλ 11

Furtheron, define:

aCC k

k =′ (4)

kikki b Φ=Φ′ (5)

and Eqs. (3), (4), and (5) give:

∑Φ′=′i

ikikC σ (6)


This equation system can be solved using a few channel spectrum unfolding technique. In this study we use the maximum entropy code MAXED [8] which requires an input curve, called the "default curve", as a priori information representing a first guess of the excitation function, here obtained from the evaluated activation cross section data file IRDF-2002 [9]. From all the curves that fit the measured data, the MAXED code chooses as solution the curve that is “closest” to the default curve which here means the curve that maximizes the relative entropy:

( ) ( )( ) ( ) ( ) dEEEEES defEdef∫

⎭⎬⎫

⎩⎨⎧

−+⎟⎠⎞

⎜⎝⎛−= σσ

σσσ ln

Here, σdef(E) is the default curve and σ(E) the sought excitation function from Eq. (6). The measure of how well the spectrum is unfolded is given by the χ2-value calculated as:

2

21

c

m

m

m

n ki i ki

nk k

C

u

σχ −

⎛ ⎞Φ −⎜ ⎟

⎜ ⎟=⎜ ⎟⎜ ⎟⎝ ⎠

∑∑

where uk is the measurement uncertainties.

A critical part is to generate the neutron fields, Φk. To allow for an accurate unfolding, the fields should together fully cover the energy interval of interest for the measured excitation function. Furthermore, the neutron fields should overlap well, be of different shapes and should be well characterised from calculation and/or measurements. This can be accomplished by, in a controlled way, flattening a well characterised quasi mono-energetic neutron field produced through nuclear reactions induced by ions from an electrostatic ion accelerator. At the IRMM, quasi mono-energetic neutron fields are routinely generated in the two energy regions 0-7 MeV and 14-19 MeV in the 7 MV Van de Graaff accelerator laboratory. Also the energy regions 7-10 MeV and 19-24 MeV are kinematically available, however only with more or less distorted neutron energy spectra due to competitive reactions like deuteron break-up neutrons.

In the previous study [4], several possible methods for neutron field distortion were considered. The chosen technique then utilized the double differential nature of the neutron fluence fields as created using an ion beam and nuclear reactions. By repeatedly scanning a sample disk under irradiation over a certain angular interval in front of the neutron producing target, the disk was exposed to neutrons of different energies and intensities, and a total neutron spectrum over a broader energy region was achieved. This technique has the advantages of being simple and the neutron spectrum can be calculated with good accuracy using pure kinematics or Monte Carlo calculations. However, a considerable drawback is that only the two energy intervals of up to about 7 MeV and 14-19 MeV are accessible due to either nuclear reaction kinematics or the parasitic components in the mono-energetic neutron spectra that are difficult to assess.

In this study we use neutron moderators as an alternative for neutron field flattening. A well characterised Bonner sphere neutron spectrometer [10] acts as the moderator, while the disk is positioned in the centre of the respective sphere replacing the originally mounted 3He detector.


4. EXPERIMENTAL

4.1. Choice of test sample

For testing the technique, a set of disks of natural indium was chosen The diameter of each disk was 20 mm and the thickness 5.0 mm. Data for both the 113In(n,n’)113mIn and the 115In(n,n’)115mIn reactions are obtained following a single activation. The respective isotopic abundances in natural indium are 4.29% (113mIn) and 95.7% (115mIn). The 115In(n,n’)115mIn excitation function is well characterised while the 113In(n,n’)113mIn is characterised to a lesser degree. Both reactions have reasonably high cross sections with top values of about 300 mb, and result in relatively short-lived radionuclides with half-lives 1.658 h (113mIn) and 4.486 h (115mIn) respectively.

4.2. Activation set-up

The disks were mounted on an aluminium stand at zero degrees relative to the ion beam, at the left 30-degree beam line in the IRMM Van de Graaff neutron laboratory, see Fig. 1. The distance between the neutron producing target and the centre of the disk holder was 100 cm. The disks were covered with a 0.1 mm gold foil, enclosed in a 1 mm thick cadmium box to reduce activation by low energy neutrons and neutron capture, see Fig. 2. The capsule was positioned in tight geometry in a cylindrical polyethylene holder, with a diameter of 40 mm, replacing the originally mounted 3He detector in the centre of polyethylene Bonner spheres, which are all included in the IRMM Bonner sphere spectrometer of type PTB-C [11], see Fig. 3. The Bonner spheres were mounted from the top of the cylindrical holder with no remaining empty space within the sphere except for a 15 mm in diameter cylindrical cavity left for the optional positioning of a 3He detector in the centre of the respective sphere. Eight Bonner spheres were used, in addition to the bare polyethylene holder, with the diameters in inches of 3, 4, 5, 6, 7, 8, 10 and 12. The ion beam current was monitored using a current integrator connected to the electrically isolated neutron producing target, and the neutrons were monitored using a moderated BF3 long counter (LC) positioned at a distance of 4 m and at 90 degrees angle to the ion beam.


Fig. 1. Schematic over the experimental set-up as seen from the side. The neutrons were produced through the 3H(d,n)4He reaction in the target to the left. The drawing is not to

scale.

Fig. 2. Schematic over capsule enclosing the disk.


Fig. 3. The polyethylene Bonner spheres used as moderators. The diameters in inches are 3, 4, 5, 6, 7, 8, 10, 12 and 18, however the 18" was not used as moderator due to its

size.

4.3. Neutron activation

Two irradiations were done; with a 17 MeV and a 19 MeV primary neutron beam respectively. For both irradiations the 3H(d,n)4He reaction was used, see Table 1 for ion beam data and Table 2 for neutron irradiation data. The neutron producing target was TiT targets mounted on a 0.5 mm thick Ag backing. The neutron yield was measured using the long counter that was calibrated using a recoil proton telescope [12].

Primary neutron beam peak energy (MeV): 17.0 19.0

Ed (MeV): 1.372 2.671 Ed fwhm (keV): 685 350 TiT target (mg/cm2): 1.936 1.941 T/Ti ratio: 1.23 1.27

Neutron yield /LC (uncert.): 2.67·104 (3.0 %)

1.51·104 (4.6 %)

Table 1. Data for the neutron production. Ed and fwhm is the energy and the fwhm of the deuteron ion beam.

BS Ii (μA)

ta (h)

Ct (μC)

LC events / 106

Φtot / 109 (sr-1)

0" 4.3 4.1 63176 12.1 322 3" 4.0 14.8 213871 38.1 1019 4" 13.5 3.9 190204 35.4 945 5" 12.5 14.6 657426 121.2 3239 6" 14.0 4.5 227241 41.8 1118 7" 13.8 4.4 218653 35.0 935 8" 12.2 14.9 657767 111.4 2975


10" 10.8 4.8 185902 35.5 948 12" 9.5 3.8 131158 23.3 621

Table 2a. Neutron irradiation data for the 17 MeV irradiation. BS is the used Bonner sphere identified by its diameter in inches. 0" indicates no Bonner sphere but only the

cylindrical polyethylene holder and the disk capsule. Ii is the average ion beam current, ta the activation time for the respective irradiation, Ct the accumulated total deuteron

beam charge, LC the acquired number of long counter monitor events in unit of 106, and Φtot the total neutron fluence yield per steradian from the neutron producing target, in 0

degree emission angle and in unit of 109 neutrons.


BS Ii (μA)

ta (h)

Ct (μC)

LC events / 106

Φtot / 109 (sr-1)

0" 3.45 21.1 262297 39.6 597 3" 3.50 3.6 45743 6.60 100 4" 3.46 14.0 173794 25.2 380 5" 3.48 19.4 242511 35.6 537 6" 3.57 3.3 41785 6.01 91 7" 3.39 16.0 195043 29.4 444 8" 3.44 4.1 50723 7.47 113 10" 3.47 6.3 78478 11.7 177 12" 3.51 17.8 224872 32.5 490

Table 2b. Same as table 2a but for the 19 MeV irradiation.

For both irradiations the neutron spectrum was measured at about 2.7 m using the same Bonner spheres as used as moderators but here also including an 18" sphere and the 3He detector in the centre of the respective sphere, see Fig. 4. For the unfolding of the spectrum the MAXED unfolding code [8] was used with input default spectra calculated from the Target Monte Carlo code [13]. Both the pre-set and the final calculated χ2-value for the unfolding was 1.0. The 3" data for the 17 MeV measurement was, for unknown reason, removed as an obvious outlier. Previous validation of the Bonner sphere system has shown that the minimum feasible distance from the neutron producing target for using the spectrometer, including the 18" sphere, is 2.5 m due to the double differential character of the neutron field and because the calculated response functions assume a parallel neutron field [14].

The neutron fluence spectra at the location of the disk sample, i.e. in the centre of the respective Bonner sphere, were simulated using MCNP-4C2 Monte Carlo calculations [15], with the respective measured neutron spectrum as input spectrum, and smoothed using 5-channel moving window averaging, see Fig. 5. The calculations of the fields assumed a void sample but no neutron multi-scattering in the disks.


0 2 4 6 8 10 12 14 16 18 20

0.05

0.10

0.15

0.20

0.25

0.30 Measured Simulated

Neu

tron

inte

nsity

/ Δ

E


0 2 4 6 8 10 12 14 16 18 20

0.05

0.10

0.15

0.20

0.25

0.30 Measured Simulated

Neu

tron

inte

nsity

/ Δ

E


Fig. 4. The 17 MeV (upper) and 19 MeV (lower) input neutron spectrum measured using the Bonner sphere spectrometer at a distance of about 2.7 m from the neutron generating

target (solid line) and at 0 degree angle. The spectrum was unfolded with a simulated spectrum as default input spectrum, (dashed line) calculated using the Target Monte

Carlo code [13]. Both spectra are normalised to 1 neutron and the energy bin width is 100 keV. The considerable spectral components between 1-6 MeV and below 100 keV, as seen in the measured spectra, are believed to be due to room in-scattered neutrons which are not calculated by the Target code and, thus, do not appear in the simulated spectrum.


0 2 4 6 8 10 12 14 16 18 2010-4

10-3

10-2

10-1

Neu

tron

inte

nsity

/ ΔE


0 2 4 6 8 10 12 14 16 18 2010-4

10-3

10-2

10-1

Neu

tron

inte

nsity

/ ΔE


Fig. 5. Monte Carlo simulated spectra in the centre of respective sphere (solid lines) using the input 17 MeV (upper) and 19 MeV (lower) measured neutron

spectra from Fig. 4 (dotted line). All spectra are normalised to 1 neutron and the energy bin width is 100 keV. The respective moderated neutron spectrum is

identified by a higher degree of moderation, i.e. a higher neutron component in the mid-energy region, the bigger the Bonner sphere.

From Fig. 5 it is obvious that the moderation of the neutrons is not optimal. Ideally, all the neutrons in the initial full energy neutron peak should be moderated to the energy region from the cross section energy threshold to the peak energy. In this case, a considerably number of neutrons are either left in the original peak energy area or moderated to neutron energies below the threshold. The neutrons left in the peak obscure the unfolding in this energy region while the low energy neutrons are just lost. This calls for a more elaborated design of the moderator like flattering filters typically used in


accelerator based neutron sources aimed for neutron capture and fast neutron therapy at hospitals. A suggestion for a flattering filter is given in Fig. 6 where only one filter is assumed and the different neutron fields are created by moving the filter between the neutron producing target and the irradiated disk. Nevertheless, for this preliminary study of the technique, the Bonner spheres were chosen as they have been thoroughly studied and validated previously [14].

Fig. 6. Schematic over suggested arrangement for neutron beam flattering filter. The filter is moved between the target and the disk holder to create the different

neutron fields.

4.4. Gamma-ray measurements

The gamma-ray measurements were carried out using a low background HPGe-detector (Ge-T2) [7] as the induced activities were relatively low (a few hundred mBq), see Table 3 and Fig. 7. The disks were placed in a holder with a well-defined geometry and centered at 5.0 mm from the end-cap of the HPGe-detector. The detector is a 20% relative efficiency, coaxial detector with an ultra pure aluminum (Kryal) end-cap and an entrance window of thickness 1.5 mm. The active volume of the Ge-crystal is 71.3 cm3 and the crystal diameter is 59 mm. The detector was calibrated experimentally by measuring calibrated point sources at different distances from the detector. The dead layer thicknesses (front, side and bottom) were modelled using the EGS4 Monte Carlo code [15] where the dimensions of the detector were determined from radiographic photos taken from two angles. The dead layer thicknesses in the model were adjusted until a good match was obtained between simulation and experimental results. The calibration approach was validated through the successful participation of an intercomparison exercise organized by NPL (National Physics Laboratory) in the UK [16]. The experimentally determined accuracy of measured activity is better than 1.5% for the detector.


Ge-T2 Ge-5 Ge-8Above Ground HADES HADES

20% 50% 19%Normal coaxial

with thick deadlayer

Planar - BEGe Planar - BEGe

Gamma line (keV)

Radio-nuclide

190 In-114m 0.070703 0.1126 0.04057336 In-115m 0.048276392 In-113m 0.042159417 In-116m 0.035794

LocationRel. Eff.

Crystal type:

FEP efficiency

Table 3. Data for the HPGe-detectors used in this study. Note that the FEP efficiency is also depending on the sample holder which was different for the three

detectors.

The specific activity per atom of the activated target isotope, A, was calculated using the formula:

1c

m

tt

A a

CMA emI N P e

λλ

γ

λε −

⎛ ⎞= ⎜ ⎟−⎝ ⎠ (7)

The notations are as in Eq. (1). The full energy peak efficiency, ε, was calculated using the EGS4 Monte Carlo code with measured dimension and composition of the disk sample as input. The calculated specific activities were further on divided by a factor Ccorr, to compensate for variations in the accelerator beam current during the activations and to provide the factor for calculation of the saturation activity:

( )

1

nn i t

corr ii

c N e λ− ⋅ − ⋅Δ

=

= ⋅∑ (8)

where Ni is the number of registered long counter events for the time-bin i, n the total number of time-bins, Δt the time-bin width, in this study set to 60 s, and λ the decay constant for the radionuclide in question. The gamma lines and decay data used are listed in Table 4.

Half-life: 1.66 h Half-life: 49.5 d Half-life: 4.49 h Half-life: 54 min

Eg (keV) Pg (%)AbsoluteUncert.

(%) for PgEg (keV) Pg (%)

AbsoluteUncert.


AbsoluteUncert.


AbsoluteUncert.

(%) for Pg

392 64.97 0.17 190 15.56 0.16 336 45.8 2.2 only those > 10% listed here558.00 4.40 0.31 497 0.047 0.01 417 28.2 0.13725.00 4.30 0.30 819 11.5 0.05

1072 56.2 0.261294 84.4 0.401507 10.0 0.052112 15.6 0.07

In-116mIn-114mIn-113m In-115m


Table 4. Decay data for the four radionuclides quantified in this study.

It is evident from Table 4, that gamma-ray spectrometry of 113mIn and 115mIn is hampered by the presence of 116mIn which is produced by thermal and epithermal neutron capture in 115In with a relative high cross section. Hence, it is essential to shield the indium disks with cadmium and gold foils in order to minimise the contribution from slow neutrons as discussed above, see also Fig. 2. The half-life of 116mIn is 54 m which is not significantly different from the half-life of 113mIn (1.66 h), making it difficult to profit from sample cooling.

Due to its relatively long half-life (49.5 d), 114mIn was measured after a decay time of about ten half-lives of 115mIn (i.e. about 2 d). For the 17 MeV irradiation 114mIn was measured in the underground laboratory HADES using the detectors Ge-5 and Ge-8, see Table 3.

Fig. 7. Photos from the low-background HPGe-detector Ge-T2. Every disk was placed on the detector in a special holder to define the measurement geometry

accurately.

5. RESULTS

The measured activities per disk at the end of activation are listed in Table 5.


SphereDisc (Bq) Uncert

(Bq)

Rel Uncert

(%)(Bq) Uncert (Bq) Rel Uncert

(%)

0 75 0.42 0.08 19 0.50 0.02 4 4.43 1 0.65 0.16 25 0.63 0.02 3.2 14.74 74 0.72 0.15 21 1.31 0.05 4 4.35 73 0.92 0.19 21 1.87 0.06 3 14.96 22 1.50 0.20 13 0.61 0.03 5 4.57 13 1.20 0.18 15 0.57 0.02 4 4.48 4 0.92 0.21 23 1.62 0.05 3 14.910 99 0.85 0.19 22 0.35 0.02 6 4.812 11 0.29 0.16 55 3.9

Irradiation time (h)

In-113m In-114m

Table 5a. The measured activity of 113mIn and 114mIn of each disk immediately after the stop of irradiation for the 19 MeV irradiation. "Disc" is the identification number for the

respective disk.

Sphere(Bq) Uncert

(Bq)

Rel Uncert

(%)(Bq) Uncert

(Bq)

Rel Uncert

(%)0 4.0 0.2 4.5 13.5 0.9 6.6 4.43 10.3 0.4 3.4 46.5 2.8 6.0 14.74 13.5 0.5 3.7 127.0 6.0 4.7 4.35 24.3 0.8 3.1 146.0 7.0 4.8 14.96 17.0 0.6 3.5 220.0 11.0 5.0 4.57 16.0 0.5 3.1 230.0 12.5 5.4 4.48 24.5 0.8 3.3 199.0 10.0 5.0 14.910 12.2 0.5 3.7 202.0 11.0 5.4 4.812 8.0 0.3 3.5 165.0 9.0 5.5 3.9


In-115m In-116

Table 5b. Same as Table 5a but for 115mIn and 116In.

SphereDisc (Bq) Uncert

(Bq)

Rel Uncert

(%)(Bq) Uncert (Bq) Rel Uncert

(%)

0 D17 1.15 0.15 13 0.80 0.15 19 21.13 D18 0.61 0.11 17 0.22 0.07 32 3.64 D22 0.63 0.13 21 0.60 0.14 23 14.05 D36 0.54 0.12 23 0.70 0.16 23 19.46 D11 0.60 0.15 26 < 0.43 dec thr, 3.37 D4 0.87 0.14 16 0.30 0.06 20 16.08 D13 0.29 0.10 34 < 0.12 dec thr, 4.110 D37 0.33 0.12 37 0.14 0.06 43 6.312 D99 0.62 0.12 20 < 0.35 dec thr, 17.8


In-113m In-114m


Table 5c. The measured activity of 113mIn and 114mIn of each disk immediately after the stop of irradiation for the 17 MeV irradiation. "Disc" is the identification number for the

respective disk.

Sphere(Bq) Uncert

(Bq)

Rel Uncert

(%)(Bq) Uncert

(Bq)

Rel Uncert

(%)0 11.4 0.4 3.5 62 3 4.8 21.13 4.8 0.2 4.6 51 3 6.1 3.64 8.4 0.3 3.6 132 7 5.3 14.05 8.7 0.3 3.4 152 8 5.3 19.46 3.7 0.2 5.4 108 6 5.6 3.37 7.2 0.3 4.2 110 5 4.5 16.08 3.4 0.2 4.4 94 4 4.3 4.110 4.1 0.2 4.1 73 4 5.5 6.312 5.4 0.2 4.6 63 4 5.7 17.8


In-115m In-116

Table 5d. Same as Table 5c but for 115mIn and 116In.

Table 6 gives the specific activity as calculated from Eq. (7) and corrected according to Eq. (8). Only 113mIn and 115mIn are included here, and hereafter, as they were the subject for the study. The uncertainties given are the combined standard uncertainties calculated following the ISO/BIPM Guide to the Expression of Uncertainty in Measurement [17]. The dominating uncertainty contributions for the gamma-ray measurements are from counting statistics and the detection efficiency. Nuclear data were taken from Ref. [18] for 113mIn and from Ref. [19] for 115mIn. Note that uncertainties due to nuclear decay data and efficiency calculation are fully correlated and will not change the shape of the final excitation function in any way. The propagation of the uncertainties in the unfolding procedure was calculated using the UMG software package [20]. Unfortunately, the UMG does not propagate uncertainties in the input neutron spectra. Instead these were added to the uncertainties in the measured input data, uother in Table 6.

The MCNP simulations of the neutron fields in the polyethylene Bonner spheres were based on cross sections for hydrogen and carbon from ENDF/VI.8 and ENDF/VI.6 respectively. From the experimental cross section data a combined uncertainty of about 4% is estimated over the total energy region. The MCNP simulations were performed with 8·108 events. However, due to the fine energy binning (100 keV), some bins contain few counts giving a rather high statistical uncertainty; after smoothing about 5 % for the total energy region.

The input spectrum for the MCNP simulations was measured with the very same Bonner sphere system as used for the irradiations but using MCNP calculated response functions that have been verified in mono-energetic neutron fields. The estimated uncertainty is about 5 %. With an additional uncertainty of 1 % related to uncertainty in the geometrical measurements of the set-up, a combined uncertainty of 8 %, in addition to the statistical uncertainty, is calculated for every irradiation, see Table 6. Uncertainties related to the weighing of the disks, the measurements of the disk dimensions and the statistical uncertainties in the number of registered long counter events are negligible.


113mIn Uncertainties (%) 115mIn Uncertainties (%) BS C uC uother

utotal C uC uother

utotal

0" 2.759 19.9 8.0 21.4 0.755 3.7 8.0 8.8 3" 2.755 23.6 8.0 25.0 0.909 1.6 8.0 8.2 4" 1.540 22.2 8.0 23.6 0.936 1.4 8.0 8.1 5" 2.246 18.3 8.0 19.9 0.952 1.7 8.0 8.2 6" 2.663 14.9 8.0 16.9 0.943 2.0 8.0 8.2 7" 3.148 20.4 8.0 21.9 1.116 2.7 8.0 8.4 8" 2.089 23.5 8.0 24.9 1.041 1.5 8.0 8.1 10" 2.006 24.8 8.0 26.1 0.878 2.5 8.0 8.4 12" 1.028 58.0 8.0 58.6 0.833 1.9 8.0 8.2

Table 6a. Measured specific activities at the stop of the activation in unit if 10-29 Bq atoms-1 and relative uncertainties for the 17 MeV irradiation. The measured data has

been corrected for variations in ion beam current and normalised to the number of monitor counts according to equation (8). BS is the used Bonner sphere referred to in table 2, C is the measured and corrected gamma-ray data, uC the uncertainty in the

measured gamma-ray data, uother additional uncertainties as discussed in the text and utotal the total uncertainties.

113mIn Uncertainties (%) 115mIn Uncertainties (%) BS C uC uother

utotal C uC uother

utotal

0" 9.154 11.4 8.0 13.9 1.689 1.9 8.0 8.2 3" 6.890 16.9 8.0 18.7 1.649 3.5 8.0 8.7 4" 5.776 19.6 8.0 21.2 1.357 2.3 8.0 8.3 5" 4.694 23.0 8.0 24.3 1.380 2.4 8.0 8.4 6" 7.045 25.5 8.0 26.7 1.313 4.0 8.0 9.0 7" 7.221 15.3 8.0 17.3 1.161 2.1 8.0 8.3 8" 2.632 38.8 8.0 39.6 1.072 3.6 8.0 8.8 10" 3.079 37.1 8.0 38.0 0.964 3.0 8.0 8.6 12" 5.640 19.4 8.0 21.0 0.880 3.5 8.0 8.7

Table 6b. Same as Table 6a but for the 19 MeV irradiation.


The unfolded excitation functions are given in Fig. 8 together with experimental data from the EXFOR data file [21]. Cross section data have been unfolded to 150 bins (17 MeV irradiation) and 170 bins (19 MeV irradiation) with an energy bin width of 100 keV covering the neutron energy region 0-15 MeV (17 MeV) and 0-17 MeV (19 MeV) respectively. The pre-set χ2-value for the unfolding [8] are given in table 7 and was chosen so as a plausible excitation function should be obtained with a minimum χ2-value. As default curves, also included in Fig. 8, a 9-degree polynomial fit to selected data points from the EXFOR data library was used for the 113In(n,n’)113mIn reaction, and for the 115In(n,n’)115mIn reaction data were obtained from the International Reactor Dosimetry File, IRDF-2002 [9]. Both the unfolded curves have been normalized to the integrated cross section calculated from the respective default curve for neutrons up to 15 MeV for the 17 MeV irradiation and up to 17 MeV for the 19 MeV irradiation. For a "sharp" case when the integrated value of the excitation function is unknown, a second material and disk, irradiated simultaneously and with well characterized cross section covering approximately the same energy region, is preferably used.

Reaction 113In(n,n’)113Inm 115In(n,n’)115Inm Primary neutron energy

17 MeV 19 MeV 17 MeV 19 MeV

Preset/achieved χ2-value

1.3/1.3 1.5/1.5 2.0/2.0 1.85/1.85

Table 7. χ2-values used as pre-set and the corresponding achieved χ2-values for the unfolding of the excitation functions.

The Maxed unfolding routine allows for uncertainty propagation also of the default curve which depicts the sensitivity of the unfolded curve to variations in the default curve. In this study it was estimated to 10 % for both the 113In(n,n’)113mIn and the 115In(n,n’)115mIn reactions.


0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 150

100

200

300

400

9-deg. polynomial This study EXFOR

........ uncertainties

Cro

ss s

ectio

n (m

b)


113In(n,n')113mIn, 17 MeV primary neutron beam

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 170

100

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9-deg. polynomial This study EXFOR


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Fig. 8a. Unfolded excitation functions for the 113In(n,n’)113mIn reaction for the 17 MeV and the 19 MeV primary neutron beam irradiations (solid blue lines). Grayed point data are from the EXFOR experimental data file [21] and the dashed red curve is a 9-degree

polynomial fit to selected EXFOR data. The dotted blue curves represent upper and lower uncertainty limits.


0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 150

100

200

300

400 IRDF-2002 This study EXFOR



Cro

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b)


0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 170

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400 IRDF-2002 This study EXFOR



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Fig. 8b. Unfolded excitation function for the 115In(n,n’)115mIn reaction for the 17 MeV and the 19 MeV primary neutron beam irradiations (solid blue lines). Grayed point data

are from the EXFOR experimental data file [21] and the dashed red curve is from the International Reactor Dosimetry File, IRDF-2002 [9]. The dotted blue curves represent

upper and lower uncertainty limits.


6. DISCUSSION

As seen in Fig. 8 the unfolded spectra rather well depict the EXFOR data. The 17 MeV and the 19 MeV irradiations give the same results within the uncertainty limits. The agreement to the EXFOR data is better than the IRFD-2002 excitation function for the 115In(n,n’)115mIn reaction, particularly considering a plausible peak pattern around 3 MeV for the 19 MeV irradiation. The height of the respective function is, however, here not absolutely determined as the functions have been normalised as discussed above. Also, the high uncertainties for the 113In(n,n’)113mIn measurement data make the unfolding rather dependent on the used default spectrum.

The study also showed that 114mIn can be measured accurately in a low-background gamma-ray detector after a few days of cooling and, thus, facilitating the measurement of the 115In(n,2n)114mIn cross section. The interfering reaction 113In(n,γ)114mIn is disfavoured due to the small isotopic abundance of 113In compared to 115In in natural indium. A suggested approach is to use the cross section of the 113In(n,γ)114mIn reaction to subtract the contribution from the 113In(n,γ)114mIn reaction to the 114mIn activity. However, this was considered being out of the scope for this project and was left for a further study.

During the project work it was found that the decay scheme of 115In (half-life 6.4 1014 y) did not include a β−branch to the first excited state of 115Sn in the table of isotopes. In order to quantify this branch, a 2.57 kg disk of pure indium was measured in HADES. The 497.48 keV gamma-ray was detected and the branching ratio was preliminary determined to 10-6 and could, thus, be disregarded.

Already in the first study [4] it was shown that neutron threshold excitation functions could accurately be measured using neutron activation in a series of well defined overlapping neutron fields. However, the technique employed then necessitated the production of neutron fields at different energies and limited the measureable energy regions to areas where mono-energetic neutron fields without parasitic spectrum components are available. This is not the case for the technique discussed in this study. On the contrary, a major advantage here is that only one single neutron spectrum has to be generated which reduces the uncertainties related to the production of neutron fields.

Thus, for the actual neutron production, a favourable situation is achieved, also as compared to point wise cross section measurements for which some neutron energy regions are difficult to reach using the conventional nuclear reactions, 7Li(p,n)7Be, 3H(p,n)3He, 2H(d,n)3He and 3H(d,n)4He. These regions include 7-14 MeV and >19 MeV where the neutron spectra are more or less corrupted, see Fig. 9. In addition, for the energy region 8-14 MeV, deuteron energies > 5 MeV and the 2H(d,n)3He reaction are necessary which limits the available laboratories providing adequate neutron beams considerably. Also, some energy regions necessitate low ion energies which produce broader full energy neutron peaks due to ion stopping in the neutron producing target. For example, a 16 MeV mono-energetic neutron peak produced using the 3H(d,n)4He reaction and a 2 mg/cm2 TiT target, will have a fwhm of about 1.1 MeV which considerably adds to the energy uncertainty of the result.

As discussed above, the largest contribution to the uncertainties, in addition to statistical uncertainties related to the gamma-ray counting, is due to the Monte Carlo calculations of the neutron fluence spectra in the spheres. This is an uncertainty that does not appear in point wise cross section measurements and constitutes the major drawback of the


technique. As it depends on the cross section data for the neutron moderator used, the choice of moderator is critical. Also the distance to the neutron producing target has to be larger than as for point wise cross section measurements since an intermediate moderator is inserted. This may introduce more room in-scattered neutrons relative to the number of direct neutrons, stressing the importance of a low scattering neutron measuring environment, but gives also higher statistical uncertainties as the neutron intensity is lower. Generally, the measurement of a complete neutron spectrum, as compared to point wise measurements, can only be done at the expense of higher statistical uncertainties since fewer neutrons are available for a particular energy area. Also, the establishment of a covariance matrix is not straightforward and has to be elaborated further.

0 5 10 15 200

100

200

300

400 NR NmE

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NmE

Fig. 9. Neutron energy areas available using conventional nuclear reactions and ion beams up to 7 MeV (cf. IRMM Van de Graaff neutron laboratory). NmE regions indicate Not mono-Energetic neutron regions and NR indicates energy region not available at all. The blue peaks indicate typical shapes of the full energy neutron peak in different energy

areas. Notice the wide energy peak achieved for the 16 MeV neutrons.

Due to the limited number of neutrons available, as compared to point wise measurements, the technique is only useful when there is enough sample material available and/or when the cross section to be determined is reasonably high (> tens of millibarns). Also, the half life of the studied isotope must be reasonably long allowing for adequate activation and gamma-ray measurement time.

Finally it should be mentioned that the discussed technique opens for measurements of excitation functions up to a neutron energy of about 14-15 MeV using a standard neutron generator, The neutron generator uses a deuteron beam and the nuclear reactions


2H(d,n)3He and 3H(d,n)4He to produce neutrons of the energies 2.5 MeV and 14.2 MeV respectively. It could, using the proposed technique, be a useful complement to point wise cross section data measurements for example for data in the "missing" and "corrupted" neutron energy regions discussed above, or for verification of excitation function models, particularly when no or only few data exists. However, further tests are necessary, for example to assess how complicated an excitation curve may be while still being possible to measure.

7. CONCLUSION

The project showed that neutron cross section curves can be measured up to about 17 MeV using flattened neutron beams. Further work is needed particular on the design of a neutron flattering filter, the modelling of the neutron fields in the spheres, including multiple neutron scattering in the disks, the calculation of the uncertainties and the reduction of the uncertainties. The use of low-level gamma-ray measurement techniques was highlighted as the available neutron flux is lower, as compared to conventional energy point wise measurements, which results in lower gamma yields.

8. REFERENCES

[1] Plompen (coordinator), “Neutron activation cross-section measurements from threshold to 20 MeV for the validation of nuclear models and their parameters”, International Evaluation Co-operation, Report NEA/WPEC-19, OECD Nuclear Energy Agency, Le Seine Saint-Germain, Issy-les-Moulineaux, France, ISBN 92-64-01070-X, (2005).

[2] The IAEA Reference Neutron Activation Library, RNAL, http://www-nds.iaea.org/ndspub/rnal/www/.

[3] V. Semkova, V. Avrigeanu, T. Glodariu, A.J. Koning, A.J.M. Plompen, D.L. Smith and S. Sudár, Nuclear Physics A 730 (2004) 255.

[4] G. Lövestam, M. Hult, A. Fessler, T. Gamboni, J. Gasparro, W. Geerts, R. Jaime, P. Lindahl, S. Oberstedt, H. Tagziria, Nucl. Inst. Meth. in Phys. Res. A, 580 (2007) 1400–1409.

[5] R. Wölfle, S. Sudar and S.M. Qaim, Nuclear Science and Engineering 91 (1985) 162.

[6] Y. Uwamino, H. Sugita, Y. Kondo and T. Nakamura, Nuclear Science and Engineering 111 (1992) 391.

[7] M. Hult. Low-level gamma-ray spectrometry using Ge-detectors. Metrologia 44 (2007) pp. S87-S94.

[8] M. Reginatto and P. Goldhagen, Health Phys. 77, (1999) 579.

[9] The international Reactor Dosimetry File IRDF-2002, http://www-nds.iaea.or.at/irdf2002/.

[10] D.J. Thomas and A.V. Alevra, Nucl. Inst. Meth. in Phys. Res. A, 476 (2002) 12-20.


[11] Wiegel, A.V. Alevra and B.R.L. Siebert, "Calculations of the Response Functions of Bonner Spheres with a Spherical 3He Proportional Counter Using a Realistic Detector Model", internal report PTB-N-21, 1994, Physikalisch Technische Bundesanstalt, Braunschweig, Germany.

[12] G. Lövestam, Nucl. Inst. Meth. in Phys. Res. A, 566 (2006) 609–614.

[13] Schlegel-Bickman, G. Dietze and H. Schölermann, Nucl. Instr. and Meth. 169 (1980) 517.

[14] G. Lövestam, F. Cserpák, W. Geerts and A. Plompen, "The IRMM Bonner Sphere System for neutron spectroscopy", IRMM internal report GER/NP/1/2003/02/03, EC-JRC-IRMM 2003.

[15] J.F. Briesmeister, "MCNPTM – a general Monte Carlo n-particle transport code", LANL report LA-13709, Los Alamos, NM, USA, 2002.

[16] V. Harms, C. Gilligan, A. Arinc, S. Collins, S. Jerome, L. Johansson, D. MacMahon and A. Pearce, “Environmental radioactivity comparison exercise 2005”, NPL Report DQL-RN 015, 2006, ISSN 1744-0629.

[17] ISO (1995) "Guide to the Expression of Uncertainty in Measurement". 1st edition corrected version. ISBN 92-67-10188-9. International Organisation for Standardisation, Geneva, Switzerland.

[18] Nuclear Data Sheets, Elsevier Science, volume 104 (2005) 791.

[19] Nuclear Data Sheets, Elsevier Science, volume 104 (2005) 967.

[20] "UMG - Unfolding using Maxed and Gravel", private communication M. Reginatto, Physikalisch Technische Bundesanstalt, Braunschweig, Germany.

[21] The EXFOR, Experimental Nuclear Reaction Data, http://www.nea.fr.


C6D6 - EXTENDED: The use of a high efficiency array of C6D6 detectors for

absolute capture cross section measurements in the thermal and epi-

thermal energy region.

Date: 24/06/2008

Authors: L.C.Mihailescu, A.Borella, C.Massimi, C. Sage, P.Schillebeeckx

Revised by: S. Kopecky

Approved by: P. Rullhusen

TABLE OF CONTENTS

1. ABSTRACT .......................................................................................................................................... D-2

2. INTRODUCTION ................................................................................................................................ D-2

3. THE CHARACTERISTICS OF THE OUTPUT SIGNAL OF THE C6D6 DETECTORS.......... D-3

4. THE DIGITIZERS ............................................................................................................................... D-4

4.1. CAEN N1728B digitizer ..................................................................................................................... D-4 4.2. Acqiris DC282 digitizer....................................................................................................................... D-4

5. RESULTS.............................................................................................................................................. D-5

5.1. Pulse height linearity and resolution.................................................................................................... D-6 5.2. Time resolution.................................................................................................................................... D-8 5.3. Dead time............................................................................................................................................. D-9 5.4. Capture measurements at GELINA ................................................................................................... D-10

6. CONCLUSIONS................................................................................................................................. D-12

7. REFERENCES ................................................................................................................................... D-13

C6D6 - EXTENDED: The use of a high efficiency array of C6D6 detectors for absolute capture D-2 / 13 cross section measurements in the thermal and epi-thermal energy region

1. ABSTRACT

The relatively long dead time in conventional data acquisition systems that provide

simultaneously the pulse height and the time information for the detected events hinders cross section measurements with high count rates. This is the case for capture cross section measurements at the time-of-flight facility GELINA using high radioactive samples or thick samples of materials having strong resonances. Either the high average count rate (e.g. due to the radioactivity of the sample) or the high instantaneous count rate for strong resonances results in a large dead time correction. One solution to reduce the impact of the dead time is the use of a data acquisition system based on fast digitizers. The performances of two commercial digitizers (CAEN N172B and Acqiris DC282), coupled to a C6D6 scintillator, have been tested in terms of pulse height linearity and resolution, dead time and time resolution. The signal processing was done on-line obtaining simultaneously the pulse height and time information for each detected event. With both digitizers a comparable pulse height linearity and resolution has been obtained as with a conventional system. The total dead time of both digital systems is at least a factor 5 shorter than the one for the conventional system. The main difference in performance between the two digitizers is the time resolution. For a relatively large scintillator, a time resolution of about 2 ns has been achieved with the DC282 module and the conventional system while the time resolution was limited to 15 ns with the CAEN N1728B module. For most nuclei a 15 ns time resolution is sufficient to perform resonance shape analysis. Therefore, the CAEN N1728B module can be used for the majority of capture cross section measurements at GELINA. However, for nuclei with low level density, for which the resolved resonance region extends to the keV-region, a better time resolution is required and the Acqiris DC282 module has to be used.

2. INTRODUCTION

At the time-of-flight facility GELINA capture cross-section measurements are performed

using the total energy detection principle in combination with the pulse height weighting technique [1]. Liquid scintillators filled with deuterated benzene (C6D6) are used for the detection of the prompt gamma-rays from the neutron capture reaction. The advantage of these detectors is their low sensitivity to neutron scattered from the sample and the good time resolution. Application of the Pulse Height Weighting Technique (PHWT) requires both the time of arrival and the energy deposited in the gamma-ray detector for each recorded event.

The conventional data acquisition used at GELINA [2] is able to provide simultaneously the time and pulse height information of an event with a fixed dead time between 2.5 and 5 μs. The main source of this dead time is the conversion time of the analog to digital converter and the corresponding time needed by the multiplexer to store the time and pulse height information of the event. Recently, large efforts have been made to reduce the overall uncertainty of capture cross section data under low count rate conditions to less than 2 % [1]. However, in case of radioactive samples 241Am or thick samples of materials having strong resonances 197Au, 113Cd with average count rates of 4000 Hz per detector, and such an uncertainty level can not be reached due to the impact of the dead time. For dead time corrections higher than a factor 2, systematic bias effects of more than 5 % can not be avoided. In addition the correction for dead time effects introduces uncertainties on the final capture yield which are strongly correlated.

To avoid large dead time corrections the count rate can be decreased by reducing the effective neutron flux or using less material. A more effective solution is to reduce significantly the dead time of the data acquisition system by using fast digitizers. Many authors have already


reported on the use of fast digitizers for cross section measurements using e.g. gridded ionisation chambers [3], Ge-detectors [4], stilbene crystal [5], BaF2 and CeF3 scintillators [6] and NE213 and C6D6 liquid scintillators [7]. Mostly, the entire waveform of the detector signal is recorded and the required information is deduced by off-line processing. This requires large data storage capabilities and on-line verification of the results is almost impossible. In case of on-line analysis the total dead time is defined by the dead time of the Digital Signal Processing (DSP) algorithms, which depends on the characteristics of the pulse, and by the re-arming time of the trigger.

In this paper the use of digitizers applying on-line DSP algorithms to determine the time and the pulse height is discussed. Two commercially available digitizers have been tested: the N1728B module provided by CAEN and the DC282 module provided by Acqiris. The pulse shape produced by gamma rays detected by C6D6 liquid scintillators has been studied and the performance of both digitizers in terms of pulse height linearity and resolution, time resolution and dead time for on-line analysis has been investigated. Finally, the digitizers have been used for capture cross section measurements at GELINA in high count rate conditions and the reduction of dead time correction has been verified.

3. THE CHARACTERISTICS OF THE OUTPUT SIGNAL OF THE C6D6 DETECTORS

In order to measure the neutron capture cross-sections at GELINA, γ-rays originating from the

reactions are detected by liquid scintillators filled with deuterated benzene. Two different types of C6D6 detectors are used: a truncated 5-sides 12.5 cm high pyramid shape filled with 2.8 l C6D6 [8] and a cylindrical shape (10 cm diameter and 7.5 cm height) filled with 0.6 l [1,9]. Both types are coupled to an EMI9823KQ photomultiplier tube (PMT) through a boron free quartz window. Due to their shape, larger volume and smaller fraction of the scintillation liquid seen by the PMT, the time resolution of the truncated pyramid detectors (about 2 ns) is not as good as the one of the cylindrical detectors (< 1 ns).

Fig. 1: The output of the C6D6 detectors recorded with the Acqiris DC282 digitizer with a sampling interval of 0.5 ns: Left fast output signal, Right slow output signal.

The PMT has a total of 14 amplification stages. Two output signals are available: 1) a fast output from the anode with a rise time of about 8 ns and a total length of less than

100 ns and

2) a slow signal from the 9th dynode. The latter is amplified by a charge sensitive preamplifier.

The output signal of the preamplifier has a rise time of 150 ns, a decay time of 1000 ns and a total length of about 5000 ns. Fig.1 shows typical pulse shapes of the fast (left panel) and slow


(right panel) signal resulting from measurements with gamma-ray sources. As the fast and slow signals are taken at different amplification stages, they require a different optimum high voltage to obtain a good linearity and pulse height resolution. From measurements with quasi mono-energetic gamma-ray sources it was verified that, below 6 MeV gamma-ray energy, the fast signal from the C6D6 detector is linear up to a high voltage of about 1600 V and the slow signal is linear up to 2000 V.

4. THE DIGITIZERS

4.1. CAEN N1728B digitizer

The CAEN N172B is a four channel 100 MHz flash ADC using a Field Programmable

Gate Array (FPGA), which includes various DSP algorithms. The module can be housed in one slot of a NIM crate and the connection to the computer is done through an USB 2.0 port. The board can digitize in parallel up to 4 input signals at a sampling period down to 10 ns with a 14 bit amplitude resolution. The 4 input channels have a full scale range of +/- 1.1 V or +/- 2.2 V. The gain settings can be defined by software. Four additional inputs accept logical NIM or TTL signals which may be used to record the trigger signals delivered by the accelerator. Different cards can be synchronized by providing the same trigger signal to a logical input.

The module is delivered with software that can initialize different cards, run data acquisition, adjust parameters for signal processing and store pulse height histograms and list mode data. The present version of the software does not produce time-of-flight histograms. Since the time information is only provided in integer numbers of sampled points, the time resolution of each channel is limited to 10 ns. The time information can be obtained from a leading edge trigger (LET) or Constant Fraction Trigger (CFD). The LET option can be applied on the direct input signal or on a differentiated signal. The Jordanov-Knoll trapezoid algorithm is implemented to determine the energy that has been deposited in the detector [10]. A software interface is used to adjust the parameters of the logarithms.

The advantages of the CAEN N1728B module for time-of-flight measurements at GELINA are the possibility to apply different internal delays and gates to each input channel and the availability of the additional inputs for logic signals. The latter can be used for the trigger signal provided by the accelerator and to monitor the intensity of the beam. Therefore, the experimental set-up does not require additional electronic modules and can be kept very simple. The disadvantage is the relatively long sampling period of 10 ns which limits the time resolution. 4.2. Acqiris DC282 digitizer

The Acqiris DC282 card is a 10-bit digitizer with a 2 GSample/s sampling rate

corresponding to 0.5 ns sampling interval. The card is housed in a Compaq PCI crate and has 4 input channels with one common external trigger. The input channels have a full scale range from 0.05 V to 5 V, which can be adjusted in discrete steps. The DC282 card does not perform DSP on-board. Therefore, the digitized detector signal is first transferred via a PCI/PXI bus to the computer and analyzed online. The detector signals have been recorded in sequence mode [11]. Using two memory buffers the data have been recorded and transferred simultaneously. In this way dead time due to the data transfer through the PCI bus is avoided and relatively high count rates (up to 40 kHz per channel) can be handled.


The electronic set-up used for time-of-flight measurements at GELINA is shown in

Fig.2. The first channel has been used to record the trigger signal (T0) provided by the accelerator and the other channels to analyse the signals originating from the C6D6 detectors. The time-of-flight for each detected event has been calculated relative to the signal in the first channel. Only one external trigger for the full card is accepted. Consequently, for each external trigger the data from all channels are transferred simultaneously and no zero-suppression is possible before transfer. The external trigger is obtained as an OR between the C6D6 detectors and the T0 signal as illustrated in Fig. 2. Since the time-of-flight of each event is taken relative to the arrival time of the signal in the first channel, the absolute time information of the external trigger has no impact on the time resolution. The veto signal in Fig. 2 makes sure that the system is always triggered by the T0.

Fig. 2: Experimental setup used for capture measurements with the Acqiris DC282 digitizer. The pre-trigger signal Pt from GELINA precedes the T0 signal with several μs.

Software has been developed for data acquisition and for processing of the signals to obtain the time and pulse height information on-line. A digital CFD algorithm including an interpolation between consecutive sampling points has been used. The pulse height has been obtained by numerical integration of the full signal pulse covering a time interval of 50 ns. For each signal the baseline has been determined by an average over 10 ns before the pulse. Marrone et al. [6] showed that for a C6D6 detector the pulse height information obtained from simple numerical integration is as good as the one deduced from more elaborated and time consuming fitting procedures. For each event the time and pulse height, together with flags that can be used to construct coincidence patterns have been stored on the hard disk.

5. RESULTS

The results of measurements performed with the truncated pyramid shape detector

connected to a conventional system and to the CAEN and Acqiris digitizer are presented in this section. In the conventional data acquisition system the fast signal has been sent to a CFD to extract the time information and the slow signal to a spectroscopic amplifier and analog to digital


converter to obtain the energy deposited in the detector. The conventional data acquisition system had a non-extendable fixed dead time of 2800 ns. The slow output has also been used with the CAEN digitizers and the fast signal with the Acqiris digitizer. The light output function and resolution have been studied by measurements of radionuclide gamma-ray sources, the time resolution has been verified by measurements with a 60Co source and the impact of the dead time has been studied by time-of-flight measurements at GELINA using a 1 mm thick 197Au sample. 5.1. Pulse height linearity and resolution

Fig. 3: Pulse height spectra of a C6D6 detector recorded with three different acquisition systems for a 137Cs (Left panel) and 238Pu+13C (Right panel) gamma-ray source.

The C6D6 detector response is used in the calculation and in the application of the weighting function. Borella et al. [9] and Sage et al. [8] reported on the response functions of the C6D6 detectors that are used for capture cross section measurements at GELINA with the conventional acquisition system. Many authors already demonstrated that reliable detector responses can be calculated by Monte Carlo simulations, provided that the geometry input file reflects the measurement conditions and the light output function and resolution are defined.

The light output function and resolution that is obtained with the three data acquisition systems have been compared by recording gamma-ray spectra for 137Cs, 54Mn, and 65Zn radionuclide sources and for gamma rays resulting from the decay of 232Th and a 238Pu + 13C mixture. Examples of pulse height spectra for a 137Cs and 238Pu+13C source are shown in Fig. 3. For photon energies up to 3 MeV Compton scattering is the dominating process in the C6D6 liquid. For mono-energetic gamma rays with an energy E gamma, Compton electrons are produced with a maximum energy of Ec [12]:

)E20.511(E2

E2

Cγ

γ

+= (1)

with all energies expressed in keV. The sharp edge around Ec has been used to determine the light output function and resolution applying an iterative procedure as discussed in Refs. [1,12,13]. The light output function and resolution have been adjusted such that the calculated response, which was obtained from Monte Carlo simulations, fitted the measured ones in the upper portion of the spectra around the Compton edges. The observed pulse height has been transformed into a light output Le in units of energy based on the direct proportionality between pulse height and electron energy for the Compton edges at Ec = 478, 640, 908 and 2382 keV observed in the spectrum for the Cs, Mn, Zn and Th measurements, respectively. In the fitting procedure the free parameters (α, β and γ) in the expressions for the resolution as a function of light output have been adjusted using the expression [12]:


2e

2

e

22

e

e

LLLL γ

+β

+α=Δ

(2)

In Figs. [4] and [5] the results obtained with the three different acquisition systems are compared. Fig.[4] shows the ratio of the light output divided by corresponding electron energy for the measurements with the three systems. This figure shows that for energies below 6 MeV the observed light output obtained with the digitizers is directly proportional with the corresponding electron energy. The results obtained with the conventional system indicate a small (less than 1 %) nonlinearity around 6 MeV. For NE213 scintillators such non-linearity has already been reported in Ref. [13,14,15]. Fig.[5] shows that the resolution broadening can well be described by the function proposed in Ref. [12]. The resolution obtained with the CAEN digitizer is slightly better than the one obtained with a conventional system. The improved resolution is mainly due to a smaller contribution of the term γ2 which expresses the contributions due to electronic noise. The results obtained with these systems are comparable with the resolution reported in Ref. [12] for a NE213 scintillator with similar dimensions. For the spectra obtained with the Acqiris system applying a numerical integration the resolution broadening is not as good. The difference in the resolution is mainly due to the term α2 in Eq.2, which limits the resolution to about 10 % even at high energies.

Similar pulse height spectra were obtained with the CAEN N1728B digitizer when the fast signal from the C6D6 detector was used. For this digitizer, the slow output signal was preferred due to some difficulties in setting the input parameters when a low gamma-ray threshold was used. Moreover, the trapezoid algorithm is more suited for charge integrated signals.

Fig. 4: The ratio between the light output of the electrons energy for a C6D6 detector and three different data acquisition systems. The statistical uncertainties are 0.5 %.


Fig. 5: The pulse height resolution of the C6D6 detector and the tree data acquisition systems. 5.2. Time resolution

The time resolution of the three systems has been determined by a start-stop measurement setup between two identical C6D6 detectors with truncated pyramid shape using a 60Co source. The results are shown in Fig. 6. For the Acqiris digitizer and the conventional system, the full width at half maximum is 2.3 ns, which results in a 1.6 ns time resolution for each detector. For the cylindrical C6D6 detector a time resolution better than 1 ns has been obtained. Similar results have been obtained from measurements using a 232Th sample and a 238Pu+13C. Therefore, the time resolution can be considered to be independent of the pulse height. For the CAEN system a time resolution of 15 ns has been observed. For many nuclei studied at GELINA the resolved resonance region covers a region up to about 10 keV and a time resolution of 15 ns is sufficient. However, for light nuclei and near neutron magic nuclei, resonances should be resolved up to a few hundreds of keV incident neutron energy. For such applications a time resolution better than 15 ns is required.

Fig. 6: Time resolution spectrum for the Acqiris DC282 digitizer and the conventional system (Left panel) and for the CAEN N1728B digitizer (Right panel). The spectra were recorded with a start-stop setup between two identical C6D6 detectors. The FWHM is 2.3 ns for the conventional system and for the DC282 digitizer and 15 ns for the N1728B digitizer.


5.3. Dead time

The dead time has been measured by registering the time difference between two

consecutive events. From the resulting time interval spectra using calibration sources (Fig. 7), a 370 ns and 560 ns dead time can be deduced for the Acqiris and CAEN digitizer, respectively. This dead time results mainly from the 350 ns re-arming of the trigger. The trapezoid algorithm applied in this work for the CAEN is an additional source of dead time. This contribution can be reduced by changing the parameters of the trapezoid. Fig. 7 shows that the dead time for the conventional system is 2800 ns. The effect of the dead time can also be seen in the time-of-flight spectrum recorded from measurements at GELINA, as illustrated in Fig.8. Due to the high count rate in the gamma-flash peak the acquisition systems are blocked immediately after the gamma-flash peak. After 350 ns the Acqiris digitizers recovers while the conventional system is still blocked.

Fig. 7: The time interval spectrum recorded with a C6D6 detector and a random gamma-ray source. The acquisition systems have the following values for the dead time: 350 ns, 560 ns and 2800 ns.


Fig. 8: The neutron time-of-flight (t.o.f.) spectrum immediately after the gamma-flash for the DC282 digitizer and for the conventional acquisition system. The digitizer recovers after 350 ns. 5.4. Capture measurements at GELINA

To verify the impact of the dead time on capture cross section experiments,

measurements have been performed with a 1 mm thick 197Au sample at a 13-m measurement station of GELINA. The gamma rays originating from the capture reaction in the 197Au sample were detected by four truncated pyramid C6D6 detectors oriented at 125o with respect to the direction of the incoming neutron beam. The average count rate was 4000 Hz per detector with GELINA operating at 800 Hz and for an 85 mm beam diameter. For the conventional system one time-of-flight signal, resulting from a logic OR of the time signals of each detector, together with the pulse height of the four C6D6 detectors have been recorded. For the CAEN digitizer the signals of the 4 detectors have been independently analyzed using the 4 input channels of the card. For the Acqiris system only 2 detectors have been used and the electronics shown in Fig. 2 has been implemented. Due to the different number of detectors the total count rate was not the same.

Fig. 9: T.o.f. spectra recorded with the CAEN digitizer and with the conventional system for a 1 mm thick 197Au sample. The corresponding dead time corrected spectra are shown as well. All the four spectra are normalized to the maximum of the 46.45 eV resonance. The energy of each resonance is indicated. The right panel shows a zoom of the spectrum around the maximum of the 60.3 eV resonance.


Fig. 10: The dead time correction coefficient for a measurement with 1 mm thick 197Au sample using fast digitizers (top) and conventional acqusition system (bottom).

The dead time corrected number of counts in time-of-flight channel I, Nc(I), has been related to the number of observed counts, No(I), by the expression [16]:

∑ −−=

−

=

1I

IJ b

o

b

o

oc

dN2

)I(NN

)J(N1

)I(N)I(N (3)

where Nb is the total number of bursts and where the dead time is given in channels by the difference I-Id. The expression in Eq.3 , which is based on elementary considerations, is valid for a non-extendable dead time and requires a stable beam.

The time-of-flight spectrum for the 197Au sample obtained with the CAEN digitizer and the conventional system are compared in Fig.[9]. For simplicity of the graph, the spectrum recorded with the Acqiris digitizer is not shown because it almost coincides with the one of the CAEN digitizer. The dead time correction as a function of time-of-flight for the three set-ups is shown in Fig.[10]. The largest correction for the conventional system, a factor 2.2, has been obtained for the 60.3 eV resonance at a time-of-flight of 120 μs. The correction for the spectra obtained with the digitizers is less than 10\% for the whole spectrum. Despite a slightly longer dead time and higher total input count rate, the dead time correction for the CAEN system is smaller compared to the one for the Acqiris system. This is because each channel of the CAEN digitizer is treated independently and a lower total count rate is used in the dead time correction.

The effect of the dead time in the conventional system is obvious for the resonances at 78.4 eV, 60.3 eV and 58.1 eV. Both the observed shape and the maximum for these resonances are affected by the dead time. A typical dip due to the long dead time is observed in the response of the conventional system on the right side (low energy) of the 78.4 eV resonance. After dead time correction, the spectra recorded with the digitizers and the conventional system agrees fairly well for this resonance where the correction is below a factor 1.5. A difference of more than 2 % can be observed for the resonance at 60.3 eV where the correction increases to a factor 2.2 for the conventional system.


6. CONCLUSIONS

The relatively long dead time of conventional data acquisition systems limits measurements of the capture cross section in the resonance region to low count rate applications. The corrections for dead time in case of high count rates introduce systematic bias effects due to the limitations of the correction algorithms. In addition they result in correlated uncertainties requiring large data storage capacities. The corrections for dead time can be significantly reduced by using data acquisition systems based on fast digitizers. In this work two solutions have been investigated: the 14-bit CAEN N1728B module with 100 MSamples/s and the 10-bit Acqiris DC282 with 2 GSamples/s.

The dead time for the CAEN and Acqiris system in case of on-line signal processing is 560 ns and 350 ns, respectively. These dead times are mainly due to the re-arming time of the trigger and should be compared with the 2800 ns for the conventional analog system. The dead time of the CAEN system can be reduced to about 350 ns by changing the parameters of the trapezoid filter. The pulse height linearity and resolution for both systems are comparable with the one for a conventional system. For most of the cross section measurements at GELINA, the CAEN digitizer may be preferred due to a much simpler experimental set-up. This module offers a cost effective solution to reduce the dead time. The only drawback of the CAEN system is the 15 ns time resolution. Such a time resolution is not sufficient in case the resolved resonance region extends to a few hundred keV incident neutron energy, i.e. for light nuclei and nuclei near magic configurations. For such applications the Acqiris digitizer, with a similar time resolution as the conventional system, can be used.


7. REFERENCES

[1] A. Borella, G. Aerts, F. Gunsing, M. Moxon, P. Schillebeeckx, R. Wynants, The use of C6D6 detectors for neutron induced capture cross-section measurements in the resonance region, Nucl. Instrum. Methods Phys. Res. A 577 (2007) 626. [2] J. Gonzalez, C. Bastian, S. de Jonge, K. Hofmans, Modular MultiParameter Multiplexer, MMPM, hardware description and user manual, Internal Report GE/R/INF/06/97, JRC-IRMM, Geel (1997). [3] G.Georginis, V. Khriatchkov, The effect of particle leaking and its implications for measurements of the (n,alpha) reactions on light elements by using isonisation chambers, Nucl. Instrum. Methods Phys. Res. A 538 (2005) 550 - 558. [4] L. C. Mihailescu, C. Borcea, A. J. M. Plompen, Data acquisition with a fast digitizer for large volume HPGe detectors, Nucl. Instrum. Methods Phys. Res. A 578 (2007) 298 - 305. [5] N. V. Kornilov, V. A. Khriatchkov, M. Dunaev, A. B. Kagalenko, N. N. Semenova, V. G. Demenkov, A. J. M. Plompen, Neutron spectroscopy with fast waveform digitizer, Nucl. Instrum. Methods Phys. Res. A 497 (2003) 467 - 4781. [6] S. Marrone, E. Barthomieux, F. Becvar, D. Cano-Ott, N. Colonna, C. Domingo-Pardo, F. Gunsing, R. Haight, M. Heil, F. Käppeler, M. Krticka, P. Mastinu, A. Mengoni, P. Milazzo, J.O'Donnell, R.Plag, P.Schillebeeckx, G. Tagliente, J. Tain, R. Terlizzi, J. Ullmann, Pulse shape analysis of signals from BaF2 and CeF3 scintillators for neutron capture experiments, Nucl. Instrum. Methods Phys. Res. A 568 (2006) 904 - 911. [7] S. Marrone, D. Cano-Ott, N. Colonna, C. Domingo, F. Gramenga, E. Gonzalez, F. Gunsing, M. Heil, F. Käppeler, P. Mastinu, P. Milazzo, T. Papaevangelou, P. Pavlopoulos, R. Plag, R. Reifarth, G. Tagliente, J. Tain, K. Wisshak, Pulse shape analysis of liquid scintillators for neutron studies, Nucl. Instrum. Methods Phys. Res. A 490 (2002) 299 - 307. [8] C. Sage, E. Barthoumieux, O. Bouland, F. Gunsing, A. Plompen, P.Schillebeeckx, P. Siegler, N. V. Opstal, R. Wynants, A new high efficiency array of C6D6 detectors for capture cross-section measurements at GELINA, Proc. Int. Conf. Nucl. Data Sci. Techn. (2007). [9] A. Borella, K. Volev, A. Brusegan, P. Schillebeeckx, F. Corvi, N. Koyumdjieva, N. Janeva, A. Lukyanov, Determination of the 232Th(n,γ) cross-section from 4 to 140 keV at GELINA, Nucl. Sci. Eng. 152 (2006) 1 - 14. [10] CAEN Nuclear Physics, Technical information manual - MOD. N1728A/B 4 CH 100MHz flash ADC - Manual Revision n.5, NPO: 00118/04:N1728x.MUTx/05 (2007). [11] Agilent Acqiris, User manual: Family of 10-bit digitizers - Models covered: DC122 / DC152 / DC222 / DC252 / DC282}, ZM020170B Rev. D (2007). [12] G. Dietze, H. Klein, Gamma-calibration of NE 213 scintillation counters, Nucl. Instrum. Methods Phys. Res. 193 (1982) 549 - 556. [13] D. Schmidt, B. Asselineau, R. B. ottger, H. Klein, L. Lebreton, S. Neumann, R. Nolte, G. Pichenot, Characterization of liquid scintillation detectors, Nucl. Instrum. Methods Phys. Res. A 476 (2002) 186 - 189. [14] L. Buermann, S. Ding, S. Guldbakke, H. Klein, T. Novotny, M. Tichy, Response of NE213 liquid scintillation detectors to high-energy photons (Eγ > 3 MeV), Nucl. Instrum. Methods Phys. Res. A 332 (1993) 483 - 492. [15] T. Novotny, L. Buermann, S. Guldbakke, H. Klein, Response of NE213 liquid scintillation detectors to high-energy photons (7 MeV < Eγ < 20 MeV), Nucl. Instrum. Methods Phys. Res. A 400 (1997) 356 - 366. [16] M.S.Moore, Rate dependence of counting losses in neutron time-of-flight measurements, Nucl. Instrum. Methods Phys. Res. 169 (1980) 245--247.

EUROPEAN COMMISSION JOINT RESEARCH CENTRE Institute for Reference Materials and Measurements Reference Materials Unit

Increasing our confidence in quantitative GMO analysis by real-time PCR

Date: 30/05/2008

Authors: Wim Broothaerts

Revised by:

Approved by:

TABLE OF CONTENTS

PART 1: DEVELOPMENT OF AN INTERNAL AMPLIFICATION CONTROL ASSAY FOR PCR PERFORMANCE QUALITY CONTROL OF DNA EXTRACTS........................ E-2

1. SUMMARY........................................................................................................................................... E-2

2. INTRODUCTION ................................................................................................................................ E-2

3. RESULTS AND DISCUSSION........................................................................................................... E-3

3.1. Purifying inhibitor-free genomic DNA for analysis .............................................................................E-3 3.2. Assessment of synthetic inhibitors in real-time PCR analysis..............................................................E-3 3.3. Target DNA synthesis and cloning.......................................................................................................E-4 3.4. IAC TaqMan assay. ..............................................................................................................................E-5 3.5. Mon 810 quantification in the presence of the IAC assay. ...................................................................E-7

4. CONCLUSIONS................................................................................................................................... E-7

5. REFERENCES ..................................................................................................................................... E-8

PART 2: THE FAILURE OF THE VALIDATED ADH1 REFERENCE GENE ASSAY FOR GMO QUANTIFICATION .................................................................................................. E-9

1. INTRODUCTION ................................................................................................................................ E-9

2. RESULTS AND DISCUSSION........................................................................................................... E-9

3. CONCLUSION ................................................................................................................................... E-10

4. REFERENCES ................................................................................................................................... E-11

Increasing our confidence in quantitative GMO analysis by real-time PCR E-2 / 11

PART 1: DEVELOPMENT OF AN INTERNAL AMPLIFICATION CONTROL ASSAY FOR PCR PERFORMANCE QUALITY CONTROL OF DNA EXTRACTS

1. SUMMARY

Successful target DNA amplification by real-time PCR depends crucially on the quality of the DNA extract being analysed. There exists no accurate method to assess the PCR performance quality of DNA extracts because the presence of compounds that could inhibit the amplification reaction cannot be easily assayed. The objective of this study, therefore, was to implement an internal amplification control (IAC) for the diagnosis of inaccurate quantitative measurements resulting from the presence of PCR inhibitors in DNA extracts. An inhibitor test model assay was developed to monitor the effect of inhibition on both the IAC and the test assay (Mon 810 maize), assayed in duplex format. Two variants of a synthetic IAC target DNA were produced by DNA synthesis and oligonucleotide assembly, and their final sequences were confirmed by sequence analysis. To amplify these IAC DNA targets, the PCR performance of several combinations of forward primer, reverse primer and probe, were compared and one set of oligos was selected for further analysis in duplex PCR assays. The results showed that, in the absence of inhibitors, the amplification of the IAC DNA was strongly influenced by the initial concentration of the test DNA. We concluded from the results that the IAC assay was not useful as an internal control of the amplification performance of DNA targets present in unknown quantities.

2. INTRODUCTION

The common method for the quantitation of genetically modified organisms (GMOs) in food and feed products is real-time PCR (polymerase chain reaction), in which a short, specific target DNA sequence is multiplied billion-fold and simultaneously detected by a fluorescence spectrophotometer. DNA is isolated from the plant matrix by one of various extraction methods, ideally providing an acceptable DNA yield and sufficient purity. However, both in-house and interlaboratory research has demonstrated an effect of the DNA extraction method on GMO quantification (Corbisier et al., 2007). Various components of plant origin may indeed co-purify with the DNA and chemicals used during extraction may end up in the final DNA extract being analysed. Impure DNA samples may result in PCR inhibition to various degrees, and such inhibition cannot easily be observed during routine analysis. The occurrence of such effects is, unfortunately, often neglected during testing until now and no adequate solutions have been suggested to assess or control the performance quality of the DNA samples. Indeed, current quality assessment relies on gel electrophoresis to visualise DNA degradation and measurement of optical density at fixed wavelengths to roughly assess purity; these techniques provide a very crude and often inaccurate measure for the performance of DNA extracts during real-time PCR. The presence of PCR inhibitors in DNA extracts can only be accurately visualised by labour-intensive experimental set-ups involving diluting individual DNA samples 4-6 times and regression analysis of the amplification signals obtained. In contrast, many labs in the medical, diagnostic and forensic field are using internal positive controls that are externally added to PCR reactions in order to verify the efficient amplification of target sequences, hence assuring confidence in the measurement results. The currently employed internal controls are all aimed at detecting minute quantities of target DNA to avoid false negative results. At high DNA concentrations, these assays fail because the amplification of the internal control is hampered by that of the test DNA.

During the certification of Certified Reference Materials (CRMs) containing GMOs, PCR inhibition at high DNA concentrations is sometimes observed. To be able to detect such inhibition effects, the objective of the current study was to develop an internal control assay that


would act as a sensitive signalling system during co-amplification reactions of test and control DNA targets. The criteria proposed for such a system to work are as follows: 1. it should work uniformally in combination with different test DNA targets; 2. in the absence of inhibition, the amplification efficiency should be close to 100 %; 3. it should display a high sensitivity towards PCR inhibition; and 4. it should be independent of the initial DNA concentration of the test DNA (which is generally unknown and the reason for testing).

3. RESULTS AND DISCUSSION

3.1. Purifying inhibitor-free genomic DNA for analysis

To function as test system to study the effects of inhibitors on TaqMan assays, maize genomic DNA was chosen because of its availability in relatively pure state and our experience with quantitative detection assays. Genomic DNA (gDNA) from Mon 810 maize was preferred because of the additional availability of a plasmid calibrant and the possibility to do duplex PCR for transgene and endogene simultaneously (which may be useful testing to further stretch the boundaries of an IAC assay). Genomic DNA left-overs from the copy number certification study, purified by the DNeasy plant maxi kit from maize leaves, were pooled (31 tubes, final 500 µg) and concentrated by ethanol precipitation. In order to obtain a pool of highly pure gDNA, the DNA was further purified using the genomic tip 500/G purification kit (Qiagen). Seventy (70) % of the DNA was recovered, the final stock concentration was 23 ng/µL, and aliquots were made for storage at -20 °C. In real-time PCR, this DNA produced a highly linear standard curve in the event-specific Mon 810 assay, with a mean PCR efficiency of 93 %.

Figure 1. Example of the performance of the quantitative Mon 810 method on purified genomic DNA from Mon 810 maize.

3.2. Assessment of synthetic inhibitors in real-time PCR analysis

To study the effect of natural inhibitors co-precipitating with DNA on real-time PCR, known potent PCR inhibitors were assessed in the Mon 810 assay. Preparations of xylan from beechwood (acidic polysaccharide), tannic acid and tea extract (both polyphenolic substances) were prepared in MilliQ water and diluted to a series of standard concentrations. Real-time PCR was performed, comparing the Ct values of pure DNA preparations with those obtained in the presence of increasing inhibitor concentrations. Fine-tuning of the inhibitor concentrations was done to see gradual inhibitor effects on PCR performance. The results, shown in Figure 2, revealed that xylan was only inhibiting at very high amounts (25 µg xylan per 25 µL reaction), in contrast to data reported in the literature (Qiagen news, but no information is given on the source of the xylan). This compound was not considered in future experiments because its high concentration in the assay may have unspecific negative effects on the amplification. Tannic acid showed no inhibition when present at <5 ng/µL, a slight inhibition at 7.5 ng/µL, 50 % inhibition

Efficiency = 99 %R2 = 0.999

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Figure 2. Effect of different synthetic PCR inhibitors on the quantitation of Mon 810 maize DNA by real-time PCR

3.3. Target DNA synthesis and cloning.

A 285 bp sequence has been designed of which the codons translate into a protein sequence with the meaningful text "European Commission internal amplification control for real-time polymerase chain reaction" (the space between words was encoded by a stop codon, and the non-existing lettercodes u and o were replaced by the next letter in the alphabet). A variation on the original sequence was also designed by changing an internal sequence stretch into a sequence with a higher G/C content, meanwhile also introducing a perfect hairpin formed by 6 complementary bases separated by a stretch of 12 bases. The rationale behind the alternative target sequence was that the more G/Cs and the presence of the hairpin may make it more difficult for the Taq polymerase to run through this sequence, and hence could be more amenable to and reflective of inhibition in the reaction. The original target was called IAC, while its alternative was called GAC (the "G" referring to the higher G/C content).

To construct the 285 bp sequence (Young and Dong, 2004), 22 overlapping 25 bp oligos were used for the IAC target, as well as 4 additional oligos for the GAC target. Dual Asymmetric PCR (DA-PCR) was performed to convert each 4 adjacent oligos (2 forward and 2 reverse) into a 65 bp double-stranded sequence. In this way, 10 partial fragments were produced for every DNA target, with each fragment overlapping with the next fragment over 40 bp. A feasibility study showed beforehand that the proofreading enzyme Platinum pfx polymerase outperformed both the Platinum Taq polymerase and the AmpliTaq Gold DNA polymerase in terms of amplification efficiency. The 65 bp fragments were purified out of an agarose gel using the QiaExII gel extraction kit, and adjacent fragments were used for further enlargement by overlap-extension PCR (OE-PCR). Although the original protocol foresaw to combine all DA-PCR fragments into a single reaction for OE-PCR, this approach didn't work out in my hands. Instead, further partial fragments were assembled by combining fragments 1+2, 2+3, 3+4, … in a first round of OE-PCR (15 cycles) and standard PCR with the outer primers (30 cycles), then purifying the nine 90 bp fragments (+ a few more for the GAC). Next, another round of OE-PCR and standard PCR generated 115 bp fragments. In a few cases, the second OE-PCR could successfully be performed on the first round OE-PCR products without first amplifying and purifying the PCR products, which saved time. Finally, using the same overlap extension approach, three overlapping 135-140 bp partial fragments (65 bp overlaps) were obtained and these served as template for producing the final 285 bp IAC and GAC sequences through OE-PCR and final PCR with the two outermost primers. After a few attempts, re-amplifying and checking intermediates, trying alternative combinations of the partial fragments and the amplification conditions, and having dealt with a primer contamination, the approach worked for both the IAC and GAC target. The whole step-wise approach is shown in Figure 3. To allow cloning into a TA vector, A-overhangs


were added to the 5' ends of the 285 bp fragments by tailing with Platinum Taq polymerase. The sequences were then cloned by Topo cloning into pCR2.1 vector (Figure 4), transformed into TOP10 cells and selected by blue/white screening and PCR. Sequence analysis showed that one of 2 pGAC colonies analysed contained the correct target sequence (pIRMM-0075). For pIAC, only 1 out of 5 colonies contained the correct sequence (pIRMM-0076), with the others having 1 or 2 mismatches at different positions.

Figure 3. Overview of the approach used to synthesize the IAC target DNA. Short overlapping oligonucleotides (topmost arrow blocks) were first assembled into larger sequences by dual assymetrical PCR (DA-PCR), then further combined with adjacent overlapping sequences by several rounds of overlap extension (OE) PCR and PCR with the outermost primers.

Figure 4. Plasmid map for pIAC and pGAC containing the synthetic target sequences for the IAC and GAC respectively. Both target sequences only differ by the presence of a perfect hairpin sequence in GAC.

3.4. IAC TaqMan assay.

Along the IAC/GAC sequence, primers and probes were selected (Figure 5) using PrimerExpress software, allowing the amplification of fragments between 70 and 275 bp (formed by 4 forward and 5 reverse primers, and 3 probes). To find the most suitable oligo combinations for highly

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efficient amplification, 22 possible combinations of forward and reverse primer and probe were tested in real-time PCR using a fixed plasmid DNA content of 200 copies of pIAC in a 25 µL reaction. Similarly, 20 possible oligo combinations were tested on 200 cp pGAC. All reactions gave Ct values in the range 33.67 – 37.60 for both targets (Figure 6). Interestingly, the P-0700 probe gave larger Ct values (35.61-37.60) than all those obtained with the other two probes (max 35.56), suggesting that it is less efficient in signal generation (despite the fact that it includes the shortest amplicon of all). Although a trend towards higher Ct values for longer amplicons was observed, amplification of a 252 bp sequence occurred quite efficient (Ct of 34.87) and the lowest Cts throughout (around 33.7) were seen for 114 till 181 bp amplicons. pGAC amplification seemed furthermore only slightly less efficient than pIAC amplification, although the difference may not necessarily be significant.

Figure 5. Location of selected oligonucleotides along the IAC/GAC sequence. Arrow blocks denote the forward and reverse primers and the red bars denote the fluorescent probes; the striped primer arrow only binds to the IAC sequence. From left to right, forward primers (pointing to the right) are named 691 to 694, reverse primers 695 to 699, and probes 700 to 702.

Figure 6. Real-time PCR results obtained in simplex PCR assays using various combinations of two primers and a probe on pIAC (upper) or pGAC (lower) as target DNA. The data shown are average Ct (cycle threshold) values obtained using the same amount of DNA in each triplicate reaction; a lower Ct value signifies a more efficient amplification.

Standard curves obtained using either of 3 selected forward primers and 3 reverse primers (together with probe P-0701) all showed a good efficiency (near 100 %) and linearity between 102 and 105 copies per reaction. Amplification of 1 or 10 copies was however either not achieved (Ct > 45) or yielded a Ct value that was outside the linear range of the standard curve obtained. The oligo combination 692/697/701 was selected for further studies (changing the reaction volume to 50 µL for convenience).

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3.5. Mon 810 quantification in the presence of the IAC assay.

When pIAC or pGAC DNA is present at 1000 cp per 50 µL reaction, the amplification of Mon 810 DNA (range 0.1 to 100 % or 50 ng/reaction) is not strongly affected; however, the amplification of the IAC/GAC target is severely hampered at Mon 810 concentrations above 1 % (Ct value increase from 35 up to nearly 42 for 100 % Mon 810). Hence, the low IAC concentration used (1000 cp/reaction) becomes undetectable at high Mon 810 gDNA concentrations, presumably due to interference between both assays. Therefore, higher pIAC/pGAC concentrations were assessed. In the presence of the Mon 810 oligos but no Mon 810 DNA, the IAC assay showed a nearly perfect efficiency between 100 and 105 cp pIAC per reaction (slope -3.30). Similarly, in the presence of the IAC oligos but no IAC target DNA, the Mon 810 assay showed a good efficiency between 1 and 100 % (50 ng). The presence of extra oligos therefore doesn't seem to harm the amplification of either targets. However, the IAC assay is affected by the presence of amplifiable Mon 810 DNA unless the latter is at low concentration (e.g. 1 ng/reaction) and the former at high concentrations (103 to 105 cp/reaction). In the presence of more Mon 810 DNA (10 ng), the amplification of even 1000 cp of pIAC is less efficient, and in the presence of 100 ng Mon 810 DNA, even 105 cp pIAC cannot be efficiently amplified anymore. Similarly, the Mon 810 assay is negatively affected as follows: at low Mon 810 concentration (1 ng), low pIAC concentrations (100-1000 cps) have no effect, but higher pIAC concentrations (104-105) tend to produce lower Cts for Mon 810 (hence more Mon 810 DNA is detected). At 10 ng Mon 810, both low (100 cp) and high (105 cp) pIAC concentrations overestimate the Mon 810 concentration, but intermediate pIAC concentrations (103-104) are detected as they should. At 100 ng Mon 810, analysis of 100 cp pIAC results in an overestimation of Mon 810 DNA, while higher pIAC copies have a less pronounced affect. It seems, therefore, that the correct Mon 810 concentration is only detected when the pIAC and Mon 810 DNA targets are balanced in one or another way. Quantification of the pIAC target is unfortunately differently affected than the Mon 810 target in these combinations.

In order to investigate if the described interference between both assays could be prevented by changing the oligo concentrations, the following experiment was done. Mon 810 DNA at 1, 10 or 100 ng per reaction (or zero) was assayed in the presence of either no pIAC DNA or 1000 or 10000 cp pIAC together with 1x, 2x or 4x IAC oligos (1x corresponding with 300 nM primers and 150 nM probe). The results are puzzling. Increasing IAC-oligo concentrations tend to result in the detection of more pIAC target for all Mon 810 target concentrations. Unexpectedly, in the presence of 1000 cp pIAC, also more Mon 810 DNA is detected when the IAC-oligo concentration increases (for all Mon 810 concentrations studied). At higher pIAC target concentrations, the situation is reversed, however, and much less Mon 810 DNA is detected at higher IAC-oligo concentrations. It is unclear how the IAC-oligo concentration may interfere with the detection of Mon 810, but the issue of interference between DNA concentrations of IAC and GM targets remains.

4. CONCLUSIONS

We have developed new real-time PCR assays targeting either of two invented synthetic DNA sequences that showed a good performance when tested in simplex format. We have not further investigated if the simplex IAC assay could be used as indicator for the presence of PCR inhibitors in DNA extracts. When assayed in duplex format, a strong interference between the amplification efficiency of both tagerts was observed, which render the IAC useless as an internal control of the amplification performance of a test DNA. We, therefore, conclude from the experiments done that the amplification of two DNA targets which are present at strongly differing concentrations cannot occur in a quantitative way.


5. REFERENCES

Corbisier, P., Broothaerts, W., Gioria, S., Schimmel, H., Burns, M., Baoutina, A., Emslie, K., Furui, S., Kurosawa, Y., Holden, M., Kim, H.-H., Lee, Y.-M., Kawaharasaki, M., Sin, D., Wang, J. Toward metrological traceability for DNA fragment ratios in GM quantification. A: Effect of DNA extraction methods on the quantitative determination of Bt176 corn by real-time PCR. J. Agric. Food Chem. 55 (2007), 3249-3257

Kontanis, E.J., Reed, F.A. Evaluation of real-time PCR amplification efficiencies to detect PCR inhibitors. J. Forensic Sci. 51 (2006), 795-804

Young L., Dong, Q. Two-step total gene synthesis method. Nucl. Ac. Res. 32 (2004), e59.


PART 2: THE FAILURE OF THE VALIDATED ADH1 REFERENCE GENE ASSAY FOR GMO QUANTIFICATION

The second part of the exploratory research project focussed on another aspect of obtaining reliable quantitative GMO measurements, which relates to a measurement bias discovered in several of the recommended quantitative GMO detection methods used in the EU. The problem has been thoroughly analysed and the results were recently published. The report below, therefore, contains an extended summary of the information that was described in the manuscript. The full text of the paper can be retrieved from: (http://dx.doi.org/10.1021%2Fjf801636d).

1. INTRODUCTION

The presence of genetically modified organisms (GMOs) in food and feed products is subject to regulation in the EU and elsewhere, which, in some jurisdictions, includes a requirement to label products containing above-threshold GMO concentrations. As part of the authorization process for GMOs in Europe, Regulations (EC) No 1829/2003 and 641/2004 specify that an analytical method for GMO analysis shall be submitted by the notifying party and that this method shall be validated by the Community Reference Laboratory (CRL) for GM Food & Feed, established at the Institute of Health and Consumer Protection of the Joint Research Centre. The preferred approach for GMO quantitation is real-time PCR employing event-specific methods targeting the junction between the inserted transgene and the plant genome. Real-time PCR measures haploid genome copies, and the resulting GMO copy number is expressed in relation to the copy number of an endogenous gene functioning as an invariable reference characteristic for the plant taxon. For the maize taxon, in contrast to soybean, no uniformity exists on reference gene targets for different GMO events, which is related to different GMO producers submitting a method for the detection of a reference gene chosen from various potentially suitable targets. Therefore, different maize GM events are quantified in relation to the copy number of either the high mobility group I protein gene (hmg), the alcohol dehydrogenase 1 gene (adh1), the zein gene, the invertase gene (ivr1), or the starch synthase IIb gene (zssIIb), which are all single or low copy genes. For the adh1 gene, there are even two different detection methods, targeting a region near the 5'-end of the gene (called Zmadh1) or near the 3'-end (called adh1), both regions being separated by roughly 1 kilobasepair (kb). The latter adh1 method is exclusively used in the CRL-validated quantitative methods for the herbicide resistant NK603 and GA21 events and for the insect-resistant MON 863 event, three GMOs submitted for authorization by Monsanto in 2004.

The study presented here was initiated by the observation of different adh1 copy numbers in samples of two maize materials containing NK603. One was a Certified Reference Material (CRM) and the other an unknown sample investigated in the frame of proficiency testing. Alarmed by this finding, the performance of the adh1 detection method was investigated in-depth in comparison with validated methods for other maize reference genes. The study focused on NK603 maize, but impacts the quantitative GA21 and MON 863 maize detection methods likewise.


In this study we have uncovered a systematic error in currently recommended event-specific methods for the quantitation of maize lines GA21, NK603 and MON 863 in the EU. The bias is caused by a sequence polymorphism in the endogenous reference gene used as a denominator in the calculation of the GM percentage. The GMOs mentioned are authorized in the EU for various purposes, including for "food containing, consisting of, or produced from" these GMOs. Reliable quantitative methods form the basis for the implementation and control of the requirement to label products containing GMOs above a defined threshold, following the EU legislation EC


(No) 1829/2003. Inaccurate measurement results, particularly around the threshold value for labeling, may affect the legal requirement whether or not to inform the consumer on the presence of GMOs in a food or feed product.

The study described here has shown that a single nucleotide polymorphism (SNP) located in the middle of the binding region of the reverse primer used for the quantitation of the adh1 reference gene strongly affected the measurement results. Evidence is provided in this study for the occurrence of the AF and FF genotypes in the analyzed RX670 and NK603 varieties, respectively, by sequencing > 1 kb around this region and by allele-specific PCR targeting a region in the gene displaying two other SNPs and a two-base indel, which are exclusively present in adh1-F. It could be shown that the used GA21 accession also bears the FF-genotype, while signals for both alleles were obtained in the MON 863 and MON 863 x MON 810 varieties available for CRM processing at IRMM. Convincing proof that the two latter varieties possess, in addition to the F-allele, the A-allele or possibly the Cm- or S-allele, which are not discriminated by the "A-specific" assay, would require sequence information from a larger region of their adh1 gene. This was beyond the purpose of this study which aimed at exploring the causes of the biased adh1 quantitation, which was traced back to a polymorphism in the reverse primer binding region.

The investigations presented here exploited a plasmid carrying several target sequences for calibrating the real-time PCR measurements. The use of cloned fragments for the quantitative comparison of different reference gene methods was not reported before. A plasmid, bearing the embedded sequences for 4 common maize reference gene targets, in addition to that for the NK603 event, was used to analyze their relative quantities in different maize varieties. The screening of several maize varieties using this plasmid for calibration revealed the wide occurrence of the observed polymorphism at the adh1 target region.

To enhance the quality of the analytical methods for GMOs in the future, the presence of SNPs or other polymorphisms and their possible effects on the analysis should be more carefully investigated in the course of the method development. The current legislation clearly demands applicants for GMO authorization under EC No 1829/2003 to justify how and why the proposed primer pair has been selected and to provide experimental results from testing the method with different varieties. A stronger emphasis should also be given to homology searches to show the absence of polymorphisms within the targeted sequences during the method validation process. It is evident from the study presented here that the method validation should not only focus on the specific GM event, but also on the reference gene used for the relative expression of the GMO fraction.

In general, the results of this study plead for an in-depth comparison of the quantitative methods targeting different endogenous genes in several species. This should lead to the harmonization of taxon-specific reference systems used in GMO testing.

3. CONCLUSION

The real-time PCR methods recommended in the EU for the quantitation of the genetically modified (GM) maize events NK603, GA21 and MON 863 measure the number of copies of the GM gene in relation to those of the maize-specific adh1 reference gene. The study reported here revealed that the targeted 70 basepair adh1 region exhibits a single nucleotide polymorphism (SNP) that hampers the binding of the reverse primer used in the adh1 detection method. This severely affects the amplification of the reference gene. Furthermore, it is shown that the SNP corresponds to an allelic polymorphism occurring in several maize varieties studied. As a result, the quantitation of the GM maize events mentioned is positively or negatively biased, depending on the calibrant used in the methods and on the genetic make-up of the intermixed non-GM variety. Therefore, it is proposed to revise the quantitative detection methods for NK603, GA21 and MON 863 maize.


4. REFERENCES

Wim Broothaerts, Philippe Corbisier, Heinz Schimmel, Stefanie Trapmann, Sandra Vincent, Hendrik Emons (2008) A single nucleotide polymorphism in the adh1 reference gene affects the quantitation of genetically modified maize (Zea mays L.). J. Agric. Food Chem. (advanced webrelease on http://dx.doi.org/10.1021%2Fjf801636d).

EUROPEAN COMMISSION JOINT RESEARCH CENTRE Institute for Reference Materials and Measurements Isotope Measurements

"Metal solid phase extraction from natural, saline and waste waters using TiO2 nano-

particles: method development"

Emilia Vassileva1, Ivan Petrov1, Christophe Quétel1* Kristina Chakarova2, Konstantin I. Hadjiivanov2

1: EC-JRC-IRMM 2: Institute of General and Inorganic Chemistry, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria *: corresponding author (Christophe.Qué[email protected])

Date: 23/06/2008

Authors: Quétel Christophe

Revised by: Verbruggen André

Approved by: Taylor Philip

TABLE OF CONTENTS SUMMARY........................................................................................................................F-2 1. INTRODUCTION .......................................................................................................F-3 2. EXPERIMENTAL.......................................................................................................F-5 2.1 Instrumental.........................................................................................................F-5 2.2 Reagents, samples and materials .........................................................................F-8 2.3 Preparation of TiO2 (anatase) and investigations on sites involved during Fe

adsorption ............................................................................................................F-9 2.3.1 Cleaning ..............................................................................................................F-9 2.3.2 Investigations on the active sites available for the Fe adsorption .......................F-9 2.4 Batch and on-column experiments ....................................................................F-11 2.4.1 Batch experiments .............................................................................................F-11 2.4.2 Column preparation and on-column experiments .............................................F-11 2.5 Calibration by isotope dilution ICP-MS............................................................F-13 2.5.1 Calculation of the amount of added spike and preparation of blend solutions .F-13 2.5.2 Selection of isotopes to be measured and ICP-MS measurements....................F-13 2.6 Method validation and evaluation of the measurement combined uncertainty.F-14 3. RESULTS AND DISCUSSION ....................................................................................F-14 3.1 Characterisation of the TiO2 phase and determination of Fe in seawater.........F-14 3.1.1 Fe solid phase extraction from coastal seawater using anatase TiO2 nanoparticles......................................................................................................F-14 3.1.1.1 General adsorption behaviour............................................................................F-14 3.1.1.2 Optimisation of the Fe separation efficiency conditions...................................F-19 3.1.1.3 Effect of the iron mass fraction and experimental conditions on recovery rates ...........................................................................................................F-21 3.1.1.4 Procedural blank and limits of detection ...........................................................F-21 3.1.1.5 Method validation..............................................................................................F-21 3.2 Determination of Cd in natural waters ..............................................................F-24 3.2.1 Optimisation of the conditions for Cd solid phase extraction using anatase TiO2 nanoparticles ............................................................................................F-24 3.2.1.1 Effect of pH conditions during sample loading.................................................F-24 3.2.1.2 Effect of the eluent acidity conditions...............................................................F-25 3.2.1.3 Effects of sample flow rates ..............................................................................F-25 3.2.2 External calibration experiments on pure water samples ..................................F-25 3.2.2.1 Effect of cadmium concentration and sample matrix on recovery rates ...........F-25 3.2.2.2 Procedural blank and limits of detection ...........................................................F-26 3.2.2.3 Application to the Euramet-924-1 sample and method validation....................F-26 3.2.3 IDMS calibration experiments on natural water samples..................................F-27 3.2.3.1 Procedural Blanks and limits of detection.........................................................F-28 3.2.3.2 Correction of interferences ................................................................................F-28 3.2.3.3 Application to the Euramet-924-2 sample and method validation....................F-29 4. CONCLUSIONS .......................................................................................................F-33 5. REFERENCES .........................................................................................................F-34

Metal solid phase extraction from natural, saline and waste waters using TiO2 nano-particles: F-2 / 35 method development

SUMMARY

This study describes validated methods for the application of high surface TiO2 nano-particles (anatase form) to the solid-phase extraction of iron from coastal seawater and cadmium from natural water samples.

The conditions for quantitative and reproducible separation, elution and subsequent off-line ICP-MS determination of iron and cadmium were investigated. Optimum separation and removal of Ca, Na and Mg from typical natural samples was studied by variation of sample size, loading pH, sample and elution rates. Samples adjusted at pH 7-8 were pumped through the column at 1.7 g min-1 and sequentially eluted with 6% HCl for determination of iron or 6% HNO3 for determination of cadmium. Recoveries between 65% and 80 % were obtained. We investigated the adsorption processes of iron on TiO2 surface by infra red spectroscopy, and we compared in batch and on-(mini)column extraction approaches (0.1g and 0.05g TiO2 per sample, respectively), combined to inductively coupled plasma mass spectrometry at medium mass resolution. The mechanism of iron preconcentration on high surface TiO2 was investigated with IR spectroscopy and different reaction schemes are proposed between Fe (III) species and the two main categories of titania sites at pH 2 (adsorption of [FeLx](3-x)+ via possibly the mediation of chlorines) and at pH 7 (adsorption of [Fe(OH)2]+ and precipitation of [Fe(OH)3]0).

Two calibration strategies - external calibration and Isotope-Dilution ICP-MS were applied.

The overall procedural blanks were 220 ± 46 (2s, n=16) ng Fe kg-1 and 17.7 ± 2.3 (2s, n=16) ng Cd kg-1. The recovery efficiency for iron estimated from the Canadian CRM CASS-2 was 69.5 ± 7.6 % ± 2.3 whereas recovery efficiency for cadmium estimated from pure water spiked solution was 93.2± 9.2 (2s, n=4). Typically, the relative combined uncertainty (k = 2) estimated for the measurement of ~1 ng Fe g-1 (0.45 µm filtered and acidified to pH 1.5) of seawater was ~12%. The relative combined uncertainty (k = 2) estimated for the measurement of ~0.2 ng Cd g-1 was ~10% and 4.7% by external calibration and IDMS, respectively.

Keywords: Iron, cadmium, solid-phase extraction, TiO2, seawater, on-line separation, inductively coupled plasma mass spectrometry, mechanism of retention, infrared spectroscopy, uncertainty estimation, method validation


1. INTRODUCTION

Often, metals present at trace levels in natural, saline and waste waters cannot be measured directly, and must be separated from a wide range of sample components, and concentrated. Different reviews exist that describe the analytical solutions available depending on elements targeted and the nature and the complexity of aqueous sample matrices. These include, as described in ref. 1, liquid–liquid extraction, coprecipitation, ion-exchange, evaporation, electrochemical deposition and solid-phase extraction (SPE). Comparatively, SPE involves generally fewer reagents in smaller amounts, requires smaller size water samples (≤ g level) and is potentially faster and less tedious than most other approaches. It also gives the possibility to achieve low matrix content, to set-up simple operation protocols and to use closed circulation systems that can easily be coupled to multi-elemental highly sensitive spectrometric techniques such as inductively coupled plasma mass spectrometry (ICP-MS). Different categories of solid sorbents have been described, including chelating ion exchangers [2], iminodiacetate chelate resin [3], immobilized chelating reagents on solid supports [4], and various kinds of metal oxides [5]. Metal oxides are particularly interesting because they are fast, selective and fully reversible (regeneration) sorbents. They can be synthesised under the form of less than 100 nm large particles (nanomaterials), and are thus characterised by large active surface areas (up to almost 100 m2 g-1). Metal oxides such as alumina (Al2O3), ceria (CeO2), zirconia (ZrO2) or titania (TiO2) offer selective multi-element extraction possibilities over a wide pH range, while matrix elements are weakly adsorbed [6]. The retention capacity, for most of them, depend on pH conditions, and according to Vassileva et al. [7] the regime is changed whether the pH is above or below the isoelectric point (IEP) of the oxide [8]. The versatility of these metal oxides for trace metals separation/preconcentration from a wide variety of environmental matrix samples is illustrated in Table 1 [references 1, 5, 7, 9-15]. To the best of our knowledge only few results have been reported regarding the extraction of iron with metal oxides from complex matrix samples [5, 10]. Seawater is one the most complex types of environmental samples. Iron concentration in open oceanic waters is in the nanomolar range or below, and the determination of the dissolved iron content in seawater requires rigorous analytical methods. In 1990 the ‘iron hypothesis’ was proposed, suggesting that addition of iron to 'high nutrient-low chlorophyll’ ocean regions would stimulate photosynthesis and phytoplankton blooming, which in turn would promote the ‘carbon pump’ [16, 17], and thus help decreasing the level of CO2 in the atmosphere. Within the last ten years, several oceanographic campaigns were conducted to test it and to better understand the Fe.

Metal solid phase extraction from natural, saline and waste waters using TiO2 nano-particles: method development F-4 / 35

Table 1 Summary of recent applications of high surface metal oxides for the separation of trace elements from natural waters

Analyte Matrix Oxide Concentration level, µg L-1 pH Flow rate,

mL min-1 Adsorption

capacity, g kg-1 LOD, µg L-1 Detection instrument Reference

Cu, Hg, Au, Pd lake water Modified Al2O3

6.6; 4.03; 0.62; 0.29 3 1.5 10.4; 16.3; 15.3; 17.4

6.6E-05; 4.9E-04; 4.6E-04; 2.6E-04 ICP-MS [9]

Cd, Cu, Pb, Zn, Fe river, waste water CeO2

0.94-0.26; 2.1-0.3, 2.8-0.28; 25.6-0.69; n.d. ≥ 7 3

13.27; 13.31;13.33; n.d.;

n.d.

1E-4; 2E-4; 3E-4; 1E-5; 5.0E-03 ETAAS [10]

Al, Bi, Cd, Co, Cr, Cu, Ga, In,

Mn, Mo, Ni, Pb, Tl, V, Sb, Sn,

Zn, Fe

river water, sea water ZrO2 1.06-60.8 for all (Fe ~56.1), ~14 for all seawater (Fe~13.7)

8 3 4.97-7.89 range for all

3E-3 - 9E-3 for all (Fe 7.0E-03) FI-ICP-AES [5]

Bi, Cd, Co, Cr, Cu, Ge, In, Mn, Ni, Pb, Sb, Sn, Te, Tl, V, Zn

Fe

natural waters TiO2 1.3-7.3 range for all (Fe 9.57) 8 3

4.6 - 9.01 range for all

(Fe n.d.)

1E-2 - 3E-2 range for all

(Fe 4.0E-02) ETAAS [11]

Cr, C, Mn, Ni lake water TiO2 170 - 33600 range for all 8 1 2 - 7.7 range for

all 0.34 - 1.78 range for

all ICP-AES [1]

Cr3+, Cr6+ rain water TiO2 0.03 - 0.42 range for all

8, 2 3 7.50 0.03, 0.024 ETAAS [7]

Cr3+, Cr6+ tap, lake water TiO2 0.32 - 0.78, 0.57 - 0.99

range for all 6 Cr3+ 1 7.6 Cr3+ 0.32 ICP-AES [12, 13] Cr3+, Cr6+ seawater TiO2 2 - 11 range for all 2 Cr6+ 1 4 Cr6+ 0.08, 0.07 ICP-MS [14]

SeIV, SeVI natural water TiO2 0.18 - 11.97 8 0.1 n.d. 0.06, 0.03 HPLC-ICP-MS [15]


marine biogeochemistry, IronEx I&II, 1993 & 1995, SOIREE 1999, Eisenex 2000, SEEDS 2001, SOFeX 2002, SERIES 2002 [18], EIFeX 2004 [19]. One of the important conclusions of these studies was that “each analytical method gave significantly different dissolved iron concentrations at the 95% confidence interval” [20]. Furthermore, it was found that "the overall range of the IRONAGES sample (0.23–1.19 nM) is unacceptably large and, if plotted as a single depth profile, these data would appear oceanographically inconsistent" [21]. The reasons for these difficulties include the combination of low concentrations to high risks of sample contamination, and the high salinity of natural water samples. The isotope dilution (ID) ICP-MS based method, involving a chemical extraction of iron from a co-precipitation with magnesium, was reviewed at IRMM, and two first papers were published [22, 23]. We consider that a TiO2 SPE based method should be envisaged as an alternative to this chemical extraction approach, at least for coastal seawater samples to start with. This was never reported in the literature. Finally, the new Water Framework Directive (WFD) has introduced drastic limits for the cadmium content in underground waters, e.g. no higher than 0.2 μg/l. Measuring cadmium routinely at this level is not simple, particularly because the risks of sample contamination are severe. Introducing a TiO2 SPE based method to extract the cadmium and concentrate it at this level was never described, and might represent an important progress toward better reproducibility and reliability of this type of measurements. With the introduction of the new directives on fresh and marine waters, methods potentially capable of addressing low metal content levels are needed and must be developed. In that respect the SPE approach using TiO2 packed into mini-columns is particularly attractive. Additionally, combining these developments to metrology in chemistry concepts such as those commonly applied at IRMM (IDMS as a primary method of measurement, complete uncertainty estimation for the measurement result) will further reinforce their robustness. The objectives of this exploratory research project included: 1- Synthesis of anatase TiO2 nano-particles 2- Establishing the conditions for reproducible blank results 3- Developing a mini-column system 4- Characterising the surface of TiO2 particles under different conditions of pH and sample matrix 5- Identifying and optimising the analytical conditions for the measurement of the Fe content in seawater using the the titania phase. Comparing batch and mini-column results. 6- Transposing results and conducting necessary additional investigations specific to cadmium in natural waters

2. EXPERIMENTAL

2.1 Instrumental

Fourier transformed infra red, FTIR, spectra for the characterisation of TiO2 were recorded on a Nicolet Avatar 360 spectrometer (Nicolet, Madisson, USA) at a spectral resolution of 2 cm-1 and accumulating 128 scans. ICP-MS measurements were performed at medium mass resolution (m/∆m ∼ 4000) on an Element2 (ThermoFinnigan MAT, Bremen, Germany) equipped with standard Ni-cones. The self-aspirating ‘SeaSpray’ nebulizer from Glass Expansion (P/N AR35-1-FSS04, West Melbourne, Australia) of declared sample uptake rate 400 µL min-1 was attached to a non cooled mini-cyclonic


quartz ‘Cinnabar’ from Glass Expansion (P/N 809-0188). An autosampler ASX-500, model 510 (CETAC Technologies, Omaha, USA) was employed. Details about the Element2 optimisation are discussed elsewhere [22], and operating conditions are summarised in Table 2.

Centrifugation of batch samples was conducted with an Eppendorf 5810R (Eppendorf, Hamburg, Germany) centrifuge equipped with a universal fixed-angle rotor (F34-6-38).

A Minipuls3 peristaltic pump (Gilson, Villiers le Bel, France) was utilised for passing the samples trough a mini-column packed with TiO2.


Table 2 ICPMS (ThermoFinnigan Element2) experimental settings and operating conditions

Parameter Fe experiments Cd experiments

Cool gas (L min-1) 16.00 15.91 Auxiliary gas flow (L min-1) 0.90 0.85 Sample gas flow (L min-1) 1.05 1.05 Plasma power (W) 1200 1270 Sensitivity, 1 µg kg-1 Co/Rh (cps) 1 000 000 1 000 000 Background on mass 220 (cps) 0 0 Dead time (uncertainty k=2) (ns) 14 (3) 15 (3) Measured isotopes 56Fe, 57Fe, 35Cl 36Ar 110Cd, 111Cd Mass resolution Medium Low Detection mode ‘Counting’ Both Mass window (%) Sample time (ms) Samples per peak

150 5; 2 for 35Cl 36Ar 30

5 100 100

Search window (%) 150 150 Integration window (%) Passes Runs Scans

40 30 5 150

80 200 6 1200

Analysis time per sample (min:sec) 1:19 2:00


2.2 Reagents, samples and materials

FTIR investigations involved carbon monoxide (>99.997% purity) from Linde AG (Munich, Germany), passed through a liquid nitrogen trap before use. Ultra pure deionised water from a Milli-Q system (Millipore, Bedford, USA) and high purity grade HNO3 and NH3 (Ultrex®, J.T. Baker, Phillipsburg, USA) were used throughout this work. Merck pH strips (Darmstadt, Germany) were used to evaluate pH conditions. The mini separation column was in Perspex (Daviron Instruments Ltd., Devon, UK) and was prepared with 100 µm glass beads from Sigma (Seelze, Germany). Assembling parts of the column setup were in plastic exclusively and involved washers (P/N F-728-16, Bohlender, Grunsfeld, Germany), Omnifit (Cambridge, UK) fittings and PTFE and Peek tubing (Upchurch Scientific, Oak Harbour, USA).

Working standard solutions of iron were prepared daily by gravimetrical dilution with 6% w/w HCl of a 1000mg Fe kg-1 solution from Johnson Matthey (London, United Kingdom). The coastal seawater CRM CASS-2 (National Research Council of Canada, Ottawa, Canada) with a certified Fe content of 1.20 ± 0.12 µg L-1 (95% confidence interval) was used for estimation of the final recovery rate under optimized conditions. The proposed analytical procedure was applied to a sample from the costal North Sea (0.45 µm filtered and acidified to pH 1.5).

A commercial Cd solution (nominally 1000 μg L-1) from Johnson Matthey was used to produce a working stock solution of Cd in 2% w/w HNO3. The Cd mass fraction in this working stock solution (257.2±3.0 μg kg-1) was established by IDMS. A daughter solution (named ‘Sample A’ hereafter, with Cd mass fraction = 135.7±3.0 ng kg-1) was established by dilution through metrological gravimetry (weighing certificate E3630) in a humidity-controlled area using substitution measurements against operational mass standards. Additionally, 4 calibration solutions were produced by dilution of ‘Sample A’ also exclusively through metrological gravimetry (weighing certificate E 3639). The ground water CRM BCR-609 (EC-JRC-IRMM, Geel, Belgium) with a certified Cd mass fraction of 164 ± 12 ng Cd kg-1 (k=2) was used for estimation of the final recovery rate for Cd. The proposed analytical procedure was applied to the two Euramet-924 test materials. First, the low level Cd Euramet 924-1 sample, prepared by the German “Federal Institution of Material Research and Testing” (BAM) by adding gravimetrically Cd to ultra pure water. Second, the low level Cd Euramet 924-2 sample, prepared by the French “National Testing Laboratory" (LNE) by adding gravimetrically Cd to filtered natural surface water. The IRMM-622 certified isotopically enriched (111Cd) material was used as the IDMS ‘spike’. Natural isotopic composition (using IUPAC data [24] as reference values) was assumed for Fe and Cd in samples, as well as for the 2 ng.g-1 Cd solution (prepared by dilution of the Johnson Matthey solution) used to correct Cd isotope ratio measurements for mass discrimination.

Reagents and water were stored in Teflon bottles; samples and elemental standard solutions were stored in polyethylene bottles or metal free polypropylene centrifuge tubes (Elkay Laboratory Products Ltd, Hampshire, UK). Only new labware material was employed and cleaned thoroughly applying a procedure described elsewhere [23]. All operations of sample preparation, except the centrifugation step, were performed in the class 10 ultra-clean chemical laboratory of IRMM [25] using designated clothes and dust free vinyl gloves.


2.3 Preparation of TiO2 (anatase) and investigations on sites involved during Fe

adsorption

The titania used in this study was of the anatase form, synthesised from TiCl4 following a procedure described elsewhere [11]. This powder can be classified as nanomaterial (measurements by transmission electron microscopy indicated dimensions < 50 nm for over 99% of these TiO2 particles). The specific surface area was ~ 83 m2 g-1 (determination by the 'BET method').

2.3.1 Cleaning

Before use the TiO2 produced (10 g) was repeatedly cleaned with portions of 50 g 3M HCl for Fe and 6M HNO3 for Cd, respectively. The iron and cadmium contents in the supernatant after each cleaning step were determined. The repeated application of the cleaning protocol improved considerably the TiO2 purity - from 7 to 0.15 �g Fe kg-1 found in the supernatant (Figure 1) and from 21 to < 1 ng Cd kg-1. Thus, the absolute amount of Fe and Cd released by 0.1 and 0.05 g of TiO2 (amounts of powder required for batch and on-column applications) were conservatively estimated to be not more than 75 and 37.5 pg iron and 0.5 and 0.25 pg Cd, respectively. For mini-columns experiments, the absolute procedural blank of TiO2 was evaluated to be 103 pg for iron (i.e. incl. 65 pg Fe contribution from the glass beads) and 0.5 pg for cadmium Cd (i.e. incl. 0.25 pg Cd contribution from the glass beads).

It must be noted that this material can be up to 20 times providing that careful cleanups are carried out in between applications.

2.3.2 Investigations on the active sites available for the Fe adsorption

The nature of the sites on anatase TiO2 potentially available to adsorption is discussed in detail in [26]. Depending on the conditions of pre-treatment of this material (T of activation), approximately 5% of these sites are hydroxyl groups [27]. The other sites arise from coordinatively unsaturated surface (c.u.s.) ions that have a tendency for additional coordination. The breaking of the crystal lattice at the surface leads to the appearance of these ions, with a lower coordination number than that in the bulk. Cations (essentially Ti4+) possess an uncompensated positive charge and coordinate molecules with a free electron pair, i.e. they are Lewis acids, while the c.u.s. oxygen anions (O2-) are Lewis bases and adsorb acidic molecules and cations [27]. The IEP of TiO2 is 6.2 [8]. When the pH of the solution is higher than this value the titania surface is covered essentially with OH- groups and is negatively charged, and the adsorption of cations is favoured [26]. However, not all c.u.s. Ti4+-O2- couples available on the surface may be available for this adsorption as shown in the case of Cu2+, Co2+ and Ni2+ cations [27, 28]. In contrast, when pH < 6.2 the titania surface is positively charged, because it is covered essentially with hydroxonium groups, and adsorption of anions is favoured [26]. It is more difficult to explain the mechanism of cation adsorption under acidic conditions.

In solution, the consumption of OH groups after adsorption of ions can be easily and directly monitored by IR spectroscopy of activated samples. The same technique can be used to obtain information about the occupation rate of surface Ti4+ ions (possibly also of surface O2- ions, by deduction) and the state of adsorbed ions, but intermediate probe molecules (CO molecules in this study) must be involved [26].


Fig. 1. Evolution of the iron (1a) and cadmium (1b) content in the washout solution over repeated cleaning cycles of the high surface area TiO2 (10 g, anatase in 50 g solution) synthesised for this study

Five samples were investigated in the present study: dry TiO2 used as a reference (sample 1), and 4 samples submitted to high amounts of dissolved iron (1000 μg Fe3+ g-1) in ultra pure water and seawater media at a pH below (pH 2, samples 2 and 3) and above (pH 7, samples 4 and 5) the titania IEP. After filtration and multiple washing with MilliQ water, samples were dried at ambient temperature under clean room conditions. The Fe mass fraction in the model solutions, much higher than in usual seawater samples, was necessary owing to the poor sensitivity of IR spectroscopy.

Self-supporting pellets (ca. 10 mg cm-2) were prepared from the application of 106−107 Pa pressure to each of the 5 types of powder samples. These pellets were introduced in purpose-made IR cells connected to a vacuum-adsorption apparatus (able to provide residual pressure conditions < 10-3 Pa).

The method used to characterise our TiO2 samples included the following steps.

Step 1- Activation (removal of any organic contaminants and adsorbed water) of the surface of the TiO2 powder at 573 K for 1 h under oxygen pressure, and

0

5

10

15

20

25

Cleaning steps

Con

tent

Cd,

ng

kg-1

0

2

4

6

8

10

Con

tent

Fe,

μg

kg-1

1a

1b

0

5

10

15

20

25

Cleaning steps

Con

tent

Cd,

ng

kg-1

0

2

4

6

8

10

Con

tent

Fe,

μg

kg-1

1a

1b


subsequent evacuation for another hour at the same temperature => acquisition of an IR spectrum (data used for normalised results reported in Table 3 for the hydroxyl bands 3735 cm-1, 3718 cm-1, 3675 cm-1 and 3642 cm-1)

Step 2- Lowering of the temperature to 100 K, and adsorption of CO (667 Pa equilibrium pressure) => acquisition of an IR spectrum

Step 3- Gradual evacuation at 100 K during one hour until spectra stop changing => acquisition of an IR spectrum for each pressure stage. Last set of data (i.e. under stabilised conditions) were used for normalised results reported in Table 3 for bands at 2209 cm-1 and 2184 cm-1

Step 4- Gradual increase of the temperature up to 298 K (disappearance of all carbonyl bands) => acquisition of an IR spectrum for each temperature stage

Beside, the amounts of iron immobilised on each of these test samples were measured (relatively to the respective amounts of titania powders). The iron was quantitatively recovered using the extraction protocol described below, and quantified by ICP-MS (3 points external calibration). Apparent Fe retention rates reported in the last column of Table 3 are results normalised to those obtained at pH 2 in an ultra pure water medium (sample 2).

2.4 Batch and on-column experiments

Using the same starting TiO2 material conditioned as a slurry suspension in Milli-Q water, in batch and on-column approaches were compared (description of the procedures developed in Fig. 2). In both cases controlled amount of NH3 were used to adjust pH conditions and controlled amount of HCl 6% or 6% HNO3 were used to recover the Fe respectively Cd adsorbed on TiO2.

2.4.1 Batch experiments

Batch experiments were carried out in centrifuge tubes containing aliquots of the suspension with ~0.1 g TiO2. Prior to the procedure described in Fig. 2a, the powder was allowed to sediment and the supernatant was eliminated.

2.4.2 Column preparation and on-column experiments

The procedure for on-line separation of iron from seawater is described in Fig. 2b, using a Perspex column (Fig. 3). This column was filled up with an aqueous slurry of TiO2 (0.05g), mixed with glass beads (1:1, w:w) to increase the porosity of the column and closed at both ends with a pair of plastic washers. The column was connected to PTFE tubing (i.d. 0.8 mm; o.d. 1.6 mm) with Omnifit fittings (Tefzel® tube ends P/N 2130 and inverted cones P/N 1544). Then the column was connected to a peristaltic pump. In this configuration the pH adjustment was performed via on-line mixing (Y-connector) of the sample with aq.NH3 (PTFE tubing, i.d. 0.3 mm; o.d. 1.6 mm), which was controlled with a 2-way valve. The seawater, Milli-Q water, diluted HCl and ammonia probes (No.12 on Fig. 3) were Peek tubing with o.d. 1.6 mm, i.d. 0.8 mm and 0.5 mm, respectively. The whole separation system, except the peristaltic pump, was placed in a class-10 ultra-clean fume hood.


Figure 2: Schematic diagrams of batch and on-column protocols for the separation of iron from seawater using high surface area TiO2 (anatase). A, B and C correspond to the 3 main successive stages of the on-column method

Figure 3: Schematics of the column setup for the on-line separation of Fe from seawater

Once assembled the inlet system was pre-cleaned by pumping for ~2h 6% HCl and 2M HNO3 for Fe or Cd experiments, respectively, and the column was conditioned by

mmColumn dimensions

15Column diameter

30Cavity length

2Cavity diameter

50Column length

mmColumn dimensions

15Column diameter

30Cavity length

2Cavity diameter

50Column length

Legend:1- PERSPEX column with TiO22- TiO2:glass beads = 1:1 (w/w)3- Tefzel® fitting/inverted cone4- PTFE tubing*5- Frit6- Plastic washer7- NH4OH 0.05% (w/w) 8- MilliQ water for conditioning9- Sample10- HCl 6% (w/w)11- Eluted sample 12- PEEK tubing13- Peristaltic pump14- 2-way valve15- Waste16-Y-connector*Connected to peristaltic pump with

Tygon® tubing

4

4

3

3

2

5

6

1

4

4

3

3

2

5

6

1

13

Class-10 clean fume hood

1

4

14

13

12

7

12

118 9 10

Alternating

15

12

13


1

4

14

13

12

7

12

118 9 10

Alternating

15

13


1

4

14

13

12

7

12

118 9 10

Alternating

15

1313


1

4

14

13

12

7

12

118 9 10

Alternating

Class-10 clean fume hoodClass-10 clean fume hood

111

4

14

4

1414

13

12

7

12

7777

12

11

12

11118 9 10

Alternating

88 99 1010

Alternating

151515

12

Column

0.1 g TiO2 : glass beads (1:1)

u.p.H2O / NH4OH 0.05% (w/w)

3 g SW / NH4OH 0.05% (w/w)

3 g HCl 6% (w/w)

ICP-MS

1min at 1.7 mL min-1

at 1.7 mL min-1

at 1.5 mL min-1

Batch

0.1 g TiO2

5 g seawater

190 μL NH4OH 0.5% (w/w)

at 8.5k rpm for 20min



Phases separation

5 g HCl 6% (w/w)

Shake & 1 h to rest

1 night

1h to rest

ICP-MS

Phases separation

Column


u.p.H2O / NH4OH 0.05% (w/w)

3 g SW / NH4OH 0.05% (w/w)

3 g HCl 6% (w/w)

ICP-MS


at 1.7 mL min-1

at 1.5 mL min-1

Column

0.1 g TiO2 : glass beads (1:1)0.1 g TiO2 : glass beads (1:1)

u.p.H2O / NH4OH 0.05% (w/w)

3 g SW / NH4OH 0.05% (w/w)3 g SW / NH4OH 0.05% (w/w)

3 g HCl 6% (w/w)

ICP-MS


at 1.7 mL min-1

at 1.5 mL min-1

Batch

0.1 g TiO2

5 g seawater

190 μL NH4OH 0.5% (w/w)




Phases separation

5 g HCl 6% (w/w)

Shake & 1 h to rest

1 night

1h to rest

ICP-MS

Phases separation

Batch

0.1 g TiO2

5 g seawater5 g seawater

190 μL NH4OH 0.5% (w/w)190 μL NH4OH 0.5% (w/w)

at 8.5k rpm for 20minat 8.5k rpm for 20min



Phases separationPhases separation

5 g HCl 6% (w/w)5 g HCl 6% (w/w)

Shake & 1 h to rest

1 night

1h to rest

ICP-MS


On-column

3 g seawater at 1.6 pH

3 g HCl 6% (w/w)

NH4OH 0.05% (w/w)at 1.7 g min-1 at 0.6 g min-1

0.05 g TiO2 + 0.05 g glass beads

0.85 g ultra-pure water

at 1.7 g min-1

at 1.5 g min-1

A

B

C

ICP-MS

Column


u.p.H2O / NH4OH 0.05% (w/w)

3 g SW / NH4OH 0.05% (w/w)

3 g HCl 6% (w/w)

ICP-MS


at 1.7 mL min-1

at 1.5 mL min-1

Batch

0.1 g TiO2

5 g seawater

190 μL NH4OH 0.5% (w/w)




Phases separation

5 g HCl 6% (w/w)

Shake & 1 h to rest

1 night

1h to rest

ICP-MS

Phases separation

Column


u.p.H2O / NH4OH 0.05% (w/w)

3 g SW / NH4OH 0.05% (w/w)

3 g HCl 6% (w/w)

ICP-MS


at 1.7 mL min-1

at 1.5 mL min-1

Column


u.p.H2O / NH4OH 0.05% (w/w)


3 g HCl 6% (w/w)

ICP-MS


at 1.7 mL min-1

at 1.5 mL min-1

Batch

0.1 g TiO2

5 g seawater

190 μL NH4OH 0.5% (w/w)




Phases separation

5 g HCl 6% (w/w)

Shake & 1 h to rest

1 night

1h to rest

ICP-MS

Phases separation

Batch

0.1 g TiO2







5 g HCl 6% (w/w)5 g HCl 6% (w/w)

Shake & 1 h to rest

1 night

1h to rest

ICP-MS


Column


u.p.H2O / NH4OH 0.05% (w/w)

3 g SW / NH4OH 0.05% (w/w)

3 g HCl 6% (w/w)

ICP-MS


at 1.7 mL min-1

at 1.5 mL min-1

Batch

0.1 g TiO2

5 g seawater

190 μL NH4OH 0.5% (w/w)




Phases separation

5 g HCl 6% (w/w)

Shake & 1 h to rest

1 night

1h to rest

ICP-MS

Phases separation

Column


u.p.H2O / NH4OH 0.05% (w/w)

3 g SW / NH4OH 0.05% (w/w)

3 g HCl 6% (w/w)

ICP-MS


at 1.7 mL min-1

at 1.5 mL min-1

Column


u.p.H2O / NH4OH 0.05% (w/w)


3 g HCl 6% (w/w)

ICP-MS


at 1.7 mL min-1

at 1.5 mL min-1

Batch

0.1 g TiO2

5 g seawater

190 μL NH4OH 0.5% (w/w)




Phases separation

5 g HCl 6% (w/w)

Shake & 1 h to rest

1 night

1h to rest

ICP-MS

Phases separation

Batch

0.1 g TiO2







5 g HCl 6% (w/w)5 g HCl 6% (w/w)

Shake & 1 h to rest

1 night

1h to rest

ICP-MS


On-column


3 g HCl 6% (w/w)




at 1.7 g min-1

at 1.5 g min-1

A

B

C

ICP-MS

On-column


3 g HCl 6% (w/w)




at 1.7 g min-1

at 1.5 g min-1

A

B

C

ICP-MS


aspirating ultra pure water (1.7 g mn-1) and 0.05% ammonia (0.6 g mn-1) for 1 min. Then 3 grams seawater sample were loaded at the same flow rate while being mixed on-line with 0.05% ammonia at 0.6 g mn-1 to adjust pH conditions. The iron/cadmium retained on the oxide powder was then eluted (1.5 g mn-1) with 6% HCl/6% HNO3 for 2 minutes and the ammonia was directed to the waste. Finally, the column was rinsed for 2 mn with 6% HCl/ 2M HNO3 (1.5 g mn-1) before its conditioning for the next sample. The titania was renewed in the column every 20 samples.

2.5 Calibration by isotope dilution ICP-MS

2.5.1 Calculation of the amount of added spike and preparation of blend solutions IDMS method is based on a determination of the change in the isotopic composition of the element of interest from the addition of some isotopically enriched material, spike, to the sample of interest. Details about IDMS and the application of the method to different sample matrices are given elsewhere [29, 30].

For Cd IDMS measurements, the optimum n(110Cd)/n(111Cd) ratio (~ 0.2) in blends was calculated based on data from the spike and preliminary information available for the samples. This optimisation was based on the estimation of the lowest possible theoretical error value including some important potential components such as the ID error magnification factor, the detector counting rate, corrections for dead time and background and weighing of sample and spike masses (but not the correction of the procedural blank).

Weighing of the sample aliquots and addition of the 111Cd enriched reference material were performed exclusively through metrological gravimetry by the metrological department of IRMM. Aliquots of water sample of about 9 g were weighed into five 35 mL Teflon bottles followed by ~0.33 g of the diluted IRMM 622 spike. The humidity and temperature of the environment in the UCCL laboratory was recorded. The exact values for the metrological weighing are listed in the weighing certificate (E.3657). After blending the bottles were capped, the solutions were mixed by shaking and left overnight for isotopic equilibration. The day of the blend preparation, nitric acid (1% HNO3) was poured into five 35 mL Teflon bottles which served as procedural blank solution.

2.5.2 Selection of isotopes to be measured and ICP-MS measurements Detailed information for the measurement conditions are given in Table 2. Isotopes were selected with respect to availability of spike materials, abundance of the isotopes and possible spectral interferences during measurement by ICP-MS. The MoO+ interference, the main problem in cadmium isotope ratio measurements by ICP-MS, affects all Cd isotopes except 106Cd, which is not suitable as a reference isotope for IDMS, because of its low abundance (1.25%). The isotopes 112Cd, 114Cd and 116Cd suffer from interference by tin, which was present at significant level in the sample [39], while 110Cd is interfered by 110Pd. After matrix separation was applied n(110Cd)/n(111Cd) ratio was eventually selected for Cd content calculations. Possible interferences for these isotopes were monitored by including 91Zr, 98Mo and 110Pd in the measurement method. To monitor for potential cross contamination the instrumental background, was measured after each sample. Procedural blank were analysed with external calibration using the 4 standard solutions described before. The correction for mass discrimination was carried out before and after each 2 blends (bracketing approach).


2.6 Method validation and evaluation of the measurement combined uncertainty

According to the ISO-17025 guidelines, validation is “the confirmation by examination and the provision of objective evidence that the particular requirements for a specific intended use are fulfilled” [31].

The ISO-17025 standard recommends the following five possible approaches for method validation.

1. calibration using reference standards or reference materials; 2. comparison of results achieved with other methods; 3. interlaboratory comparisons; 4. systematic assessment of the factors influencing the result; 5. assessment of the uncertainty of the results based on scientific understanding of

the theoretical principles of the method and practical experience.

These approaches were followed in the present study.

All uncertainties indicated in this report are expanded uncertainties U = k · uc where uc is the combined standard uncertainty and k is a coverage factor equal to 2. Combined standard uncertainties were obtained by propagating together individual uncertainty components according to the ISO/GUM guide [32]. In practice, a dedicated software program was used [33], based on the numerical method of differentiation described by Kragten [34].


3.1 Characterisation of the TiO2 phase and determination of Fe in seawater

3.1.1 Fe solid phase extraction from coastal seawater using anatase TiO2 nanoparticles

3.1.1.1 General adsorption behaviour

In aerated aqueous solutions iron is essentially present as iron (III). At circumneutral pH the hexaaqua iron (III) cation becomes hydrolyzed, followed by the formation of polynuclear oxy-hydroxides [35]. According to the inorganic speciation model of Fe(III) in seawater, the species present at pH < 6.2 include essentially [FeCl2]+, [Fe3+], [FeCl]2+, [Fe(OH)]2+ and [Fe(OH)2]+ [35]. Between pH 6.2 and pH 10, this model predicts the predominance of [Fe(OH)2]+, [Fe(OH)3]0 and [Fe(OH)4]- [35].

Infra-red spectra of the TiO2 material dry (sample 1)

Step 1. Four bands were observed, with maxima at 3735, 3718, 3675 and 3642 cm-1 (spectra not shown). In agreement with literature data [26, 27] these bands were assigned to the O−H stretching modes of different kinds of surface Ti–OH groups.

Steps 2 & 3. Two very intense bands at 2139 and 2155 cm-1 dominated in the spectrum, characterizing respectively, according to reference [36], weakly (physically) adsorbed


CO and CO polarized by surface Ti-OH groups. After a short evacuation at 100 K there were essentially three bands remaining, at 2209, 2184 (most intense) and 2134 cm-1 (Fig. 4a, spectrum a). Maxima shifted toward higher frequencies and the last band almost disappeared after further evacuation at 100 K (Fig. 4a, spectra b-d).

Step 4. The increasing of the evacuation temperature up to 298 K leaded to a gradual disappearance of all bands in the spectrum (Fig. 4a, spectra e-h). According to literature data [28, 36] the bands at 2209 and 2184 cm-1 can be assigned to Ti4+-CO surface complexes (α-Ti4+-CO and β-Ti4+-CO, respectively). The band at 2134 cm-1 arises from the 13CO satellite of the band at 2184 cm-1 [36] and will be no more considered below. It is assumed that the α-sites are four-coordinated Ti4+ ions with two coordination vacancies, while the β-sites are considered to be five-coordinated Ti4+ ions. The coverage shift of the β-Ti4+-CO band is well documented in the literature [36] and is due to decrease of the lateral interaction between the adsorbed CO molecules.

Figure 4a: FTIR spectra of CO adsorbed on activated TiO2 (sample 1 or ‘TiO2’), at progressively decreasing coverage after evacuation of pre-adsorbed CO at 100 K (a-b) and at increasing temperatures up to 298 K (c-h).

2250 2200 2150 2100

TiO2

- 213

4

β-Ti4+- CO

α-Ti4+- CO

h

- 220

9

0.1 - 2184

a

Abs

orba

nce,

a.u

.

Wavenumber, cm-1

Fe/TiO2 samples prepared at pH 2 in ultra pure water and seawater (samples 2 and 3)

At pH 2, the species distribution according to the inorganic speciation model of Fe(III) in seawater gives nearly 50% for [FeCl]2+, half of this fraction for [Fe3+] and [Fe(OH)]2+, and the rest (nearly 10%) for [FeCl2]+ [35].

Step 1. For both types of samples all OH bands were about half of that from sample 1. This suggests that positively charged iron-containing species may have reacted with hydroxyl groups. The reaction scheme 1 is proposed particularly for the –OH groups corresponding to the band at 3642 cm-1.

2Ti⎯OH + [Fe(OH)]2+ ⎯→ HO-Fe-[Ti-O]2 + 2H+ (1)

Steps 2 & 3. For samples 2 and 3, intensity of the carbonyl bands were lower than for sample 1 (Fig. 4b). For the band at 2209 cm-1 the drop in intensity was more than 2 times stronger for sample 2 than for sample 3, thus indicating possibly less activity of the α-


Ti4+ sites in seawater than in ultra pure water. The difference in absorbance between these bands also suggest that Ti sites corresponding to 2209 cm-1 have less affinity for Fe species than Ti sites corresponding to 2184 cm-1.

A weak band was also observed at 2171 cm-1, an absorbance that is assigned to Fe2+-CO complexes [36]. Fe3+ ions are believed to be coordinatively saturated and, thus, do not form any carbonyl complexes. Since it is assumed that originally only Fe (III) ions were present in solution, it is concluded that a reduction process preceded the immobilization of iron on this type of site.

Globally for samples 2 and 3 (Table 3), IR spectra results were nearly identical despite obvious differences in sample composition whereas there was a difference between apparent retention rates of Fe (~ 1.6 times higher in seawater than in ultra pure water). There were chlorine ions in both samples (acidification was done with HCl), but of course more in the seawater than in the ultra pure water. These observations may therefore indicate that the retention of Fe on the TiO2 surface under acidic conditions is favoured in the presence of chlorine and the higher the chlorine content the better. In order to explain the apparent adsorption of iron species on Ti4+ sites, and since a cation cannot be located on a cationic site, we propose the mediation of an anion A- (Cl-) in solution with the oxide surface according to the reaction scheme 2 below (with 0<x<2).

Ti ⎯ O + [FeLx](3-x)+ + A- ⎯→ A-Ti - O-[FeLx](2-x)+ (2)

Figures 4b: FTIR spectra of CO adsorbed on activated Fe/TiO2 after Fe adsorption in ultra pure water and in seawater at pH=2 (sample 2 or ‘MQ-2’ and sample 3 or ‘SW-2’, respectively), after evacuation of pre-adsorbed CO at 100 K (a) and at increasing temperatures up to 298 K (b-f).

2250 2200 2150 2100

MQ-2

2171

- 212

7

Fe2+- COβ-Ti4+- CO

α-Ti4+- CO

f

- 220

7

- 218

1

0.1

a

Abs

orba

nce,

a.u

.

Wavenumber, cm-1


Table 3: IR bands peak height intensities (% comparison with sample 1 results) and apparent Fe retention rate on high surface area TiO2 (anatase) under different pH and media conditions (normalised to sample 2 results)

Sample number Sample type

IR bands peak height intensities

(normalised to sample 1 results)

Apparent Fe retention rate

(normalised to

sample 2 results)

Bands assigned to the stretching modes of different kinds of surface Ti-OH

cm-1 @ 573 K under vacuum conditions

Bands assigned to the stretching modes of different kinds of Ti4

+-CO surface complexes

cm-1 @ 100 K under near vacuum conditions

3735 3718 3675 3642 2209 2184

1 Dry TiO2 0.141 (100%) 0.127 (100%) 0.116 (100%) 0.160 (100%) 0.072 (100%) 0.793 (100%) 2 pH 2 - MQ 0.071 (50%) 0.056 (44%) 0.075 (65%) 0.065 (41%) 0.023 (32%) 0.421 (53%) 1.0 3 pH 2 - SW 0.069 (49%) 0.048 (38%) 0.067 (58%) 0.061 (38%) 0.039 (54%) 0.625 (79%) 1.6 4 pH 7 - MQ * * * * 0.006 (8%) 0.052 (7%) 6.9 5 pH 7 - SW * * * * 0.033 (46%) 0.166 (21%) 7.6

*: absorbances measured are not reported as they correspond to more or less intense broad band signals (tailing toward higher frequencies) assigned to carbonates deposited on the titania surface


2250 2200 2150 2100

2174

SW-2

- 218

5

- 213

4

Fe2+- COβ-Ti4+- CO

α-Ti4+- CO

f

- 220

9

0.1

a

Abs

orba

nce,

a.u

.

Wavenumber, cm-1

Fe/TiO2 samples prepared at pH 7 in ultra pure water and seawater (samples 4 and 5)

The Fe(III) species present in seawater at pH 7 are essentially [Fe(OH)2]+ and [Fe(OH)3]0 and in equal proportions, whereas at pH 10 there is only [Fe(OH)4]- [35]. Since we assumed that above pH 7 the TiO2 surface is globally negatively charged, adsorption involving [Fe(OH)2]+ is likely to occur at this pH, but immobilisation (precipitation) of neutral species is also envisaged.

Step 1. Absorbance of Ti-OH sites for both samples 4 and 5 could not be observed and seemed to be masked by broad band signals that were not visible with sample 1 (titania alone). The absence of surface OH bands may reflect the coverage of active sites with precipitated iron hydroxide species. The broad band observed for sample 5 (seawater) was more intense and tailing more largely than for sample 4 (ultra pure water). It appeared that these broad bands would almost disappear following the introduction of hydrogen in the cell. We attributed this to a reduction process and assigned these broad bands to carbonates present on part of the Ti-OH surface sites.

Steps 2 & 3. CO adsorption bands for samples 4 and 5 were much less intense than for sample 1, thus indicating also the important presence of iron containing species adsorbed on the corresponding titanium sites (Fig. 4c). There were however significant differences between the pure water and the seawater samples, and between the bands at 2209 cm-1 and at 2184 cm-1. For instance between pH 2 and pH 7 for the seawater sample there was no significant difference at 2209 cm-1 and the band at 2184 cm-1 dropped in intensity by a factor 3.8, whereas for the ultra pure water sample both bands dropped in intensity (by a factor 3.8 and by a factor 8.1, respectively). Overall, not surprisingly, these results showed also that far more iron was immobilised at pH 7 than at pH 2, particularly for the sites corresponding to the band at 2184 cm-1. Furthermore, data in last column of Table 3 show that the adsorption capacity for Fe species increased faster for ultra pure water (factor 6.9) than for seawater (factor 4.8) although, globally, this high surface area (anatase) titania phase appeared to be slightly more efficient with seawater than with ultra pure water.


The interaction of [Fe(OH)2]+ (as well as other cationic iron species) with the oxide surface under basic conditions may be described as follows (reaction scheme 3).

HO Fe(OH)2 ⎜ ⎜ Ti⎯O + [Fe(OH)2]+ + OH- ⎯→ Ti⎯O (3)

Regarding the deposition of neutral species we suggest the reaction scheme 4, at least for the initial stages.

HO⎯Fe(OH)2 ⎜ Ti⎯O + [Fe(OH)3] 0 ⎯→ Ti⎯ O (4)

Figures 4c: FTIR spectra of CO adsorbed on activated Fe/TiO2 after Fe adsorption in ultra pure water and in seawater at pH=7 (sample 4 or ‘MQ-7’ and sample 5 or ‘SW-7’, respectively), after evacuation of pre-adsorbed CO at 100 K (a) and at increasing temperatures up to 298 K (b-i).

2250 2200 2150 2100

2180 2160

MQ-7

- 220

7

- 218

4 Fe2+- CO

β-Ti4+- CO

α-Ti4+- CO

e

0.1

aAbs

orba

nce,

a.u

.

Wavenumber, cm-1

e

2173

-

3.1.1.2 Optimisation of the Fe separation efficiency conditions

These experiments were carried out with iron fortified (to ~16 µg Fe kg-1) seawater, and the Fe content used as reference value was established by isotope dilution mass spectrometry (IDMS), following the procedure described in [23]. The Fe separation efficiency was calculated as the ratio between the absolute amounts of Fe adsorbed and of Fe originally available in solution.

The pH was increased stepwise from 2 to 10. As expected from the above the Fe separation efficiency increased quickly to ~80% until pH 7, and progressed more slowly to ~95% at pH 10 (Fig. 5). The absence of decay around pH 10 is in contradiction with


what has been reported previously with higher amounts of Fe in a water sample [11]. At pH 10 [Fe(OH)4]- dominates and, thus, is not expected to adsorb on the negatively charged sites of TiO2. Processes involved must then combine precipitation and also, if possible from an energetic point of view, substitution of hydroxyl anions by Fe anions on the oxide surface.

Figure 5: Fe extraction from seawater (batch protocol): evolution of the % Fe recovery (diamonds) and the % residual salinity as a function of pH conditions

0

10

20

30

40

50

60

70

80

90

100

1 3 5 7 9 11pH

Fe re

cove

ry, %

0

0.001

0.002

0.003

0.004

0.005

0.006

Res

idua

l sal

inity

, %

Fe recovery, % Residual salinity, %

Some residual salinity was observed in the separated samples. Although low (always < 0.01%), thus illustrating the high specificity of this phase for Fe, it worsened with pH. Under these experimental conditions the level of Ti brought into solution from partial dissolution of TiO2 was negligible (< 100 ng Ti g-1 eluant), i.e. not high enough to introduce significant non-spectroscopic interference. Finally, considering that between pH 7 and 10 the Fe recovery rate is improved only by ~ 15% while the level of residual salinity is multiplied by almost a factor 3, and considering that the lower the salinity of samples measured by ICPMS the better [22], pH 7 appeared as a good compromise overall and was selected as the optimum value for the rest of this study.

A range of 0.5-4.0 g min-1 sample flow-rates was tested by passing portions of 3 g of sample solution through the column. The highest efficiency was obtained at 1.7 g min-1. Elution from the titania phase was done using diluted HCl (iron forms stable chloride complexes). The Fe recovery rate did not improve with concentrations of HCl higher than 6%, and 5g and 3g of 6% HCl were used during batch and on-column experiments, respectively.


3.1.1.3 Effect of the iron mass fraction and experimental conditions on recovery rates

The recovery rate at pH 7 for the CASS-2 CRM was found to be 68.5 ± 7.3 % and 69.5 ± 7.6 % (2s, n=3) for the batch and on-column protocols, respectively. The difference with ~80% obtained for a seawater approximately 10 times more concentrated (cf. above) seems to indicate a dependence to the concentration of Fe species in solution (the higher the more pronounced the retention on the titania surface) although we do not understand exactly why.

Under static conditions (batch experiments), increasing the time of centrifugation from 10 to 20 min (and 8500 rpm rotation speed) and repeating it twice improved the recovery rate by 9-13%. This variability is probably due to the tendency of TiO2 particles to remain in suspension because of their low size (< 50 nm).

3.1.1.4 Procedural blank and limits of detection

Since contamination is a crucial issue during measurements of the Fe content in seawater samples, the evaluation of meaningful procedural blanks is of primary importance [23]. For the batch and on-column protocols (applied to ultra pure water acidified to pH 1.6) successively we found 127 ± 43 ng Fe kg-1 and 220 ± 46 ng Fe kg-1 (2s, n=6). The sample-to-blank ratio was ~6 and limits of detection (3 standard deviations rule) were ~ 65 and ~ 69 ng Fe kg-1, respectively.

3.1.1.5 Method validation

Four of the five possible approaches recommended by the ISO-17025 standard for method validation were followed.

First, we used a reference material (CASS-2) to develop our methods.

Second, we compared for a North Sea coastal seawater the external calibration batch and on-column results with an IDMS based value (1.21 ± 0.07 µg kg-1) obtained using the validated IDMS-Mg(OH)2-coprecipitation method described in [23]. It is important to underline that recovery rates applied corresponded to a sample (CASS-2 CRM) with similar characteristics (Fe and matrix contents). As illustrated in Fig. 6 the agreement within stated uncertainties (k=2) was excellent.

Third, as described above, the factors influencing the final results were systematically assessed. This included the effect of pH conditions on the ratio ‘Fe recovery rate/level of residual salinity’, and the effect of sample flow-rates and acid concentration in the eluant.

Fourth, the uncertainty of the results was assessed based on the mathematical description of the entire measurement process (Table 4, Fig. 7). Three standards were gravimetrically prepared (Eq. 1). They were measured at the beginning of the sequence, followed by the procedural blanks (typically four replicates) and the samples (typically six). The standard with the lowest Fe content was randomly re-measured during the sequence to monitor the instrumental drift. A two points (1 and 1.5 µg Fe kg-1 standards) bracketing calibration strategy [37] was applied (Eq. 2). It is in theory more advantageous than a three points linear regression approach in term of uncertainty propagation as i) the measurement cycle is fast and the instrumental drift is minimised, and ii) the effect of instrumental non-linearity is also minimised. Calculated mass fractions were corrected for procedural blank (Eqs. 3 and 4) and for recovery rates (Eqs. 5 and 6). Signal intensities were corrected for blank and instrumental background (Eq. 7, for calibration standard


solutions) and for the difference between the loaded and eluted masses of samples (Eq. 8, for procedural blank and seawater samples).

Typically, the relative combined uncertainty (k = 2) for the measurement (on-column protocol) of ~1 ng Fe g-1 of seawater was ~12%. Hopefully this uncertainty estimation was at least equal to (in fact larger than) the experimental standard deviation of the mean of all six replicate measurements. As illustrated in Fig. 5 the main uncertainty component (~82% contribution) originated from the correction for recovery, followed by the correction for procedural blank (~13%). The repeatability on the measurement of 56Fe intensity for the standards and samples contributed for ~3%, each, while the uncertainty on the reference value of the Fe stock solution had a negligible effect (<1%).

Table 4: Equations for the calculation of Fe content in seawater after separation by solid-phase extraction with high surface TiO2 (anatase)

Preparation of calibration standards

( ) ( ) ( )iidi

i

ddM

MMiD mm

mmm

mmm

mCC

_)1(

)1(

22_1

1

11__ ...

+××

+×

+×=

−

− [1]

Sample bracketing calibration and other corrections

( ) ( )( )( )( )ii

SiiDiSiDmeas II

IICIICC

−

−×+−×=

+

++

1

1_)1_( [2]

∑×=q

BlkBlk Cq

C1

1 [3]

Blkmeascorr CCC −= [4]

[ ]∑×=n

CC

nR

certCRM

ncorrCRM

1

1

_

_ [5]

[ ]∑×=

ppcorr

rec RC

pC

1

1 [6]

Corrections on signal intensities

BlkStdmeasStdcorrStd III ___ −= [7] loadS

eluSmeasSBefColS m

mII

_

___ ×= [8]


Parameter Index C, C mass fraction, average mass

fraction (mg Fe kg-1) D working calibration standard

m mass (kg) M stock solution I signal intensity i dilution step after dilution 1 (i

≥ 2) R average recovery rate S sample CRM Certified Reference Material Std calibration standard meas measured cert certified n, p, q number of repeats Blk blank rec correction for recovery corr correction for procedural blank

(inc. instrumental background) BefCol before column separation load loaded on the column elu eluted from the column

Figure 7: Uncertainty budget for the measurement of the Fe content in a North Sea coastal seawater sample

IV. 2.5%III. 3.2%II. 12.6%

I. 81.5%

V. 0.3%

I. Uncertainty on the estimated recovery rateII. Repeatability on the 56Fe intensity measured in the procedural blanksIII. Repeatability on the 56Fe intensity measured in the external calibration standardsIV. Repeatability on the 56Fe intensity measured in the samplesV. Uncertainty on the value of the Fe content in the commercial Fe stock solution


3.2 Determination of Cd in natural waters

We participated to the Euramet 924 project co-organised by the BAM (Germany) and the LNE (France) as a series of inter-laboratory comparison exercises to support the implementation of the European WFD. There were two legs, Euramet-924-1 and Euramet-924-2, centred on the determination of Hg, Cd, Pb and Ni contents in batches of ultra pure water and of filtered river water, respectively. Our Cd values (Table 5) established by regular IDMS for both Euramet-924-1 (direct determination) and Euramet-924-2 (after separation using an Bio-Rad AG1-X8 anion exchange protocol) served to validate the method developed in this study on the application of TiO2 for the SPE extraction of Cd from natural water samples. Description of the way these Cd values were obtained as IRMM contribution to Euramet-924-1 and Euramet-924-2 can be found in refs. 38 and 39.

Table 5 Certified mass concentration (μg ·L-1) values determined at IRMM by IDMS for the EURAMET 924.1 and 924.2 samples (gravimetrically fortified water samples)

Euramet 924.1 Euramet 924.2

0.2059 (48) 0.946 (17)

3.2.1 Optimisation of the conditions for Cd solid phase extraction using anatase TiO2 nanoparticles

3.2.1.1 Effect of pH conditions during sample loading

The optimum pH conditions for sample loading were investigated with a batch of 10 g ultra-pure water solutions spiked with 1 µg kg-1 Cd, Mo and Zr. Diluted ammonia, respectively HNO3 were added to adjust the pH value from 2 to 10. The influence on the retention rate of Mo and Zr was also investigated because of the regular presence of these elements in natural waters and the possible interferences on the Cd isotopes due to MoO+

and ZrO+ formation during the ICP-MS measurement. Elution was performed with 12 % HNO3. Our results (Figure 8) show that at pH 7-9 the recovery efficiency of the amounts adsorbed and then eluted, calculated as a percentage of the amount introduced, is quantitative (~100%) for Cd and decreases from 60% to 10% for Mo. Cd could not be separated from Zr in the whole pH range studied. Thus, pH 8 was used for the rest of our experiments.


Figure 8. Effect of pH on the extraction efficiency of 1 µg kg-1 Cd, Mo and Zr on high surface TiO2. Elution was performed with 12% and 6% HNO3

pH dependence

0

20

40

60

80

100

120

1 2 3 4 5 6 7 8 9

pH

Ext

ract

ion

effic

ienc

y,%

Cd 12% HNO3

Zr 12% HNO3

Mo 12% HNO3

Mo 6% HNO3

3.2.1.2 Effect of the eluent acidity conditions Similar experiments were carried out with elution at 6% HNO3 (using solutions with 5 µg kg-1 Cd and Mo). At pH 7 and above the Cd recovery efficiency was also maximum, but only at 90%, whereas it was 20% and dropped to 10% for Mo (Figure 8). These results showed that 6% HNO3 in the eluent was more appropriate since, comparatively to 12% HNO3 conditions (cf. above), the recovery efficiency was much more reduced for Mo than for Cd. Additionally, more concentrated acid would create undesirable matrix effects for the ICP-MS measurements and would also increase the analytical blank. Beside, there is a possible disadvantage when using metal oxides as solid phase extractants under very acidic elution conditions which is a partial dissolution of the oxide. The Ti concentration in the separated samples did not exceed 1 μg g–1, when elution was done with 6% HNO3 and that Ti amount did not cause problems in the analysis step. Therefore, 6% HNO3 was used for the elution of cadmium for the rest of our experiments.

3.2.1.3 Effects of sample flow rates Changing the sample flow rate from 1 to 6 g min–1 while keeping the eluent flow-rate constant (1 g min–1) only resulted in small variations of the recovery of Cd. Thus a flow rate of 2 g min–1 was chosen for all further investigations. Preliminary tests showed that the sample volume was not an important factor when the mass of analyte adsorbed at the column was kept constant.

3.2.2 External calibration experiments on pure water samples

3.2.2.1 Effect of cadmium concentration and sample matrix on recovery rates

The on-column approach using external calibration was tested on ‘Sample A’ and on the CRM BCR-609 described in the experimental section. The Cd recovery rate at pH 8 was respectively 76.7 ± 7.9 % (2 RSD) and 93.2 ± 9.2 % (2 RSD). This difference, despite


very similar Cd mass fractions in both cases (e.g. a bit less than 0.2 ug kg-1), may be explained from the major differences in matrix characteristics between the two types of samples. This apparent influence of the sample matrix conditions is somewhat similar to what we had observed for the extraction of Fe. These results also emphasise, for external calibration purposes, the necessity to estimate recovery efficiencies from reference materials matching unknown samples not only for Cd content but also for matrix characteristics.

3.2.2.2 Procedural blank and limits of detection

From the application of the on-column method to ultra-pure water samples we found 1.76 ± 0.11 ng Cd kg-1 for the procedural blanks, thus leading to a limit of detection (3 standard deviation rule) of ~ 0.33 ng Cd kg-1. Typically for ~1 ng Cd g-1 natural samples and under these experimental conditions, the uncertainty introduced by the correction for procedural blanks was negligible with <1 % of the combined uncertainty of the final mass fraction result.

3.2.2.3 Application to the Euramet-924-1 sample and method validation

The TiO2 SPE method was applied to the Euramet-924-1 test material using external calibration as already described in the case of Fe experiments (cf. Table 4). Four standards – 56, 110, 332 and 557 ng Cd kg-1 – were prepared (cf. ‘Experimental’ section) for this purpose. They were measured at the beginning of the sequence, followed by the pre-concentrated procedural blanks and samples. The standard with lowest Cd content was randomly re-measured during the sequence to monitor for instrumental drift. The measurement sequence included 4 procedural blanks and the Euramet 924.1 sample. The procedural blank value (cf. ‘Experimental’ section) was obtained with 1 point calibration, whereas the Euramet 924.1 sample (concentrated ~ 3 times) was bracketed with the 332 and 557 ng Cd kg-1 standards. The sample-to-blank ratio in this study was ~86. The application of the TiO2 column method led to Cd content values of 191 ± 21 ng kg-1.

Four of the five possible approaches recommended by the ISO-17025 standard for method validation were followed.

First, as described above, the factors influencing the final results were systematically assessed. This included the effect of pH conditions, procedural blank, the effect of sample flow-rates and acid concentration in the eluent.

Second, the extraction efficiency was assessed from a Cd mono-elemental solution which Cd content had been established by IDMS separately. Matrix characteristics and Cd content in this material, ‘Sample A’, was similar to that of the Euramet-924-1 sample.

Third, we compared for the Euramet 924.1 sample the external calibration on-column results with an IDMS based value (Table 5) obtained by using the validated method described in [38]. As illustrated in Fig. 9 there was an excellent agreement within stated uncertainties (k=2) between values obtained using both approaches. There was no agreement when the external calibration result was corrected for the Cd recovery efficiency established with the BCR-609 material (ground water).

Fourth, the uncertainty of the results was assessed based on the mathematical description of the entire measurement process (Table 4, Fig. 10). The uncertainty on the correction for the Cd recovery efficiency dominated the uncertainty of the final result (~94%),


followed by the repeatability on the ICP-MS measurements of the standard solutions (~5%).

Figure 9 Cadmium content in Euramet 924.1 sample, determined by direct IDMS (♦) and by TiO2 column method with external calibration for which extraction efficiency was established with mono-elemental Cd solution in 2% HNO3 (●) or ground water CRM BCR-609 (■). Vertical bars indicate combined uncertainty, k=2.

0.125

0.135

0.145

0.155

0.165

0.175

0.185

0.195

0.205

0.215

IRMM ref IRMM TiO2 2 IRMM TiO2 1

Cd,

μg

kg-1

Figure 10 Uncertainty budget for the measurement of the Cd amount content in the EURAMET 924.1 sample

94.0%

0.7%5.0%

0.0%0.3%

Certified value of the Cd content in the commercial Cd stock solutionRepeatability on the 110Cd intensity measurement in the external calibration standardsRepeatability on the 110Cd intensity measurement in the samplesUncertainty on the estimated recovery rate

3.2.3 IDMS calibration experiments on natural water samples

Results described above show that an external calibration approach applied to the TiO2 SPE method necessitates a correction for Cd recovery efficiency. This recovery rate can only be obtained following a preliminary "scan" of the sample to identify a reference material matching the unknown sample in Cd content and matrix characteristics. Application of an IDMS calibration based approach eliminates this difficulty. Matrix


separation and Cd preconcentration was achieved by means of the on-line TiO2 column method according to the description given in the experimental section. 9 g sample blends were loaded at the optimised flow rate while being mixed on-line with 0.05% ammonia at 0.5 g mn-1 to adjust pH conditions. The cadmium retained on the oxide powder was then eluted (1.5 g mn-1) with 6% HNO3 for 2 minutes and the ammonia was directed to the waste. Finally, the column was rinsed for 5 min with 12% HNO3 (1.5 g mn-1) before its conditioning for the next sample.

3.2.3.1 Procedural Blanks and limits of detection

The procedural blank samples followed exactly the same analytical procedure as water samples (the addition of spike was substituted by addition of the same amount of 2% HNO3). The relative and absolute procedural blank contents of Cd were 16.7 ± 2.3 ng kg-

1 and 158 ± 21 pg (n=5), respectively. The limit of detection at preconcentration level 3, calculated as 3 times the reproducibility of the procedural blank was 2.3 ng kg-1. The contribution to the combined uncertainty arising from the correction for procedural blanks formed 1% of the Uc in the case.

3.2.3.2 Correction of interferences Preliminary tests confirmed the presence of a saline matrix, which could generate ICP-MS analytical artefacts. The application of the TiO2 SPE was particularly interesting in view of the high amounts of Mo and Zr present in this sample at the same levels than Cd. After matrix separation, our results showed that the Cd/Mo and the Cd/Zr mass fraction ratios had dropped to ~ 120 and to ~ 200, respectively. From separate experiments, using the same experimental parameters as for the measurements of the blend samples, on a standard solutions containing 4 ng Mo g-1 and 1 ng Zr g-1 it was found that MoO+ /Mo+ and ZrO+ /Zr+ ratios were ~ 0.4% and 2.3% respectively. Using this data the Cd intensities detected in the IDMS blends (typically 110Cd was ~44700cps and 111Cd was ~266000cps) were corrected for oxide formation effect on and these corrections changed the blend ratio by 0.14% to 0.94%. Such corrections were not applied on for the Cd measurements for mass discrimination correction because mono-elemental solution was used. After matrix separation the intensity on 105Pd (natural abundance 22.3%) for the samples was found to be ~ 21000cps. Correction for 110Pd interference on 110Cd would affect the final Cd content result by ~30%. Therefore, to confirm the necessity of 110Pd correction, additional investigation on the isotopic composition of Pd in the blend samples was carried out and the results were compared to the IUPAC data [24]. It appeared that the Pd isotopic pattern was significantly distinct from the natural, e.g. the relative difference between the IUPAC and measured in the blends values of the n(105Pd)/n(102Pd) and n(105Pd)/n(104Pd) were 90% and 83%. There was no information for possible enrichment in certain Pd isotopes in the samples and Pd contamination during sample preparation was also excluded. For that reason interferences on the Pd isotopes were investigated (e.g. 88Sr 16O1H, 65Cu40Ar on 105Pd; 86Sr 16O on 102Pd; 88Sr 16O, 64Zn40Ar on 104Pd) and the significant amounts of Cu, Zn and Sr with natural isotopic composition were detected (63Cu was ~ 760000cps, 68Zn was ~400000cps, 86Sr was ~2e7cps). These results indicated that the origin of the 105Pd intensities, detected in the blends measurements, was very likely from interferences on Pd and that 110Pd correction on the 110Cd intensities was not necessary. Nevertheless, a factor associated to 110Pd correction equal to unity with uncertainty of 3% was introduced in the model equation in order to back up the final result for possible overestimation (in case of non-correcting of 110Pd). The way that uncertainty was calculated – from the experiments described above we can say with 95%


confidence limit, that the 30%-difference between the corrected or uncorrected for 110Pd content value of Cd is not realistic. The remaining 5% of that difference, i.e. 30% x 0.95 = 1.5%, was multiplied by factor of 2 and used as uncertainty of that factor.

3.2.3.3 Application to the Euramet-924-2 sample and method validation

The TiO2 SPE method was applied to the Euramet-924-2 test material using IDMS as described in Table 6.

Three of the five possible approaches recommended by the ISO-17025 standard for method validation were followed.

First, as described before, the factors influencing the final results were systematically assessed.

Second, the uncertainty of the results was assessed based on the mathematical description of the entire measurement process (Table 5, Fig. 11). The isotope ratios of the blends were measured as described in the experimental section. From these isotope ratios, the weighing and the spike data, the mass concentrations of the different blends were calculated using equations 1-5 (Table 5).


Table 6: Equations for calculation of the Cd amount content by IDMS

1. ∑∑

⋅−⋅

⋅−⋅⋅=

iy

ix

xblendxx

blendxxyyyx R

R

RrKrKR

mCN_

_

_

_

2. 21 ⎟⎟

⎠

⎞

⎜⎜

⎝

⎛+=

+j_x

x

j_x

xj r

RrRK

3. Pdx

blankxx F

mNN

C ⋅−

=)(

4. MCxx ⋅=γ

5. 610⋅⋅= samplexx ηγρ

6.

5

5

1∑== i

j

final

ρρ

7. τ⋅−

=I

IIcor 1

8. blankBbckgBB

blankAbckgAAcorblankAB III

IIIr

__

____ −−

−−=


Parameter Index

C Amount content (mol g-1) blend blend

N Amount (mol) y spike material

m Mass (g) x Sample

Ri Known isotope ratio i, j generic indices

R Measured isotope ratio A, B generic indices

K Mass discrimination correction term bckg correction for instrumental background that is specific to the ratio and sample type

F Factor corresponding to correction for 110Pd interference on 110Cd Pd Palladium

M Molar mass (g·mol-1) blank Procedural blank contribution

γ Mass fraction (g·g-1) cor Corrected quantity

τ Dead time value (s)

I Ion signal intensity (counts s-1)

ρ Mass concentration (μg L-1)

η density of sample solution (kg m-3)

Figure 11 shows the major contributions to the total uncertainty of the Cd mass concentration in the fortified natural water sample for the EURAMET 924.2 study. The uncertainty associated with possible 110Pd spectral interferences on 110Cd during sample blends measurements represented the dominant part with ~88%, followed by the uncertainty coming from the IUPAC data on the Cd natural isotopic composition [24] with 7.7%. The uncertainties on the procedural blank determination and on the isotope ratio measurements for the blends and mass discrimination correction were with shares of 1.7% and 0.9%, respectively.


Figure 11. Uncertainty budget for the measurement of the Cd amount content in the EURAMET 924.2 sample

87.9%

0.9%7.7%1.8% 1.7%

Uncertainty on the procedural blank correctionUncertainty on the IUPAC data on natural isotopic compositionRepeatability on the measurement of natural and blend n(110Cd)/n(111Cd) ratiosUncertainty on possible 110Pd effect on 110CdOthers - IRMM-622 data, dead time effects

Third, we compared for a Euramet 924.2 sample IDMD –TiO2 on-column results with an IDMS based value [42]. The mass fraction of Cd in the fortified natural water sample for the EURAMET 924.2 study found with IDMD –TiO2 was 0.952 ± 0.045 μg Cd L-1

(k=2). This was in agreement with the IDMS value obtained after application of anion exchange resin separation method, reported as IRMM result in the certification campaign of EURAMET 924.2 study - 0.946 ± 0.017 μg Cd L-1 (k=2) [39]

Figure 12 Cadmium content in Euramet 924.2 sample – fortified natural water – determined by IDMS with TiO2 column (♦) and with anion exchange resin (‘IRMM Ref’) matrix separation. Vertical bars indicate combined uncertainty, k=2.

IRMM TiO2

IRMM Ref0.9

0.92

0.94

0.96

0.98

1

1.02

Cd μg

kg-1


4. CONCLUSIONS

High surface area TiO2 (anatase) can be optimally used at pH 7 for the extraction of iron from seawater at ng g-1 level, and our results also show that it is more efficient with seawater than with ultra pure water. At pH 2 there is also retention but much less (6.9 and 4.8 times lower for the ultra pure water and the seawater, respectively).

TiO2 (anatase) can be optimally used at pH 7-8 for the extraction and preconcentration of cadmium from natural water below the ng g-1 level.

IR experiments with adsorbed Fe show that results corresponding to acidic conditions are nearly identical for pure water and seawater despite obvious differences in sample composition. This is pointing at a possible mechanism of adsorption involving chlorine containing Fe species (acidification was done with HCl and thus chlorine ions were also present in the ultra pure water sample). At pH 7 the retention of Fe species becomes easier (presence of neutral species that may precipitate and no competition of cationic species with H3O+). It seems that some surface Ti-OH sites cannot be mobilized (owing to coverage with carbonates), particularly with seawater samples, but this is not an important limitation (surface hydroxyl groups represent ~5% of the sites potentially available to adsorption [27]). The capacity of adsorption comes essentially from two types of Ti4+ based surface sites, revealed from the more or less intense IR absorbance of two carbonyl bands at 2209 and 2184 cm-1. Our results suggest that α-Ti4+ sites (first type) have less affinity for Fe species than β-Ti4+ sites (second type), and that α-Ti4+ sites are less active in seawater than in ultra pure water.

The on-(mini)column separation protocol we developed requires minute amounts (0.05g / sample, recyclable) of high surface TiO2 (anatase) and is applicable to the determination of moderate iron mass fractions (~1.2 µg kg-1) in seawater, i.e. typically coastal seawaters and or estuarine waters with variable salinities. The perspective is to address iron contents from open ocean seawaters that are often ~ 2 orders of magnitude lower. For this purpose it will be necessary to further optimize the method toward the concentration of samples (mass of sample passed >> mass of solution eluted) and lower levels of procedural blanks. Beside, the method we described here is based on external calibration. Furthermore, application of an IDMS based approach will eliminate the necessity to correct results for extraction efficiency, as was shown in the case of Cd experiments.


5. REFERENCES

1. P. Liang, Y. Qin, B. Hu, T. Peng, and Z. Jiang, Anal. Chim. Acta, 2001, 440, 207.

2. Scindia et al., Anal. Chem., 74 (2002) 4204-4210

3. Vassileva and Furuta, Spectrochimica Acta B58 (2003) 1541-1552

4. Pu et al., J. Anal. At. Spectrom., 19 (2004) 984-989

5. E. Vassileva and N. Furuta, Fresenius' J. Anal. Chem., 2001, 370, 52.

6. Camel, V., 2003. Solid phase extraction of trace elements. Spectrochimica Acta Part B: Atomic Spectroscopy, 58(7): 1177-1233.

7. E. Vassileva, K. Hadjiivanov, T. Stoychev and C. Daiev, Analyst, 2000, 125, 693.

8. Brunelle, J.P., 1979. Jacobs, G. Poncelet, Elsevier, Amsterdam. In: B. Delmon, P. Grange, P. Jacobs and G. Poncelet (Editors), The Second International Symposium on the Preparation of Catalysts. Elsevier, Louvain-la-Neuve, pp. 211.

9. X. Pu, Z. Jiang, B. Hu and H. Wang, J. Anal. At. Spectrom., 2004, 19, 984.

10. E. Vassileva, B. Varimezova and K. Hadjiivanov, Anal. Chim. Acta, 1996, 336, 141.

11. E. Vassileva, I. Proinova and K. Hadjiivanov, Analyst, 1996, 121, 607.

12. P. Liang, T. Shi, H. Lu, Z. Jiang, and B. Hu, Spectrochim. Acta Part B, 2003, 58, 1709.

13. P. Liang, B. Hu, Z. Jiang, Y. Qin and T. Peng, J. Anal. At. Spectrom., 2001, 16, 863.

14. J. C. Yu, X. J. Wu and Z. Chen, Anal. Chim. Acta, 2001, 436, 59.

15. Y.C. Sun, Y.C. Chang, and C.K Su,. Anal. Chem., 2006, 78, 2640.

16. Martin and Fitzwater, Nature, 1988, 331, 341

17. Martin, Paleoceanography, 1990, 5, 1

18. Available at http://www.bbm.me.uk/FeFert/experiments.htm

19. Available at http://www.awi-bremerhaven.de/AWI/Presse/PM/pm04-1.hj/040402EIFEX-e.html

20. Bowie et al., Mar. Chem., 2003, 84, 19.

21. Bowie et al., Mar. Chem., 2006, 98, 81


22. I. Petrov and C. R. Quétel, J. Anal. At. Spectrom., 2005, 20,1095.

23. I. Petrov, C. R. Quétel and P. D. P. Taylor, J. Anal. At. Spectrom., 2007, 22, 608.

24. International Union of Pure and Applied Chemistry, Isotopic Composition of The Elements 1997, Pure & Appl. Chem., 70 (1998) 217-235.

25. A. Lamberty, et al., Fresenius’ J. Anal. Chem., 1997, 357, 359.

26. K. Hadjiivanov and D. Klissurski, Chem. Soc. Rev., 1996, 25, 61.

27. K. Hadjiivanov, J. Lamotte and J. C. Lavalley, Langmuir, 1997, 13, 3374.

28. A. Davydov, Molecular Spectroscopy of Oxide Catalyst Surfaces, Wiley, Chichester, 2003.

29. Quétel, C.R., S. Nelms, L. Van Nevel, I. Papadakis, P. D. P. Taylor, J. Anal. Atom. Spectrom., 2001, 16 (9), 1091-1100.

30. E. Vassileva, C. Quétel, Anal. Chim. Acta , Vol. 519 (2004) 79-86.

31. ISO, General requirements for the competence of testing and calibration laboratories, ISO, Geneva, 2005.

32. International Standards Organisation, I. (Editor), Guide to Expression of Uncertainty in Measurement, Geneva, 1995.

33. Metrodata.GmbH, "GUM Workbench, The Software Tool for the Expression of Uncertainty in Measurement" v.2.3.6, D-79639 Grenzach-Wyhlen, Germany, 2003.

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36. K. Hadjiivanov and G. Vayssilov, Adv. Catalysis, 2002, 47, 307.

37. J. N. Miller and J. C. Miller, Statistics and Chemometrics for Analytical Chemistry, Pearson Education Ltd., Harlow, England, 2000.

38. E. Vassileva, C. Quétel, The determination of Cd mass concentration in water – contribution of IRMM to Euramet 924. GE/R/IM/09/07.

39. E. Vassileva, C. Quétel , Certification of Cd amount content in natural water at concentration level required by the Environmental Quality Standards by Isotope Dilution Inductively Coupled Mass Spectrometry, GE/R/IM/19/07.

EUROPEAN COMMISSION JOINT RESEARCH CENTRE Institute for Reference Materials and Measurements Reference Materials Unit

Investigation of possibilities to quantify allergenic proteins, in

particular major peanut allergens in the presence of natural enzyme

inhibitors

Date: 28/08/2008

Authors: Amalia Muñoz and Radim Kral

Revised by: Ingrid Zegers, Heinz Schimmel

Approved by: Hendrik Emons

TABLE OF CONTENTS

1. INTRODUCTION ................................................................................................................................ G-2

2. RESULTS AND DISCUSSION........................................................................................................... G-3

3. CONCLUSIONS................................................................................................................................... G-3

4. REFERENCES ..................................................................................................................................... G-4

Investigation of possibilities to quantify allergenic proteins, in particular major peanut allergens G-2 / 4 in the presence of natural enzyme inhibitors

1. INTRODUCTION

Peanuts (Arachis hypogaea) are widely used in the food industry owing to their nutritive value and to their taste. They are used for the preparation of a variety of and are also relied on as a protein extender in developing countries.

Peanut is the cause of food allergies that are among the most severe due to their persistency and the life-threatening character [1]. Consumer product diversification led to an increase in recipes containing peanuts, resulting in an increased risk for inadvertent ingestion of peanuts by allergic individuals.

The nature of the allergenic compounds in peanuts has been studied extensively in recent years and two proteins, Ara h1 and Ara h2, have been identified as the two major allergenic proteins responsible for more than 90 % of the sensitive reactions [2-4]. Ara h1 belongs to the vicilin family of seed storage proteins and contains 23 linear IgE binding epitopes [5-6]. Analysis of these epitopes indicated that substitution of a single amino acid within either of them can lead to the loss of IgE binding; in addition, hydrophobic residues appeared to be most critical for the IgE binding [7]. Ara h2 is a member of the conglutin family of seed storage proteins, with sequence homology to proteins of the 2S albumin family. Ara h2 contains 10 linear IgE binding epitopes and functions as trypsin inhibitor. Roasting processes, including Maillard reaction, cause an increase of the inhibitory activity of Ara h2 [6, 8-10].

The methods generally employed to estimate the content of these proteins in food products are based on immunoassays. Although these methods have provided a generic screening tool, they are, due to the variation in antibody binding affinities, kinetics and specificity, at best semi-quantitative methods that cannot provide adequate accuracy of the results. Moreover, it is necessary to consider the changes that proteins undergo during food processing and which may affect the peptide structure recognized by the antibody, therefore modifying the immunoresponse [9, 11-12].

The aim of this project was to investigate the possibility of using LC-MS/MS in combination with stable-isotope labelling for the detection and quantification of the major peanut allergen, Ara h1.

At present, mass spectrometry in the field of protein quantification uses predominantly trypsin, a serine protease, to generate specific peptides. To avoid the possible inhibitory activity of Ara h2 on trypsin, it was decided to investigate the use of another proteolytic enzyme, Arg-C. Arg-C is a cysteine-protease which specifically cleaves the protein chain at the arginine sites. The trypsin inhibitory domain of Ara h2 [9] should not affect the activity of Arg-C since its active site has a different structure than the active site of trypsin. The use of Arg-C should result in a lower variability on the percentage of digestion than that observed when using trypsin, therefore making the quantification of Ara h1 more reliable. After enzymatic digestion, one unique and conserved peptide for Ara h1 is selected for quantification. The target peptide is separated and quantified by LC-MS/MS using isotopically labelled synthetic peptides as internal standards. The use of two internal standards, added before and after the digestion, allows for the estimation of the target peptide losses occurring during the digestion step and a correction for losses during further sample treatment steps.

The assessment of the method required the selection and investigation of the peptide to be used for the quantification of Ara h1, the investigation of the conditions for the LC-MS/MS method and the optimisation of the conditions for the enzymatic digestion. In a second step, the inhibitory action of Ara h2 on Arg-C was investigated.



Peptide identification and selection of a unique conserved peptide corresponding to Ara h1 were carried out in-silico and further verified in-vitro by using LC-MS/MS (liquid chromatography coupled to mass spectrometry).

The selected peptide is found in the mature form of the all Ara h1 isoforms but not in other plants of the seed storage proteins family (pea, soybean). This assures the specific quantification of Ara h1 even in the presence of other protein contaminants. Simulated non-trypsic enzymatic digestion of Ara h1 results in 63 fragments including the target peptide. This in-vitro selected peptide was experimentally observed by LC-MS/MS proving the adequacy of the in-silico prediction.

Both peanut proteins, Ara h1 and Ara h2, were characterised by its molecular mass using SDS-PAGE and amino acid analysis. In addition, Ara h1 was characterised by using MALDI-TOF mass spectrometer ABI 4800 (KU Leuven, BE), triple quadrupole mass spectrometer (4000 QTrap (RM Unit, IRMM, BE) and N-terminal sequencing.

The enzymatic conditions were optimized for the source of the enzyme, different digestion times and protein to enzyme ratios.

Further on, the chromatographic conditions for the separation of the target peptide from other products of the enzymatic digestion were optimised. After necessary experimental controls, it was concluded that there is no overlap with any other signal originating either from proteolysed enzyme, chemical degradation of Ara h1 or from other components used in the incubation blend. Finally the peptide was sequenced de novo to further verify its sequence identity.

As the aim of this work is to develop a method for the absolute quantification of Ara h1, it is necessary to assure that all possible sources of losses during the enzymatic hydrolysis or the sample treatment are taken into consideration. This aspect was tackled with by using isotopically labelled analogues of the target peptide as internal standards.

The reproducibility of the quantification including all the procedural steps was also investigated. For each digestion time three samples were independently prepared and analysed. The results indicate reproducibility at a CV of about 7 %.

Finally, the possible inhibition of Arg-C by Ara h2 was first investigated. The results from this experiment were compared to those of the incubation which did not contain Ara h2. It was observed that the amount of target peptide released from Ara h1 decreases in the presence of Ara h2. However, if the amount of enzyme is adjusted to maintain a constant enzyme : protein ratio, there is no significant difference between the sample containing Ara h1 and Ara h2 and those containing only Ara h1.

3. CONCLUSIONS

The work showed that the unique and conserved selected peptide resulting from the enzymatic digestion meets the requirements for the quantification of the Ara h1 in terms of selectivity and MS/MS signal intensity.

Peptide analysis using LC-MS/MS has proven to be a promising method for the absolute quantification of Ara h1. The proper separation of the target peptide is achieved in a single chromatographic step. The use of internal standards has been demonstrated to be crutial to account for losses occurring during the sample digestion.

The source of the enzyme influenced its activity dramatically. While recombinant enzyme worked well, the protein isolated from natural sources showed poor performance.

The selected enzyme performed well in the cleavage of the protein chain and resulted in the successful release of the desired peptide. There was no significant decrease of the digestion rate


of the Ara h1 in the presence of the Ara h2 when the enzyme/substrate ratio was kept constant above a certain threshold. This might correspond to a multisubstrate enzymatic reaction where the enzymatic activity is divided between both proteins according to their affinities. It might be also caused by unspecific binding of Ara h2 or any other protein. Based on these findings, when measuring Ara h1 in a matrix material, the total protein content needs to be taken into account for the preparation of the digestion mixture.

4. REFERENCES

[1] Sampson HA, McCaskill CC (1985) J. Pediatr. 107, 669-675.

[2] Burks AW, Williams LW, Helm RM, Connaughton C, Cockrell G, O'Brien TJ (1991) J. Allergy Clin. Immunol, 88, 172-179.

[3] DeJong EC, Van Zijverden M, Spanhaak S, Koppelman SJ, Pellegrom H, Penninks AH (1998) Clin. Exp. Allergy 28, 743-751.

[4] Burks AW, Williams LW, Connaughton C, Cockrell G, O'Brien TJ, Helm RM (1992) J. Allergy Clin. Immunol. 90, 962-969.

[5] Shin DS, Compadre CM, Maleki SJ, Kopper RA, Sampson H, Huang SK, Burks AW, Bannon GA. (1998) J. Biol. Chem., 13753-13759.

[6] The Pfam protein families database: Finnn RD, Tate J, Mistry J, Coggill PC, Sammut JS, Hotz HR, Ceric G, Forslund K, Eddy SR, Sonnhammer EL, Bateman A (2008) Nucleic Acids Research Database Issue 36:D281-D288.

[7] Bannon GA, Shin D, Maleki S, Kopper R, Burks AW, (1999) Int. Arch. Allergy Immunol., 118, 315-316.

[8] Chatel JM, Bernard H, Orson FM (2003) Int. Arch. Allergy Immunol., 131, 14-18.

[9] Maleki SJ, Viquez OM, Jacks T, Dodo H, Chanpagne ET, Chung SY, Landry SJ, (2003) J. Allergy Clin. Immunol., 112,190-195.

[10] Dodo HW, Viquez OM, Maleki SJ, Konan KN (2004) J. Agric. Food Chem., 52, 1404-1409.

[11] Koppelman SJ, Vlooswijk RAA, Knippels LMJ, Hessing M, Knol EF, van Reijsen FC, Bruijnzeel-Koomen CAFM (2001) Allergy, 56, 132-137.

[12] Pomes A, Helm RM, Bannon GA, Burks AW, Tsay A, Chapman MD (2003) J. Allergy Clin. Immunol. 111, 640-645.

EUROPEAN COMMISSION JOINT RESEARCH CENTRE Institute for Reference Materials and Measurements Food safety and quality

High temperature liquid chromatographic analysis of PAHs

Date: 19/06/2008

Authors: Hollosi Laszlo, Lerda Donata, Szilagyi Szilard, Wenzl Thomas

Revised by: Jensen Anne-Mette

Approved by: Ulberth Franz

TABLE OF CONTENTS

1. SUMMARY ......................................................................................................................H-2

2. INTRODUCTION .............................................................................................................H-3 2.1 General overview on PAHs............................................................................................ H-3

2.2 Legal aspects .................................................................................................................. H-3

2.3 Analytical methods for PAHs determination ................................................................. H-5

2.4 High temperature HPLC................................................................................................. H-6

3. OBJECTIVES ..................................................................................................................H-7

4. MATERIALS AND METHODS .........................................................................................H-7

4.1 Equipment, consumables, reagents ................................................................................ H-7

4.1.1 Equipment.............................................................................................................. H-7

4.1.2 Consumables (columns) ........................................................................................ H-8

4.1.3 Reagents ................................................................................................................ H-9

4.2 Experimental design..................................................................................................... H-11

4.3 Experiments.................................................................................................................. H-13

4.3.1 Thermo Hypercarb ®........................................................................................... H-13

4.3.2 Zirchrom®-PS ..................................................................................................... H-13

4.3.3 Zirchrom®-CARB............................................................................................... H-15

4.3.4 X-Bridge®........................................................................................................... H-17

5. RESULTS AND DISCUSSION..........................................................................................H-20 5.1 Thermo Hypercarb® .................................................................................................... H-20

5.2 Zirchrom-PS®.............................................................................................................. H-20

5.3 Zirchrom-CARB® ....................................................................................................... H-31

5.4 X-Bridge®.................................................................................................................... H-31

6. CONCLUSIONS .............................................................................................................H-35

7. ACKNOWLEDGEMENTS...............................................................................................H-36

8. REFERENCES ...............................................................................................................H-36

High temperature liquid chromatographic analysis of PAHs H-2 / 38

1. SUMMARY

The use of temperature as a possible optimisation parameter for improving chromatographic

separations in liquid chromatography is not a recent issue, but the temperatures applied so far

have been well below 100°C whilst for this project temperatures up to 190°C were tested.

The specific objective of this exploratory project was toevaluate whether columns, currently

available on the market, would be suitable for use at high temperature (above 100°C), in order to

reach an improved separation of polycyclic aromatic hydrocarbons (PAHs) relevant to EU food

legislation. A PAH standard mixture in solvent was used as a test solution to study the effect of

the variation of chromatographic conditions.

Various parameter combinations were tested for their effect on chromatographic separation of

relevant PAHs: column temperature, mobile phase composition, flow rate and mobile phase

gradient. The values obtained for the retention factor (k') and resolution (Rs) were considered as

criteria for acceptability of the results. In this study, the liquid chromatographic approach at high

temperatures was applied to standard mixtures of PAHs only, not to food matrices (point 9.7 of

the proposal), since no satisfactory separation of the 16 PAHs listed in the legislation was

obtained with any of the experimental conditions tested.


2. INTRODUCTION

2.1 General overview on PAHs

Polycyclic aromatic hydrocarbons (PAHs) constitute a large class of organic substances: 660

different molecules are contained in the NIST special publication 922 [1]. The chemical structure

of PAHs consists of two or more fused aromatic rings made of carbon and hydrogen. When

PAHs are considered in a mixture together with heterocyclic aromatic compounds and/or PAH

derivatives they are named PAC (polycyclic aromatic compounds). PAHs may be formed during

the incomplete combustion of organic compounds and can be found in the environment.

PAHs in food may derive from environmental contamination or can be formed during food

processing and domestic preparation, such as smoking, direct fire-drying and heating, roasting,

baking, frying, or grilling [2].

2.2 Legal aspects

Taking account of the legal framework of Council Regulation EEC 315/93 [3], the European

Commission started a Scientific Co-operation task (SCOOP - task 3.2.12) to collect and collate

recent data on the occurrence of benzo[a]pyrene (BaP) and other PAH in foodstuffs; a final

report was issued in 2004 [4]. The 16 "EPA PAHs" (where EPA stands for the US Environmental

Protection Agency) have been considered for the evaluation of PAHs in food due to their

recognised, probable or possible genotoxicity and carcinogenicity, according to International

Agency for Research on Cancer (IARC) studies [5].

The SCOOP report contained data on PAH levels in foodstuffs measured between 1992 an 2003

in 8861 samples from 14 European countries. The five categories of foodstuffs showing elevated

levels of contamination were: sausages and ham, vegetable oils, fish / fish products, meat.

In 2002 the European Commission’s Scientific Committee on Food (SCF) identified 15

individual PAHs as being of major concern for human health [6]. Due to their genotoxicity and

carcinogenicity, they represent a priority group in the risk assessment for long-term adverse

health effects following dietary intake of PAHs. Most important, the 15 SCF PAHs are not

identical to the EPA list, which contains only 8 of these compounds. Additionally, the monitoring

of benzo[c]fluorene (BcL) was recommended by the Joint FAO/WHO Expert Committee on

Food Additives (JECFA) in 2006 [7]. In order to distinguish this set of PAHs from the set of

PAHs that have been addressed by the US EPA, known as the 16 EPA PAHs, the terminology

15+1 EU priority PAHs was chosen. They are listed in Table 1 (the abbreviations given in Table

1 are used throughout this report). This new set challenges the efficiency of currently applied

chromatographic separation technology, because PAHs with similar structure and, therefore,

similar chemical and physical properties (e.g. the four different dibenzopyrenes, the three

benzofluoranthenes) have been included in the EU priority list. The sitation will be even more

complicated in real food samples, where more isomeric compounds will be present.


Table 1: Names, abbreviations and chemical structures of the 15+1 EU priority PAHs

15-Methyl

chrysene (5MC)

9

Cyclopenta

[cd]pyrene

(CPP)

2Benzo[a]

anthracene (BaA)

10Dibenzo

[a,e]pyrene (DeP)

3Benzo[a]

pyrene (BaP)

11

Dibenzo[a,h]

anthracene

(DhA)

4

Benzo[b]

fluoranthene

(BbF)

12Dibenzo

[a,h]pyrene (DhP)

5Benzo[ghi]

perylene (BgP)

13Dibenzo

[a,i]pyrene (DiP)

6Benzo[j]

fluoranthene (BjF)

14Dibenzo

[a,l]pyrene (DlP)

7

Benzo[k]

fluoranthene

(BkF) 15

Indeno[1,2,3-

cd]pyrene

(IcP)

8Chrysene

(CHR)

+ 1Benzo[c]fluorene

(BcL)

As a consequence of these findings, the European Commission (EC) issued Commission

Recommendation 2005/108/EC [2], asking for further investigation into the levels of the 15 SCF

PAHs in certain foods, and Commission Regulation (EC) No 1881/2006 setting maximum levels

of benzo[a]pyrene in some foodstuffs [8]. The Regulation states that benzo[a]pyrene can be used

as a marker for the occurrence and effect of carcinogenic PAH in food, but that further analyses

of the relative proportions of these PAH in food is necessary to support a future review on the

suitability of benzo[a]pyrene as a marker.

Following the request for a scientific opinion on PAHs in food, the European Food Safety

Authority (EFSA) had asked the EU Member States to submit monitoring data on PAHs levels to

its database on PAHs in food [9]. The results indicated that the use of BaP as marker is

questionable [10] and, in 2007, EFSA was requested by the Directorate General Health and

Consumer Protection (DG SANCO) to provide a scientific opinion on the suitability of BaP as a

marker and on its possible substitution with a set of PAHs [11].

As a consequence it may become mandatory to detect and quantify several PAHs in food

matrices according to the provisions listed in Commission Regulation (EC) No 333/2007 [12],

which at present applies to benzo[a]pyrene alone.


2.3 Analytical methods for PAHs determination

Gas chromatography - mass spectrometry (GC-MS) and high performance liquid chromatography

with fluorescence detection (HPLC-FLD) are the most popular analytical techniques for the

determination of PAHs.

GC-MS is able to identify compounds, provided that a sufficient number of ions is produced, but

for PAHs limits of detection are significantly higher than those provided by HPLC-FLD due to

the high stability of PAHs.

Moreover, with GC-MS it has to be taken into account that a complete chromatographic

separation of PAHs having identical or similar mass spectral characteristics, as in the case of BbF

and BkF, is fundamental for attaining accurate quantification.

Additionally, instrumental limitations of the injection part of the GC could also arise, especially

when high molecular mass PAHs are concerned; they may irreversible be adsorbed or

decomposed in the injector (parts of the injector, like glass wool or frits) or in the column, with

consequent decrease of response and eventual disappearance of the compound.

Thus, HPLC has advantages when analysing high molecular mass PAHs. With the exception of

CPP, all PAHs on the EU priority list are fluorescent. HPLC-FLD offers high sensitivity but

presents two disadvantages: the lack of unambiguous confirmation of the identity of the analytes

and the lack of fluorescence for CPP.

Until now, columns of 25 cm lengths with particles of 5 µm diameter were sufficient to analyse

the set of 16 EPA priority PAHs in environmental and food matrices, but the.new EU legislation

necessitates the use of more efficient separation systems to separate the EU 15+1 PAHs.

Separation efficiency is related to the number of theoretical plates (N) calculated for a

chromatographic system, and in particular for a given chromatographic column. It defines how

many times the equilibrium is established for the solute distributed between the mobile and

stationary phase before the substance is eluted from the column. The higher the value of N, the

higher is the chromatographic efficiency of the system.

For a given column, N is proportional to its length and reciprocal to the height of a theoretical

plate:

N = H

L Equation 1

Where:

N = number of theoretical plates

L = column length

H = height of the theoretical plate

For a given H, the longer the column, the better the separation.

But N depends also on the dimension of the stationary phase particles through the following

equation:

N ∝∝∝∝ 2

1

pd Equation 2

Where:

dp = particle size (diameter)

N = number of theoretical plates

From the Equation 2 it can be inferred that, for a given stationary phase and given column length

L, the separation is more efficient with lower the particle size.


If higher than standard resolution is needed (like in the case of 15 +1 EU priority list PAHs),

either a longer column or a stationary phase with smaller particles should be used. However, the

common HPLC systems have already reached the upper limit of back pressure. Consequently, an

increase of column length or the use of smaller particles is hardly possible, at least not at ambient

temperature.

With increasing temperature, the viscosity of the eluents decreases and, along with it, the back

pressure decreases. Since PAHs are not temperature sensitive they do not decompose at the high

temperatures used. Therefore, the use of high temperature HPLC for PAHs separation seems to

be a possible solution to the lack of resolution.

2.4 High temperature HPLC

The main effects of temperature on liquid chromatography can be summarised as follows [13]:

1. Decrease of back pressure (as a consequence of the decrease of eluent viscosity)

2. Increase of analyte diffusivity and improved separation efficiency

3. Individual changes in retention times and, consequently, in selectivity, due to the

relationship between the retention factor of a molecule and the temperature according to

the Equation 3

4. Possible changes in structure and/or polarity of the stationary phase

5. Increased speed of analysis [14]

With reference to point 3, the van t´Hoff equation (Equation 3) describes the effect of

temperature on the retention factor:

βlnln ´ +∆

+∆

−=R

S

RT

Hk Equation 3

Where: k´= retention factor

∆H = enthalpy change associated with the transfer of the solute between

phases

∆S = entropy change associated with the transfer of the solute between phases

R = molar gas constant

T = absolute temperature

β = phase ratio of the column

In reversed-phase chromatography the value of ∆H is typically negative and for PAHs < -15

KJ/mol. For the same change in temperature, the k' of solutes with large ∆H will be more affected

than k' of solutes with small ∆H. Thus, different selectivity may be obtained at different

temperatures. This effect, especially when exploited through a temperature gradient as a possible

surrogate of a solvent gradient, is less important for small molecules than for macromolecules,

where also the entropy factor is important [15]. This consideration has been taken into account

for the planning of experiments (temperature, gradient and initial eluent composition had been

treated as separated influencing factors) and interpretation of results.

The use of temperature, as a parameter to influence HPLC separations, is limited by the

availability of HPLC column oven equipment (no fully controlled and integrated oven is, at

present, commercially available for temperatures higher than 90°C) and of HPLC columns

resistant to high temperatures, especially above 100 ºC.

Most commercially available columns are stable up to 50 °C [16,17].

The traditional silica based reversed-phase HPLC columns, normally used for PAHs separations,

were not resistant to high temperatures, especially in the presence of water and buffer salts due to

hydrolysis and consequent loss of bonded phase [14]. A multidentate bonding of the octadecyl

stationary phase to the silica support recently has been developed, obtaining a C18 phase stable

up to 200°C under certain RP conditions [18]. Also hybrid columns, like X-bridge BEH from

Waters, are reported to be stable up to 150°C under restricted RP conditions [19].


Columns based on other materials such as graphite and zirconia-based polymer columns [20] are,

according to literature, also stable at temperatures of 150 °C and are commercially available.

Concerning the set-up to be used for high temperature HPLC, it has to be taken into consideration

that:

- Baseline distortions might arise for UV and FLD detection from a gradient of

temperature in case THF is used. This is due to the change of the refractive index (RI) of

the mobile phase, which in turn affects the amount of light reaching the detector. The

magnitude of the baseline drift is related to the RI value of the mobile phases.

- at high temperatures, close to or above the boiling point of the constituents of the mobile

phase, a backpressure regulator is needed to avoid boiling within the column.

- if the incoming solvent is cooler than the column wall, the fluid at the column centre will

be cooler than the fluid at the walls, resulting in peak broadening [21, 22]. Thus,

preheating the solvent is strongly recommended. With standard size columns, it is

suggested that the temperature difference between the mobile phase entering the column

and the column should be less than 7 °C in order to avoid band broadening [23].

- The effluent temperature

3. OBJECTIVES

This exploratory research project aimed to evaluate the potential of HPLC separation at high

temperature as a possible alternative to current techniques to improve resolution, selectivity,

sensitivity and speed of analysis of a complex mixture of PAHs. The analytes were the 15+1 EU

priority PAHs, in a solvent matrix. Commission Regulation (EC) No 333/2007 specifies

minimum method performance criteria for analytical methods applied for the official control of

BaP in food. For this project, the key parameter considered is the specificity which means, the

selectivity and resolution.

4. MATERIALS AND METHODS

4.1 Equipment, consumables, reagents

4.1.1 Equipment

An Agilent 1200 Series LC system equipped with a quaternary pump, a HiP-ALS SL auto

sampler, and an Agilent 1200 Series fluorescence detector (Agilent Technologies) was used. A

backpressure regulator was placed after the detector to avoid bubble formation in the mobile

phase.

The column temperature was controlled by a Polaratherm Series 9000 Total Temperature

Controller (Figure 1) equipped with a mobile phase preheater, postcolumn thermostat (Selerity

Technologies, Salt Lake City, UT, USA). The system applies active, controlled preheating of the

incoming mobile phase. The preheater temperature was usually set 5 to 8 °C higher than the oven

temperature, which was necessary to heat up the mobile phase to the temperature of the analytical

column, thus avoiding peak broadening. The effluent temperature was controlled using a cooling

bath set to 22 - 30 °C. The maximum temperature that can be reached by the column oven is 200

ºC. The temperature in the column compartment is controlled by forced air circulation.

Temperature programming and start/stop commands were set through the software controlling

the HPLC system.


Figure 1: Structure and picture of the oven used for the experiments.

4.1.2 Consumables (columns)

The columns tested for the experiments on the set of 15+1 EU priority PAHs have been:

1. Thermo Hypercarb® 5 µm (100 x 2,1 mm + 50 x 2,1 mm) [100% graphitic carbon,

max temperature specified by the supplier as 200ºC] supplied by Thermo Electron.

According to the supplier, the particles are spherical and fully porous. The surface is

composed of flat layers of hexagonally arranged carbon atoms as in a very large

polynuclear aromatic molecule. The Hypercarb phase is very stable at high temperatures

and was therefore considered in this project although it is normally used for very polar

compounds. Its surface is stereo-selective and can separate geometrical isomers and other

closely related compounds. Its compatibility with all solvent systems allows the

application of very strong eluents for elution of PAHs that are likely strongly adsorbed

via the dispersive interactions on the polynuclear aromatic surface. As the strength of

interaction of the analyte interactions with the Hypercarb phase is largely dependent on

the area of the analyte molecule that is in contact with the graphite surface, selective

retention power is expected for the different PAHs. The elutropic solvent series

associated with silica bonded phases does not apply to Hypercarb. The elution strength of

organic solvents is solute-dependent: in general, the strongest eluents are tetrahydrofuran

(THF) or dichloromethane (DCM). In non-aqueous analysis of hydrophobic solutes (i.e.,

compounds with high hydrocarbon content) which are retained mainly by dispersive

interactions, chloroform and toluene are the strongest solvents, followed by DCM and

THF.


2. Zirchrom PS® 3 µm (150 X 4.6 mm) [ZrO2 coated with a polymer similar to

octadecylsilylane (ODS), max temperature 160ºC] supplied by ZirChrom – Supelco.

ZirChrom®-PS (polystyrene) is an alternative to ODS selectivity for reversed-phase

analytical HPLC. It is a reversed-phase like material but with different selectivity for

aromatic compounds and it is generally less retentive. It can be used in 100% aqueous

mobile phase and is stable from pH 1 to 13. Thermal stability allows it to be used up to

150 ºC (with possible changes in selectivity). Studies on this kind of stationary phase

[21] indicate that as for C18 the retention factor increases with molecular

hydrophobicity, decreases with % of organic modifier in the mobile phase and with

increase of temperature (3-fold/50 °C); the solvent strength sequence is tetrahydrofuran >

acetonitrile > methanol. Furthermore the efficiency is comparable to the efficiency of

C18 columns with the same particle size (N > 90,000 plates/meter). The differences

observed in comparison with traditional phases concern polar and ionized compounds.

3. Zirchrom Carb® 3 µm (150 X 4.6 mm) [ZrO2 coated with carbon, min temperature 60-

75 ºC, max temperature 200 ºC] supplied by ZirChrom – Supelco. As it is a carbon based

column, high temperatures have to be used (60 ºC is the minimum) associated with high

flow rates (3 ml/min) and at least 10-15% of organic solvent (ACN, MeOH, iso-

propanol) to elute apolar compounds from the stationary phase. In particular with highly

conjugated aromatic or planar flat molecules like PAHs are, the supplier advised to add

1-5% of a strong solvent like tetrahydrofuran, octanol, octanitrile or toluene.

4. X-bridge® C18 2.5 µm (50 X 2.1 mm) [prepared by the copolymerization of

tetraethoxysilane as the precursor of the inorganic component, with

octadecylethoxysilane as the organic component, max temperature declared is 80 °C]

supplied by Waters (BEH Technology). The particles resulting from this polymerization

provide the advantageous properties of high-purity silica-based particles, such as their

mechanical strength, combined with the advantageous properties of polymeric particles,

such as their pH (and temperature) stability. The specific attributes of such packing

materials are a function of the selection of the organic component, which is in this case

octadecylethoxysilane. The incorporation of a large amount of organic groups reduces

the amount of silanol groups on the surface of the packing and, as a consequence, the

achievable surface coverage in a bonding reaction. The quantity of silanol groups

available is much reduced and, hence, they have almost no influence on the column

selectivity. The decrease of silanol groups adds also to an increased stability of the

stationary phase at extreme pH and at high temperatures; loss of bonded phase from the

silica support is related to hydrolysis of free silanols which is enhanced by these two

factors.

For the columns 2, 3 and 4 the particle diameter (dp) is smaller than for the specific PAHs

columns used for the method developed in our laboratory for the analysis of food samples; the

effect of this parameter on column separation efficiency is reported in equation 2.

4.1.3 Reagents

a. Water (W) of HPLC grade was obtained with a Water Purification system Milli Q

gradient 10.

b. Tetrahydrofuran (THF) of HPLC grade was supplied by Merck KGaA

c. Acetonitrile (ACN) of HPLC grade was supplied by Merck KGaA

d. Ethyl Acetate (ETA) of HPLC grade was supplied by Merck KGaA

e. Methanol (MeOH) of HPLC grade was supplied by Merck KGaA

f. PAH standard mixtures containing the 16 PAHs listed in Table 1, each of them at a

concentration of about 80 ng/ml, were prepared by diluting a 10 mg/L standard stock

solution (Dr. Ehrenstorfer GmbH, Augsburg, Germany). The standard mixture was


prepared for every set of experiments using a solvent composition equal to the initial

eluent composition of the chromatographic method applied

g. Blank solutions prepared using a solvent composition equal to the initial eluent

composition of the chromatographic method applied

h. Column test solutions as recommended by the supplier


4.2 Experimental design

Experiments have been planned to take into account the following influencing factors:

a. Initial eluent composition (strength), expressed as % of organic solvent in the eluent.

b. Gradient slope, (organic solvent change in composition over time) expressed as % /

minute

c. Temperature (isothermal), expressed in °C

d. Eluent Flow rate, expressed in ml/min

The response variables (retention factor and resolution for the 15+1 PAHs present in the standard

mixture) were determined for different values of the influencing factors a - d.

The values tested for each factor are reported in the tables at the beginning of each section

dedicated to the respective column settings evaluated.

PAHs were detected by fluorescence detection at following wavelengths:

Excitation: 270 nm

Emission A: 380 nm (for detection of: BcL, CHR and 5MC)

Emission B: 420 nm (for detection of: BaA, BkF, BaP, DhA, DlP, BgP and DeP)

Emission C: 450 nm (for detection of: BbF, DiP and DhP)

Emission D: 508 nm (for detection of: BjF and IcP)

For all the columns, a single factor experimental design was chosen.


The determined response variables were:

1. Retention Factor: k' =

0

0

t

ttR − ; Equation 4

where: tR = retention time of the peak; t0 = dead time (retention time of an unretained solute)

t0 had been obtained from the unretained compound of the test solution supplied with the

column.

2. Resolution: RS = )(

)(2

2,01,0

12

ww

tt RR

−

− Equation 5

where: w0,1 and w0,2 are the widths of the peaks 1 and 2 (among which the resolution is

calculated) at the base, and tR1 and tR2 are the retention times of the earlier eluting peak (tR1)

and later eluting peak (tR2)

3. Number of peaks detected: n

Qualitative evaluation of the effects was made through the graphical representation of the data, as

visualised by the figures included in each of the sub-chapters in chapter 5. The graphs always

represent k' or RS against one of the influencing factors (initial eluent composition, gradient slope,

flow rate, temperature) keeping the other factors constant. The number of peaks detected (n) is

not graphically visualised but simply written, having been in most cases constant for each column

under all conditions.

For response variables acceptance criteria were set in accordance with basic rules in

chromatography:

1. 1< k' < 15 (for k' values >> 15, chromatography is not efficient)

2. RS > 1.5 (corresponding to baseline separation)

3. n = 15 (corresponding to the number of FLD detectable PAHs in the standard

solution)


The sequence of experiments was the following:

- Performance check of the column at ambient conditions following the test protocol

specified by the supplier (mixture of compounds, and chromatographic conditions) and

the number of theoretical plates (N) compared against the value given by the supplier.

N = 16*

2

0

w

tR

Equation 6 where: N is the number of theoretical plates, tR is the retention time of the

particular peak and w0 is the peak width at the base of the particular peak

- Test of the thermal stability of the column: The thermal stability of the column was

checked by repeating the column test as described in the previous point after a set of

chromatographic runs at increased column temperature (up to the maximum temperature

specified for the particular column). N was calculated from the test chromatograms and

compared to the value before starting experiments at elevated temperature.

- As well as having verified the thermal stability of the column, the influence of the

different chromatographic parameters on the response variables was tested by injecting

PAH standard mixtures.

4.3 Experiments

Before starting with every set of experiments, columns were tested according to the attached

technical sheet; the test was repeated after every series of high temperature elutions to test the

stability of the stationary phase with high temperature and different mobile phases.

4.3.1 Thermo Hypercarb ®

A series of experiments hasbeen executed with very high eluent strength and high temperatures.

None of the PAHs eluted and the column was not further tested.

Table 2 summarises the chromatographic conditions applied in the experiments carried out with

the Thermo Hypercarb® column.

Table 2: Summary of experimental conditions (Thermo Hypercarb®)

Sequence

Initial Eluent

Composition

[%ACN/water]

Solvent

Gradient

[%/min]

Temperature

[°C]

Flow Rate

[ml/min]

85 0 70 0.35

85 0 100 0.35

85 0 180 0.35

Same initial conditions

at different

temperatures 85 0 200 0.35

4.3.2 Zirchrom®-PS

As the supplier declared that the column behaves similarly to a C18 column, the first experiments

with this column type were carried out using the chromatographic conditions applied in an

optimised method for PAHs in food, which was developed at the CRL PAHs (Table 3).

Afterwards, the following sets of experiments were performed:

1. Different initial eluent compositions kept for 25 minutes at constant low temperature

and gradient up to 100% ACN: initial composition factor checked.


2. Different initial eluent compositions kept for 25 minutes at constant low temperature

and different gradients up to 100% ACN: gradient slope factor effect checked for

different initial compositions.

3. Different temperatures in the range of 30 °C to 180 °C were tried at constant eluent

strength (25 and 45 minutes of isocratic conditions).

4. Three columns in series (to increase N) were tested at high temperatures, which were

necessary to avoid back pressure problems.

Table 3 summarises the chromatographic conditions applied in the experiments carried out on

Zirchrom PS® column.

Table 3: Summary of experimental conditions (Zirchrom-PS®)

Sequence

Initial Eluent

Composition

[%ACN/water]

Solvent

Gradient

[%/min]

Temperature

[°C]

Flow Rate

[ml/min]

40 0 30 1.0

60 0 30 1.0

80* 1.0* 30* 1.0*

40 0 30 2.0

60 0 30 2.0

Different initial eluent

strength at low

temperature. Initial

conditions kept for 25 min

70 0 30 2.0

20 3.0 30 1.0

30 3.0 30 1.0

40 3.0 30 1.0

50 3.0 30 1.0


strength at low


conditions kept for

25 min. 60 3.0 30 1.0

20 0.5 30 1.0

30 0.5 30 1.0

45 0.5 30 1.0

50 0.5 30 1.0

20 1.0 30 1.0

30 1.0 30 1.0

40 1.0 30 1.0

45 1.0 30 1.0

50 1.0 30 1.0

30 2.0 30 1.0


strength and different

gradients at low


conditions kept for 2 min.

40 2.0 30 1.0

* Parameters of an analysis method optimised by the CRL PAH for 4.6 mm C18-PAH

columns


Table 3 continued

Sequence

Initial Eluent

Composition

[%ACN/water]

Solvent

Gradient

[%/min]

Temperature

[°C]

Flow Rate

[ml/min]

30 0 50 1.0

30 0 70 1.0

30 0 90 1.0

30 0 100 1.0

30 0 110 1.0

30 0 120 1.0

30 0 130 1.0

30 0 140 1.0

30 0 150 1.0

Constant initial eluent

strength and constant

gradient at different

temperatures

Initial conditions kept for

25 in.

Max temp. specified to

150 °C

30 0 180 1.0

30 2.0 50 1.0

30 2.0 70 1.0

30 2.0 90 1.0

30 2.0 100 1.0

30 2.0 110 1.0

30 2.0 120 1.0

30 2.0 130 1.0

30 2.0 140 1.0

Constant initial eluent

strength and constant

gradient at different

temperatures

Initial conditions kept for

45 in.

Max temp. specified to

150 °C

30 2.0 150 1.0

20 0.8 100 1.0 Three columns in series

20 0.8 180 1.0

4.3.3 Zirchrom®-CARB

Taking into consideration the poor results obtained with the Hypercarb® column and the very

high affinity of PAHs for carbon structures, a stronger solvent like THF was used. All the

necessary precautions for instrument safety and personnel health protection were taken in order

to eventually allow the use of THF at high percentage (peek tubing had been replaced with

stainless steel tubing, THF used was always freshly sonicated, all the bottle refillings have been

carried out under fume-hood).

The experimental sequence was the following:

1. Constant initial eluent composition (50% ACN) kept for 5 minutes with constant

gradient to 70% THF/ACN at different column temperatures: temperature factor

checked.

2. Constant initial eluent composition (100% ACN) kept for 30 minutes at different

temperatures and constant gradient to 70% THF/ACN: temperature factor checked at a

higher solvent strength.

3. Different temperatures and different isocratic conditions, with THF as organic

component of the eluent, were tried.

Table 4 summarises the chromatographic conditions applied in the experiments carried out with

the Zirchrom CARB® column.


Table 4: Summary of experimental conditions for Zirchrom-CARB® columns

Sequence

Initial Eluent

Composition

[%org/water]

Solvent

Gradient

[%/min]

Temperature

[°C]

Flow Rate

[ml/min]

50 3.0 40 1.0

50 3.0 80 1.0

50 3.0 120 1.0

Constant initial conditions

at different temperatures

Org = ACN 50 3.0 160 1.0

100 5.0 40 1.2

100 5.0 80 1.2

100 5.0 120 1.2



Org = ACN 100 5.0 160 1.2

40 0 50 1.2

40 0 70 1.2

40 0 90 1.2

40 0 100 1.2

40 0 110 1.2

40 0 120 1.2

40 0 130 1.2

40 0 140 1.2



Org = THF

40 0 150 1.2

50 0 70 1.2

50 0 100 1.2

50 0 130 1.2

50 0 170 1.2



Org = THF

50 0 190 1.2

60 0 70 1.2

60 0 140 1.2



Org = THF 60 0 190 1.2

70 0 70 1.2

70 0 140 1.2



Org = THF 70 0 190 1.2

(Org: organic modifier in mobile phase)


Table 4 continued

Sequence

Initial Eluent

Composition

[%org/water]

Solvent

Gradient

[%/min]

Temperature

[°C]

Flow Rate

[ml/min]

80 0 70 1.2

80 0 70 1.2

80 0 140 1.2



Org = THF 80 0 190 1.2

90 0 70 1.2

90 0 140 1.2



Org = THF 90 0 190 1.2

99 0 70 1.2

99 0 140 1.2



Org = THF 99 0 190 1.2

(Org: organic modifier in mobile phase)

4.3.4 X-Bridge®

The X-Bridge® material was tested in the following groups of experiments:

1. Different isocratic eluent compositions were applied in range of 10 % to 80 % ACN in

water at constant low column temperature for checking and optimising retention and

resolution values.

2. Different solvent gradients in the range of 0.5 % to 3 %/min were applied at constant

column temperature for checking and optimising retention, selectivity and resolution

values. The endpoint of the gradient elution was determined by the k´-value. The

gradient was stopped when k´=20 was reached.

3. Different column temperatures in the range between 30 °C and 150 °C were tried at

constant eluent strength.

4. Different flow rates at different column temperatures, eluent strengths and solvent

gradients were applied for evaluating selectivity and resolution values.

Table 5 details the chromatographic conditions applied in the experiments with the X-Bridge®

column.


Table 5: Summary of experimental conditions (X-Bridge®)

Sequence

Initial Eluent

Composition

[%ACN/water]

Solvent

Gradient

[%/min]

Temperature

[°C]

Flow Rate

[ml/min]

10 0 30 0.6

20 0 30 0.6

40 0 30 0.6

50 0 30 0.6

10 0 50 0.6

20 0 50 0.6

40 0 50 0.6

50 0 50 0.6

10 0 70 0.6

20 0 70 0.6

40 0 70 0.6

different isocratic eluent

compositions, at different

column temperatures, and

at constant flow rate

50 0 70 0.6

10 0 50 0.4

20 0 50 0.4

40 0 50 0.4

different isocratic eluent

compositions, at constant

column temperature, and

at constant low flow rate 50 0 50 0.4

40 1 50 0.6

40 2 50 0.6

40 3 50 0.6

40 1 70 0.6

40 2 70 0.6

40 3 70 0.6

40 0.5 70 1

40 1 70 1

different flow rates,

different column

temperatures, different

solvent gradient with

constant, weak initial

eluent strength

40 2.5 30 0.5

60 0 30 0.5

70 0 30 0.5

80 0 30 0.5

60 0 70 0.5

70 0 70 0.5

80 0 70 0.5

60 0 100 0.5

70 0 100 0.5

80 0 100 0.5

60 0 150 0.5

70 0 150 0.5

isocratic elution with

strong eluent strengths at

constant flow rate and

different column

temperatures

80 0 150 0.5


Table 5 continued

Sequence

Initial Eluent

Composition

[%ACN/water]

Solvent

Gradient

[%/min]

Temperature

[°C]

Flow Rate

[ml/min]

10 1 50 0.7

10 2 50 0.7

10 1 55 0.7

10 2 55 0.7

20 1 45 0.7

20 2 45 0.7

20 1 50 0.7

gradient elution at

different column

temperatures, constant

flow rate starting from

weak initial eluent

strengths

20 2 50 0.7

30 2 40 0.4

40 2 40 0.4

isocratic elution at

constant column

temperature, low flow rate

and different solvent

strengths 50 2 40 0.4



5.1 Thermo Hypercarb®

Although expected, PAHs did not elute from this column even at the highest possible temperature

and high eluent strengths. This kind of column showed too strong retention of PAHs to be

interesting for this particular class of analytes. Consequently no efficiency/selectivity study could

be carried out.

5.2 Zirchrom-PS®

For simplicity, the PAH peaks are identified in the following graphs and tables, presenting results

gained with the Zirchrom-PS® column, with numbers. Table 6 contains the respective key. It

shall be pointed out that complete separation of all target compounds was not possible on the

Zirchrom-PS® column, independent of the chromatographic conditions applied.

Table 6: Peak identification.

Peak number

PAH

1 BcL

2 BaA + CHR

3 5MC

4 BjF +BbF + BkF

5 BaP + DhA

6 DlP

7 IcP

8 BgP

9 DeP

10 DiP + DhP

From the first set of experiments conducted at room temperature it can be concluded that elution

of PAHs is possible on this kind of column, even without ETA, which is needed to elute the 6

rings PAHs from C18 columns. Figure 2 and Figure 3 show chromatograms obtained with 20 %

respectively 70 % of ACN in the eluent. At low percentages of the organic modifier k´-values

exceed the maximum acceptable level of 15 (Figure 2), whereas BcL was already eluted with a

k´-value below one when the mobile phase contained 70 % ACN. Hence the optimum solvent

composition range for the liquid chromatographic separation of the target analytes lies between

these two values, which will be further detailed below.

Under isocratic conditions, the elution of the whole set of PAHs is acceptable with regard to k'-

values, when the mobile phase contains at least 35% but less than 70% of ACN (see Figure 4 and

Figure 5). Hence the possible range of solvent composition for the optimisation of the

chromatographic method is with ambient column temperature narrow.


Figure 2: Chromatogram obtained under isocratic conditions at room temperature with

20% ACN in the eluent.

The green box indicates the acceptable range for k-values (between 1 and 15).

1

2

3

4

5

6

7

8

9 10


Figure 3: Chromatogram obtained under isocratic conditions at room temperature with

70% ACN in the eluent.

The green box indicates the acceptable range for k'-values (between 1 and 15).

Figure 4 presents the dependence of the retention factor (k´) from the eluent composition in

isocratic operation mode. The change in steepness of the curves, occurring around 35% - 60% of

ACN, indicates eluent compositions that allow elution and separation of the PAHs. k´-Values

became low at higher percentages of ACN in the eluent and were very close to each other. The

analytes were poorly retained on the stationary phase, which entails poor peak resolution. This

was similar to the weak, although for most peaks sufficient, peak resolution at low organic

modifier concentration, which can be concluded from the closeness of the curves.

Hence outside of the eluent composition range of 35 % to 60 % of ACN the exchange of the

PAHs between the two phases is either too much in favour of the stationary phase or of the

mobile phase. It shall also be note that, with all the eluent compositions applied, the elution order

did not change, which is indicated in Figure 4 by parallel curves.

1

2

3

4

5

6

7

8

9 10


Figure 4: Retention factor plotted against eluent composition expressed as %ACN (isocratic

conditions).


The influence of the eluent composition on peak resolution (RS) was evaluated and results are

plotted in Figure 5.

0,0

5,0

10,0

15,0

20,0

25,0

30,0

35,0

40,0

10 20 30 40 50 60 70 80 % ACN

k´

Peak 1 Peak 2 Peak 3 Peak 4 Peak 5 Peak 6 Peak 7 Peak 8 Peak 9 Peak 10


Figure 5: Peak resolution between the 10 peak pairs plotted against solvent composition

(isocratic conditions).

0

1,5

3

4,5

6

7,5

9

10,5

12

13,5

15

16,5

10 20 30 40 50 60 70 80

Eluent composition (% ACN in water)

RS

Peak 1-2

Peak 2-3

Peak 3-4

Peak 4-5

Peak 5-6

Peak 6-7

Peak 7-8

Peak 8-9

Peak 9-10

The green box indicates the acceptable range for k'-values (between 1 and 15). The red dotted

line represents the minimum limit for RS values (1.5).

The resolution values were satisfactorily for the gained peaks with all tested eluent compositions,

as they were always above 1.5. However, it shall be repeated that chromatographic resolution

was in general limited by a lack of shape selectivity of the stationary phase, which did not allow

separating all 15 analytes from each other. Maximum possible resolution was achieved in the

range between 40% ACN and about 60 % ACN. This is also the range that gives acceptable

retention factors. The strongest increase of resolution was found for the peaks 1 and 2,

corresponding to BcL and BaA and CHR.

This behaviour can be reasoned with the specific retention mechanism of this stationary phase.

Table 7 list values of Rs obtained under isocratic elution with either 30 % or 40 % of ACN in the

eluent. As can be seen the increase in resolution is for most peak pairs significant.


Table 7: Resolution values with different isocratic conditions.

ACN

(%)

Peaks

1-2

Peaks

2-3

Peaks

3-4

Peaks

4-5

Peaks

5-6

Peaks

6-7

Peaks

7-8

Peaks

8-9

Peaks

9-10

30 8,7 5,7 3,8 3,4 3,4 2,9 2,6 4,3 1,4

40 15,4 7,2 4,9 3,5 5,0 2,8 2,7 5,1 1,4

Figure 6: Retention factor plotted against gradient expressed as % variation of

ACN/minute (initial 30% ACN).

0

5

10

15

20

25

30

35

40

45

0,3 0,5 0,7 0,9 1,1 1,3 1,5 1,7 1,9 2,1

dGEluent

[%ACN/min]

k'

Peak 1

Peak 2

Peak 3

Peak 4

Peak 5

Peak 6

Peak 7

Peak 8

Peak 9

Peak 10


From Figure 6 it becomes evident that k´ reaches for most PAH peaks acceptable values only

with high gradient slopes of ≥2 % ACN/min.


Figure 7: Retention factor plotted against gradient expressed as % variation of

ACN/minute (initial 40% ACN).

0,0

5,0

10,0

15,0

20,0

25,0

0,9 1,1 1,3 1,5 1,7 1,9 2,1

dGEluent [%ACN/min]

k'

Peak1

Peak2

Peak3

Peak4

Peak5

Peak6

Peak7

Peak8

Peak9

Peak10


Experiments with 40 % ACN content in the initial eluent were conducted only with gradients of 1

% ACN/min and 2 % ACN/min, since the experiments with initially 30% ACN content revealed

for gradients below 1 %/min k´-values far above the acceptable range. As can be seen from

Figure 7, a gradient of 1.7 % ACN/min was sufficient to reach k'-values within the acceptable

range. All peaks were even at steeper gradients well separated.

Again, it is evident that efficient chromatographic separation is not taking place when the eluent

is not strong enough. Chromatographic efficiency, which is considered acceptable with k´-values

below 15, depends very much on the initial eluent composition. This can be explained by the time

the system needs to get in gradient elution to an eluent composition that is suitable to elute the

analytes from the column. Starting from a weak eluent, this time is simply longer. Hence k´-

values are with a gradient of e.g. 1 % ACN/min higher (Figure 6) than values achieved with the

same gradient starting from a stronger initial eluent (Figure 7). However, this does not imply that

peak resolution is worse. In gradient elution, initial conditions do not significantly influence peak

resolution. This becomes obvious when comparing resolution values for different eluent

compositions under isocratic elution (Table 7) and gradient elution (Table 8). The strongest effect

has in gradient elution mode the steepness of the gradient. Changing from a gradient of 1

%ACN/min to 2 %ACN/min entails a loss of resolution for most peak pairs of about 7 % to 28

%. Only the peak pair DlP and IcP (peak pair 6-7) was not affected.

Table 8 documents the influence of the solvent gradient on resolution.


Table 8: Resolution values with different solvent gradients.

Initial

ACN

(%)

dG

(%/min)

Peaks

1-2

Peaks

2-3

Peaks

3-4

Peaks

4-5

Peaks

5-6

Peaks

6-7

Peaks

7-8

Peaks

8-9

Peaks

9-10

30 1 11.3 8.1 5.7 4.3 7.5 3.0 3.4 7.5 1.8

40 1 11.4 8.1 5.6 4.4 7.3 3.2 3.4 7.8 1.9

30 2 10.3 7.2 4.9 4.0 5.3 3.2 3.1 6.4 1.7

40 2 10.3 7.1 4.9 4.1 5.3 3.3 3.1 6.4 1.7

To evaluate the effect of column temperature on k' and Rs, an eluent strength outside of the ideal

range for k' found under isocratic conditions at room temperature (30% ACN) was applied.

Figure 8 shows the temperature effect on k'-values for the different PAH peaks. It is strong but

less homogeneous for the different PAHs then the initial solvent strength effect (Figure 4). The

contributions of temperature to the model that relates k' to various thermodynamic parameters

(Equation 3) and the logarithmic relation between k' and temperature, could explain this non-

linear behaviour of k'. The results gained confirm the findings of other authors who identified

temperature as a possible surrogate of solvent strength to achieve lower k'-values [14].


Figure 8: Retention factor plotted against column temperature (isocratic conditions of 30%

of ACN for 25 minutes).


The k´-values as well as chromatographic peak resolution are significantly influenced by the

applied column temperature. Figure 8 presents the relationship of k´-values and column

temperature. k´-Values were only plotted when they were close to the acceptable range. In the

range of 50°C to 150°C k´-values are changing from outside the acceptable range to values within

the range of 1 to 15. This is the column temperature range that can be used for this particular set

up to influence chromatography. Above 150 °C k´-values were for most of the peaks below 5.

The closeness of the curves indicates similar retention times that became more similar with

increasing temperature. This however does not imply insufficient peak resolution as

demonstrated in Figure 10.

Figure 9 and Figure 10 present chromatograms that were recorded under gradient elution

conditions with an initial eluent composition of 30 % in water, hold constant for 25 minutes. The

flow rate was in both experiments 1.0 mL/min and the gradient was set to 2 %ACN/min. The

column temperature was maintained at 50 °C for the chromatogram in Figure 9. As can be seen,

elution times are very high. The k´-values of the peaks are similar and outside the acceptable

range, which is indicate by the green box. This is different when a higher column temperature of

150 °C is applied (Figure 10). The analysis time decreased. The PAH peaks elute already with the

initial eluent composition. This demonstrates that a gradient of the column temperature might

have similar effects as a gradient in solvent strength.

0,0

5,0

10,0

15,0

20,0

40 60 80 100 120 140 160 180 Column temperature [°C]

k'

Peak1 Peak2 Peak3 Peak4 Peak5 Peak6 Peak7 Peak8 Peak9 Peak10


Figure 9: Chromatogram obtained in gradient elution at a column temperature of 50°C

with initially 30% ACN in the eluent

The green box indicates the acceptable range for k'-values (between 1 and 15). The peak with a

retention time of 49 minutes is a system peak and stems from the change of solvent composition

at the end of the chromatographic run.

1

2

3

4

5

6

7

8

9

10


Figure 10: Chromatogram obtained in gradient elution at a column temperature of 150°C

with initially 30% ACN in the eluent


However, with none of the parameter sets tested a separation of the 15 FLD detectable PAHs was

possible; only 10 peaks could be resolved. From k' graphics, it became also evident that the

selectivity of this stationary phase does not change very much, neither by increasing solvent

strength nor by changing the column temperature.

The experiments with three columns in series did not show any improvement in resolution. Even

if efficiency increases (with the plate number) the selectivity of this phase for PAHs is not

sufficient to separate all target analytes, independent of the different chromatographic conditions

tested.

Experiments using MeOH instead of ACN have been performed as well, since MeOH is a weaker

eluent than ACN. However, only 8 peaks were detected for the 15 EU priority PAHs with worse

peak shapes (strong tailing) compared to the experiments with ACN as organic modifier.

Consequently, experiments with MeOH as eluent constituent were not continued.

Water becomes at very high temperatures unpolar. However, the elution strength of water was

even at the highest possible temperature too weak to elute the analytes within a reasonable period

of time. k´-Values were in all experiments with 100% of water as eluent, at all temperatures

tested far above 15. This indicates that a minimum amount of organic modifier in the eluent is

required for efficient liquid chromatographic analysis of PAHs on this type of column. Therefore,

experiments with 100 % water were not continued.

Long retention times showed in general adverse effects on the peak shapes. They improved when

k´-values were decreased by applying either higher percentages of organic modifier in the eluent,

and/or higher flow rates, and/or higher column temperatures.

To summarise the findings for Zirchrom-PS® columns:

- the effect of initial solvent strength on the retention factor k´ was in isocratic elution

much stronger than in gradient elution.

1

2

3

4 5

6

8

7 10 9


- the shape selectivity of this stationary phase was independent of the applied conditions

not sufficient to achieve separation of all

- the peak resolution did not improve by using three columns in series as high column

temperatures had to be applied to avoid excessive back pressure. The temperature effect

compensated the effect of increased column length.

- temperature was a powerful tool to speed up elution, but selectivity was only slightly

influenced, which consequently did not have big influences on the separation of the

target compounds.

- only 6 PAHs out of 15 were completely resolved from the others; most important BaP,

the key compound for the control of food, was not separated from DhA in any of the

experiments performed.

5.3 Zirchrom-CARB®

PAHs did not elute from the Zirchrom-CARB® column, although rigorous conditions such as

99% THF as eluent and high column temperatures (190°C) were applied. This column showed,

as the Thermo Hypercarb®, too high retention for PAHs. Hence retention, resolution and

selectivity studies could not be carried out.

5.4 X-Bridge®

Experiments with isocratic eluent conditions at room temperature showed (Figures 11 and 12)

that ACN/H2O mixture provided enough eluent strength to elute target PAHs from the stationary

phase. Unacceptable high retention factors (k'>40) were observed for all target analytes when

low percentages of ACN (0-40%) were applied. For elution of PAHs at room temperature

(1<k'<15) a minimum eluent strength of 68 % ACN in water has to be applied to reach the

acceptable retention factor range (Figure 11). The difference between k´-values gets, as expected,

smaller with increasing amount of organic modifier in the eluent. This results in overlapping of

peak 9 and 10 at the highest eluent strength. Table 9 gives an overview for peak identification.

Table 9: Peak identification table for X-Bridge column experiments

Peak number

PAH

Peak number

PAH

1 BcL 7 DhA +DlP

2 BaA + CHR 8 IcP

3 5MC 9 BgP

4 BjF +BbF 10 DeP

5 BkF 11 DiP

6 BaP 12 DhP


Figure 11: Retention factors at different isocratic eluent strength at 30°C.

0

5

10

15

20

30 40 50 60 70 80 90

Eluent composition [% ACN]

k´

Peak 1

Peak 2

Peak 3

Peak 4

Peak 5

Peak 6

Peak 7

Peak 8

Peak 9

Peak 10

Peak 11

Peak 12


In combination with elevated temperature the percentage of organic modifier in the eluent could

be decreased by 15 % to achieve k´-values within the acceptable range (Figure 12). However,

BgP and DeP as well as DiP and DhP could not be separated from each other at the higher

column temperature, independent from the applied eluent composition.


Figure 12: Retention factors at different isocratic eluent strength at 70°C.

0

5

10

15

20

30 40 50 60 70 80 90

Eluent composition [% ACN]

k´

Peak 1

Peak 2

Peak 3

Peak 4

Peak 5

Peak 6

Peak 7

Peak 8

Peak 9+Peak 10

Peak 11+ Peak 12

The green box indicates the acceptable range for k' values (between 1 and 15).

The temperature effect on analyte retention was investigated under weak initial isocratic

condition (Figure 13). An eluent of 50 % ACN in water and column temperatures in the range of

30 °C to 70 °C were applied. As expected, application of higher temperatures resulted in faster

elution of PAHs but had simultaneously negative effects on peak resolution: 10 peaks were

observed at 70°C, while 11 peaks were separated applying 30°C. However at a medium column

temperature of about 50 °C the shapes of the curves for the peaks 9 to 12 (BgP, DeP, DiP and

DhP) is different compared to those of the other analytes. The increase of the distances between

the curves is equal to a larger difference in retention time, which does not necessarily imply

better resolution. However, peak resolution was increased in this particular case, which confirms

the suitability of temperature as a tool to manipulate chromatographic separation.


Figure 13: Retention factor values at different column temperatures.

0

5

10

15

20

25

30

35

40

20 30 40 50 60 70 80

Column temperature [°C]

k´

Peak 1Peak 2Peak 3Peak 4Peak 5Peak 6Peak 7Peak 8Peak 9Peak 10Peak 11+12


For evaluating the selectivity of the X-Bridge® column in gradient elution at elevated

temperature, experiments were conducted with weak initial eluent strengths (40% ACN/H2O) and

different gradient slopes (1-3 %/min). Weak initial eluent strengths combined with low solvent

gradients at elevated temperature resulted in slightly better peak resolution but, as presented in

Figure 14, retention factors were above the acceptance limit. When applying a gradient of 2

%ACN/min instead of 1 %ACN/min, k´-values became similar, or nearly identical for many

peaks, resulting in co-elution of DeP, DiP and DhP.

Experiments targeting improvement of peak resolution were carried out by varying of flow rates.

Lower flow rates (0.4 ml/min) resulted in higher retention values, but did not increase peak

resolution compared to chromatograms recorded with a flow rate of 0.6 ml/min. Best resolution

values were gained for the whole set of analytes at a column temperature of 70 °C with a flow

rate of 1 ml/min and gradient elution. The initial eluent composition was 40% ACN in water and

the gradient slope was 0.5 %ACN/min. However, retention factors were still high.


Figure 14: Effect of solvent gradient on retention factors at 70 °C. Initial solvent

composition was 40% ACN in water; the flow rate was 0.6ml/min.

0

5

10

15

20

25

30

35

40

45

0,5 1 1,5 2 2,5 3 3,5

Solvent gradient [%/min]

k´

Peak 1Peak 2Peak 3Peak 4Peak 5Peak 6Peak 7Peak 8Peak 9Peak 10Peak 11Peak 12


According to Liu et al. [19] this column material is stable even at high temperatures. Therefore,

the performance of the column was evaluated also at column temperatures of 100 °C and 150 °C

(see Table 5 for details). As described before, the column performance was evaluated with

column test mixtures at ambient temperature before and after heating it up to the respective high

temperature. In contrary to reports in the literature, the X-Bridge® column was not resistant

against high temperatures. A fast and irreversible decrease of column performance was found.

Hence experiments at high column temperatures were not continued.

To summarise the findings for X-Bridge® columns:

- The X-Bridge® column did not show sufficient shape selectivity to separate all 15 target

compounds

- The effect of solvent gradient and initial eluent composition on analyte retention was

much stronger than the effect of column temperature on analyte retention.

- The influence of the slope of the applied gradient on selectivity was negligible

- Temperature is a powerful tool to speed up elution, but a decrease of selectivity has to be

taken into account.

6. CONCLUSIONS

At the time of performing the experiments four different types of temperature stable columns

were available. Two of them showed too strong retention of PAHs and were therefore not further

tested. The other two commercially available columns (Zirchrom PS® and X-Bridge®) were

tested both in isocratic and gradient elution, at ambient and at high column temperatures.

Retention factors and resolution values were determined from the recorded chromatograms.

In general the two tested columns do not show sufficient selectivity to separate all 15 target

PAHs, independent of the applied conditions. The separation was worse than on standard C18-

PAH columns. Hence the goal of increased chromatographic efficiency for the determination of

PAHs in food was not reached.


However it has been shown for this particular case, that the column temperature has an effect,

which is similar to a solvent gradient. Further, it has been demonstrated that an increased column

temperature provides at least the potential for reducing of the amount of organic modifier in the

eluent. Increased column temperatures speeded up analyses. However this has to be balanced

with the required peak resolution.

Despite the specifications, only one column was found resistant to high temperatures. The other

column lost rapidly its performance when exposed to temperatures equal or above 100 °C.

Hence chromatography of PAHs at very high temperatures with 100 % water as eluent could be

evaluated only for one column. The results revealed that a minimum amount of organic modifier

is necessary to elute PAHs from this particular stationary phase.

However, continuation of experiments will be considered when new temperature stable columns

become commercially available.

7. ACKNOWLEDGEMENTS

The authors would like to thank the Scientific Committee for having accepted and supported the

Exploratory Research proposal, the Head of the Unit "Food Safety and Quality", Franz Ulberth,

and the involved personnel of the "Management Support Unit", for the support in procurement

procedures, Anne-Mette Jensen and Rupert Simon for accurate revision of this report and all the

people who contributed to the realisation of this project.

8. REFERENCES

[1] NIST Special Publication 922 "Polycyclic Aromatic Hydrocarbon Structure Index" Lane C.

Sander and Stephen A. Wise http://ois.nist.gov/pah/

[2] Commission Recommendation (2005/108/EC) of 4 February 2005 on the further investigation

into the levels of polycyclic aromatic hydrocarbons in certain foods. Official Journal of the

European Union, 2005 (L 34): p. 43-45

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[3] Council Regulation (EEC) No 315/93 of 8 February 1993 laying down Community

procedures for contaminants in food

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&pos=2&page=1&nbl=2&pgs=10&hwords=&checktexte=checkbox&visu=#texte

[4] European Commission – Directorate-General Health and Consumer Protection, Reports on

tasks for scientific cooperation, Report of experts participating in Task 3.2.12 " Occurrence

data on PAH in food", October 2004, "Collection of occurrence data on polycyclic aromatic

hydrocarbons in food"

http://ec.europa.eu/food/food/chemicalsafety/contaminants/scoop_3-2-

12_final_report_pah_en.pdf

[5] International Agency for Research on Cancer (IARC), Overall Evaluations of Carcinogenicity

to Humans, in IARC Monographs on the Evaluation of Carcinogenic Risks to humans,

I.A.f.R.o. Cancer, Editor. 2006: Lyon accessed on: 16.10.2006,

http://monographs.iarc.fr/ENG/Classification/crthgr01.php

[6] European Commission: Opinion of the Scientific Committee on Food on the risks to human

health of Polycyclic Aromatic Hydrocarbons in food (expressed on 4 December 2002).

http://europa.eu.int/comm/food/fs/sc/scf/out153_en.pdf

[7] Joint FAO/WHO Experts Committee on Food Additives (JEFCA), Evaluation of certain food

contaminants, in WHO technical report series 930, WHO, Editor. 2006, JECFA: Geneva.


[8] Commission Regulation (EC) No 1881/2006 of 19 December 2006 setting maximum levels

for certain contaminants in foodstuffs. Official Journal of the European Union, 2006. L 364:

p. 5-24


[9] European Food Safety Authority (EFSA), Invitation to submit data: 10 October 2005 – 10

October 2006. http://www.efsa.eu.int/science/data_collection/pah/catindex_en.html

[10] European Food Safety Authority (EFSA), Findings of the EFSA Data Collection on

Polycyclic Aromatic Hydrocarbons in Food. 2007

http://www.efsa.europa.eu/EFSA/Scientific_Document/datex_report_pah.pdf

[11] European Food Safety Authority (EFSA), Register of Questions, Request for a scientific

opinion on Polycyclic aromatic Hydrocarbons in food; EFSA-Q-2007-136 for the Working

Panel [WP] CONTAM:

http://registerofquestions.efsa.europa.eu/roqFrontend/questionDetailsRO.jsf

[12] EU, Commission Regulation (EC) No 333/2007 of 28 March 2007 laying down the methods

of sampling and analysis for the official control of the levels of lead, cadmium, mercury,

inorganic tin, 3-MCPD and benzo(a)pyrene in foodstuffs. Official Journal of the European

Union, 2007. L 88: p. 29-38


[13] T. Greibrokk, T. Andersen: High-temperature liquid chromatography, Journal of

Chromatography A, 1000 (2003) 743-755

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solvents, temperature, and electric fields, Journal of Separation Science, 27 (2004) 1402-

1408

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EUROPEAN COMMISSION JOINT RESEARCH CENTRE Institute for Reference Materials and Measurements Food safety and quality

Production and detection of potentially allergenic peptides derived from milk enzymatic hydrolysates by proteomic

and immunochemical approaches.

Date: 19/06/2008

Authors: Tregoat Virginie, van Hengel Arjon

Revised by: Franz Ulberth, Anne-Mette Jensen

Approved by: Franz Ulberth

TABLE OF CONTENTS

SUMMARY................................................................................................................................................ I-4

1. INTRODUCTION ................................................................................................................................. I-5

2. MATERIALS AND METHODS.......................................................................................................... I-6 2.1. PRODUCTION OF MILK HYDROLYSATES ............................................................................................. I-6

2.1.1. Milk protein samples................................................................................................................. I-6 2.1.2. Enzymes.................................................................................................................................... I-6 2.1.3. Hydrolysis................................................................................................................................. I-7

2.2. CHARACTERISATION OF MILK HYDROLYSATES.................................................................................. I-7 2.2.1. Protein quantification by nitrogen content................................................................................ I-7 2.2.2. Degree of Hydrolysis ................................................................................................................ I-8

2.3. DETECTION OF MILK HYDROLYSATES WITH IMMUNODETECTION....................................................... I-8 2.3.1. Immunodetection of milk hydrolysates by dot blot analysis..................................................... I-8 2.3.2. ELISA....................................................................................................................................... I-9

2.4. DETECTION OF MILK HYDROLYSATES BY ELECTROPHORESIS AND WESTERN BLOTTING..................... I-9 2.5. DETECTION OF MILK HYDROLYSATES WITH A PROTEOMIC APPROACH. ............................................ I-10

2.5.1. Capillary electrophoresis-UV (CE-UV) ................................................................................. I-10 2.5.2. Capillary electrophoresis-ESI-MS .......................................................................................... I-10 2.5.3. Nanoelectrospray quadrupole time-of-flight tandem mass spectrometry (nano-ESI Q-TOF MS/MS) ............................................................................................................................................ I-11

3. RESULTS AND DISCUSSION.......................................................................................................... I-12 3.1. PRODUCTION OF MILK HYDROLYSATES ........................................................................................... I-12 3.2. MILK HYDROLYSATES CHARACTERISATION..................................................................................... I-12

3.2.1. Protein content of the hydrolysates......................................................................................... I-12 3.2.2. Degree of hydrolysis............................................................................................................... I-12

3.3. DETECTION OF MILK HYDROLYSATES WITH IMMUNODETECTION..................................................... I-15 3.3.1. Residual antigenicity of milk hydrolysates by dot blot........................................................... I-15 3.3.2. ELISA Performance................................................................................................................ I-16

3.3.2.1. Total hydrolysate ..............................................................................................................................I-16 3.3.2.2. Ultrafiltered hydrolysates..................................................................................................................I-19

3.4. PEPTIDE ANTIGENICITY IDENTIFIED WITH ELECTROPHORESIS AND WESTERN BLOTTING ................. I-21 3.4.1. Milk protein standard.............................................................................................................. I-21 3.4.2. Total hydrolysates................................................................................................................... I-21 3.4.3. Ultrafiltered hydrolysates........................................................................................................ I-24

3.5. PEPTIDE DETECTION AND IDENTIFICATION BY CAPILLARY ELECTROPHORESIS AND MASS SPECTROMETRY...................................................................................................................................... I-24

3.5.1. Capillary electrophoresis-UV ................................................................................................. I-24 3.5.2. Nanolectrospray quadrupole time-of-flight tandem mass spectrometry (nano-ESI Q-TOF MS/MS) ............................................................................................................................................ I-27

4. CONCLUSION .................................................................................................................................... I-30

ACKNOWLEDGEMENTS .................................................................................................................... I-30

REFERENCES ........................................................................................................................................ I-31

ANNEXES................................................................................................................................................ I-32

Production and detection of potentially allergenic peptides derived from I-2 / 42 milk enzymatic hydrolysates by proteomic and immunochemical approaches

LIST OF FIGURES FIGURE 1: PH CONTROLLED HYDROLYSIS SYSTEM........................................................................................ I-7

FIGURE 2: ELISA SYSTEMS FOR THE ANALYSIS OF MILK DERIVED PROTEIN HYDROLYSATES ....................... I-9

FIGURE 3: SCHEMATIC PRINCIPLE OF CE-MS ............................................................................................. I-11

FIGURE 4: TIME COURSE OF A: TRYPSIN AND B: THE COMBINATION OF PROTEASES (A AND O) FROM B. AMYLOLIQUEFACIENS AND S. ORIZAE DIGESTION OF SKIMMED MILK PROTEINS............................ I-13

FIGURE 5: ANTIBODY DETECTION OF CONFORMATIONAL AND LINEAR EPITOPES ON A NATIVE, DENATURED OR DIGESTED ALLERGENIC PROTEIN. ............................................................................................... I-15

FIGURE 6: DOT BLOT ANALYSIS OF β−LG AND α−LA IN WPC HYDROLYSATES AT DIFFERENT HYDROLYSIS TIMES......................................................................................................................................... I-16

FIGURE 7: TIME COURSE DETECTION OF MILK, CN, β-LG PROTEINS PRESENT IN MILK (MT AND MA/O), CN (CT, CA/O) AND WPC (WT, WA/O) ENZYMATICALLY DIGESTED WITH EITHER TRYPSIN OR A MIXTURE OF PROTEASES FROM B. AMYLOLIQUEFACIENS AND S. ORIZAE WITH ELISA KITS. ........ I-18

FIGURE 8: INFLUENCE OF THE ULTRAFILTRATION PROCESS OF WPC TRYPTIC DIGEST ON THE DETECTION OF β-LG WITH ELISA........................................................................................................................ I-20

FIGURE 9: PROGRESSION OF THE ENZYMATIC DIGESTION (WITH PROTEASE FROM B. AMYLOLIQUEFACIENS) OF A STANDARD MIXTURE OF β-LGA AND β-LGB (AT 5, 10, 20, 30, 40, 60, 120, 180, 240 300 AND 360 MINUTES)................................................................................................................................... I-21

FIGURE 10: ELECTROPHORESIS OF MILK PROTEINS HYDROLYSED (MA/O) BY THE PROTEASE MIXTURE FROM B. AMYLOLIQUEFACIENS AND S. ORIZAE (A) AND IMMUNODETECTION OF B: β-LG AND C: α-LA AFTER GEL TRANSFER BY WESTERN BLOT. ................................................................................ I-22

FIGURE 11: PRINCIPLE OF 2DE-DIGE FOR THE SIMULTANEOUS DETECTION OF TOTAL MILK PROTEINS AND MILK-DERIVED PEPTIDES OBTAINED AFTER 30 MINUTES OF HYDROLYSIS................................... I-23

FIGURE 12: 2D-DIGE ELECTROPHORESIS OF MILK PROTEINS BEFORE (RED) AND AFTER 30 MINUTES ENZYMATIC HYDROLYSIS (GREEN)............................................................................................. I-23

FIGURE 13: EFFECT OF ULTRAFILTRATION ON THE DETECTION OF MILK DERIVED PEPTIDES EMERGING BY HYDROLYSIS WITH THE COMBINATION OF PROTEASES (FROM B. AMILOLIQUEFACIENS AND S. ORIZAE) (MA/O). ....................................................................................................................... I-24

FIGURE 14: ELECTROPHEROGRAMS OF 3 DIFFERENT INJECTIONS OF STANDARD MIXTURE OF β-LGA AND β-LGB HYDROLYSATE AT 5 AND 360 MINUTES. ............................................................................ I-25

FIGURE 15: ELECTROPHEROGRAMS OF MILK DIGESTED WITH THE MIXTURE OF PROTEASES FROM B. AMILOLIQUEFACIENS AND S. ORIZAE BEFORE AND AT 5, 60 AND 360 MINUTES OF HYDROLYSIS.. I-26

FIGURE 16: FRAGMENTATION PATTERN OF AN ION CHARACTERISTIC OF αS1 CASEIN PEPTIDE.................... I-27

LIST OF TABLES

TABLE 1: OPTIMAL CONDITIONS FOR DIFFERENT PROTEASES........................................................................ I-6 TABLE 2: PROTEIN CONTENT AND HYDROLYSIS DEGREE OF CN, WPC AND MILK HYDROLYSED BY A VARIETY

OF ENZYMES WITH INCREASING HYDROLYSIS TIMES. .................................................................... I-14 TABLE 3: IMMUNODETECTION OF CN, β-LG, α-LA, LF, IG WITH COMMERCIAL ELISA KITS AND DOT BLOT

TECHNIQUES. ................................................................................................................................ I-16

TABLE 4: EFFECT OF THE ULTRAFILTRATION PROCESS OF CN AND WPC HYDROLYSATES ON THE ANTIGENIC DETECTION DETERMINED WITH ELISA......................................................................................... I-20

TABLE 5: MILK-DERIVED PEPTIDES IDENTIFIED BY NANOLC-ESI Q TOF.................................................... I-27


LIST OF ANNEXES

ANNEX 1: COMPOSITION OF MILK POWDERS. .............................................................................................. I-32 ANNEX 2: CHARACTERISTICS OF THE COMMERCIAL ELISA KITS. .............................................................. I-33 ANNEX 3: CALIBRATION CURVE FROM THE LEUCINE STANDARD................................................................ I-34 ANNEX 4: A: ELECTROPHORESIS OF NA-CN HYDROLYSED WITH PROTEASE FROM B. AMYLOLIQUEFACIENS

(CA), PROTEASE FROM A. ORIZAE (CO), THE COMBINATION OF BOTH PROTEASES (CA/O), TRYPSIN (CT), PANCREATIN (CP) AND BROMELAIN (CB). B: WESTERN BLOTS OF THE GELS SHOWN IN A IN WHICH CN PROTEINS WERE DETECTED BY α-CN ANTIBODIES. ............................................................................ I-35

ANNEX 5: A: ELECTROPHORESIS OF WPC HYDROLYSED WITH PROTEASE FROM B. AMYLOLIQUEFACIENS (WA), PROTEASE FROM A. ORIZAE (WO), THE COMBINATION OF BOTH PROTEASES (WA/O), TRYPSIN (WT), BROMELAIN (WB) AND PANCREATIN (WP). B: WESTERN BLOTS OF THE GELS SHOWN IN A IN WHICH WHEY PROTEINS WERE DETECTED BY β-LG AND α-LA ANTIBODIES. ..................................... I-36

ANNEX 6: A: ELECTROPHORESIS OF MILK HYDROLYSED WITH PROTEASE FROM B. AMYLOLIQUEFACIENS (MA), PROTEASE FROM A. ORIZAE (MO), THE COMBINATION OF BOTH PROTASES (MA/O), TRYPSIN (MT), BROMELAIN (MB) AND PANCREATIN. B: WESTERN BLOTS OF THE GELS SHOWN IN A IN WHICH MILK PROTEINS WERE DETECTED BY β-LG AND α-LA ANTIBODIES. ........................................................... I-38

ANNEX 7: 2D-DIGE ELECTROPHORESIS PROTOCOL ................................................................................... I-40


SUMMARY

Milk hydrolysates are produced to provide a suitable substitute diet for milk allergic children. However, in some cases the consumption of such hypoallergenic formulae still induce adverse reactions suggesting the presence of residual allergic epitopes. Industrial innovations for the manufacture of new food products possessing health benefits focus on the use of milk derived peptides that present many functional properties. There is therefore a substantial risk of introducing in food products milk-derived peptides potentially responsible for allergic reaction in milk allergic patients. Sensitive analytical methods are required for the detection of milk derived peptides that emerge from enzymatic hydrolysis. Several milk hydrolysates have been produced on site and studied with common immunological methods. ELISA, dot blot and Western blot showed severe limitations in the detection of milk-derived peptides especially when the hydrolysates were submitted to ultrafiltration. As a confirmatory method that is more suitable for the detection of peptides in hydrolysates, we investigated the use of capillary electrophoresis and mass spectrometry. This technique allows an unambiguous identification of peptides present in the hydrolysates. ABBREVATIONS: Caseins (CN); Sodium caseinate (Na-CN); Whey protein concentrate (WPC); Beta-lactoglobulin (�-LG); Alpha-lactalbumin (�-LA); Lactoferrin (LF); Immunoglobulin (Ig); Capillary electrophoresis (CE), Mass spectrometry (MS)


1. INTRODUCTION Milk allergy is particularly frequent during childhood below the age of 3 [1]. This type of allergy is defined as temporary since 80% of the allergic paediatric population become tolerant to milk [2]. However, the remaining 20% do not outgrow milk allergy and this type of allergy can even occur in adulthood [3]. During their milk allergy, children or even adults must completely avoid milk or dairy food products consumption. Most of milk allergic children receive specific diets corresponding to milk based formulae that have been processed to reduce milk proteins allergenicity i.e hypoallergenic formulae [4, 5] and in more severe cases amino acid based formulae. The primary purpose of milk hydrolysed formulae was to provide the allergic children with a satisfying nutritional substitute able to reduce the occurrence of allergic reactions. Over recent years, the use of milk hydrolysis has been extended for the production of foods enriched in bioactive peptides that provide health benefits [6] and new functional properties (improved solubility, gelation, emulsifying and foaming properties) [7, 8]. Milk-derived peptides with bioactive properties indeed have a promising future as nutraceuticals and in functional food with health benefits and will more and more be included in the formulation of food products [6]. However, reports on the persistence of adverse reactions in several allergic children to milk hypoallergenic formulae [9, 10] highlights the risk to introduce on the market new products containing "similar" peptides with added value. According to European legislation, specifically Directive 2007/68/EC [11], the use of milk as an ingredient or in derived form has to be declared on the label of any products containing it. To support legislation and to improve the health protection of allergic patients by proper labelling of food products, analytical methods are available to detect milk proteins in food matrices (e.g. ELISA, electrophoresis, LC-MS). However, most of the analytical techniques used for the analysis of milk allergens detect intact proteins and are not designed to detect peptides, despite the fact that the persistent allergy is often triggered by linear epitopes. It remains to be investigated to which extent those techniques such as commercially available ELISA kits can be employed to detect peptides from milk hydrolysates. As one of the aims of the project, it was important to investigate the performance of the existing methods. In the likely event that the available methods are not suitable enough to detect peptides derived from milk hydrolysates, new methods capable to identify traces of milk peptides need to be developed in order to minimise the occurrence of milk allergic reactions. It is indeed important to have methods at hand that are able to detect milk peptides since more and more novel processes are employed by the food industry in order to create new ingredients derived from milk compounds, which add nutritional or functional properties to food products, but on the other hand increase the allergenic potential of such products. Therefore, another intention of this work was to detect milk allergens by the detection of peptides resulting from milk hydrolysis. A wide range of “milk” hydrolysates is available on the market due to the extended choice of starting protein source and food grade enzymes used by the industry. Additionally, the food industry uses several different methods of hydrolysis and therefore the milk-derived peptides differ strongly in terms of molecular size and properties. This is likely to affect their detection and constitutes a high risk for allergic consumers. For this purpose, controlled material needed to be produced and further analysed by different existing analytical techniques. Therefore, a panel of milk hydrolysates was generated with individual enzymes or combinations of enzymes and their characterisation was described. The analysis of the corresponding hydrolysates with different methods like ELISA, dot blot and electrophoresis linked to immunoblotting techniques is also presented to assess the performance of such tests in their capacity to detect the remaining antigenicity of those hydrolysates. The potential of capillary electrophoresis and mass spectrometry as confirmatory methods for the presence of milk derived peptides in the hydrolysates was also investigated.


2. MATERIALS AND METHODS

2.1. Production of milk hydrolysates

2.1.1. Milk protein samples Sodium caseinate (Na-CN) and whey protein concentrate (WPC) employed for the production of hydrolysates were supplied by the food industry while skimmed milk powder was obtained from Sigma Aldrich (St Louis, MO, USA). Both industrial Na-CN and WPC sources were rich in proteins with protein contents of respectively 90 % and 75 % whereas skimmed milk powder contained 36,5 % proteins. The composition of the different milk powders is described in Annex 1. 2.1.2. Enzymes The different enzymes used to perform the protein hydrolysis were purchased from Sigma Aldrich. Those food grade proteases were from different origins. Trypsin (treated to eliminate the chymotrypsin activity) and pancreatin were tested besides proteases from plants such as bromelain. Bacterial and fungal enzymes like the proteases from Bacillus amyloliquefaciens and from Aspergillus orizae, which are more and more applied in different food industry sectors, were also used. Hydrolysis was performed using the optimal conditions for the different enzymes listed in Table 1. Among these enzymes one is an exoprotease, which specifically removes terminal amino acids from proteins and peptides at the C or N terminal, while all others are endoproteases that cleave amide bonds within the protein sequence. Table 1: Optimal conditions for different proteases.

Proteases Type of enzyme Temperature (° C) pH Trypsin Endoprotease 50 8

Protease B. amyloliquefaciens Endoprotease 60 8 Pancreatin Endoprotease Mixture 50-60 7-8 Bromelain Endoprotease 50-60 6-8

Protease A. orizae Exoprotease 50 6-7


2.1.3. Hydrolysis

Milk powders (Na-CN, WPC) and skimmed milk were dissolved in distilled water to obtain 5 % and 10 % (w/v) solutions respectively and an aliquot of the starting solution (t0) was taken at this stage. Since whey proteins with their globular structure are quite resistant to hydrolysis, WPC and skimmed milk were thermally treated (6 min at 90 °C) in a water bath. A 100 ml "milk" solution was then loaded in a thermostated "flask" at 50 °C (as shown in Figure 1) and an aliquot (2 ml) was collected before the equilibration of the solution to the pH value required for optimal hydrolysis (Table 1). Figure 1: pH controlled hydrolysis system pH control was performed with the Titrino pH system (Figure 1). Another aliquot (2ml) was taken at this stage before addition of the enzyme. The hydrolysis started as soon as the enzyme (0.5 %, w/v) was added to the solution. The hydrolysis was carried out at constant pH controlled by addition of 0.1 M NaOH. The degradation of milk proteins was followed by collecting aliquots (8 ml) every 10 minutes in the first hour of hydrolysis when the hydrolysis is the fastest and every hour for the next 5 hours. The enzymatic digestion in each aliquot was stopped by a heat treatment for 3 minutes at 90 °C. The resulting aliquots were subsequently centrifuged for 30 minutes at 3000 x g at room temperature and the supernatant containing peptides were harvested and stored at -20 °C before their analysis. Aliquots obtained from milk protein hydrolysis were coded and further referred to with an abbreviation according to the following manner. The first letter of the aliquot corresponds to the protein source (C, W or M respectively for CN, WPC or Milk) followed by a second letter determining the protease used (A, O, T, B, P, A/O for Amyloliquefaciens, Orizae, Trypsin, Bromelain, Pancreatin and the combination of Amyloliquefaciens and Orizae) and finally a number corresponding to the hydrolysis time (5, 10, 20… 360 for 5 minutes… till 360 minutes of hydrolysis) (Table 2). 2.2. Characterisation of milk hydrolysates

2.2.1. Protein quantification by nitrogen content The protein concentration of the different milk hydrolysates was estimated from the measurement of the total nitrogen content by the Dumas method. In principle, nitrogen freed from the sample by combustion at high temperature (at least 900 �C) in pure oxygen is measured by thermal


conductivity detection and converted to protein equivalent by using an appropriate conversion factor. Aliquots of 250 mg hydrolysed solution were weighted and freeze-dried in metallic cups (crucible). Calibration substance (glutamic acid) supplied by VWR International (West Chester, PA, USA) was used as a control for the combustion and for the remaining quantity of oxygen. The different samples and the calibration substance were placed on the carousel of the Elementar Vario MAX CN analyser (Elementar GmbH, Hanau, Germany) and were sequentially introduced in the analyser. The integration of the nitrogen peak (released from the combustion of the samples) with the software Elementar Vario, allowed to quantify the nitrogen and consequently the protein content in the sample. 2.2.2. Degree of Hydrolysis The degree of hydrolysis is generally evaluated with spectrophotometry techniques estimating the level of free reactive amino groups. Different spectrophotometry techniques exist among which the most popular is the TNBS (trinitro benzene sulfonic acid) assay adapted from the method described by Adler-Nissen in 1979 [12]. This method is based on the reaction of TNBS, under alkaline conditions, with primary amines resulting in the transformation of TNBS into a chromophore detectable with spectrophometry. L-Leucine (0.5–3.0 mM) (VWR) was used to generate a standard curve. All samples and standard solutions were prepared in 1 % (w/v) SDS. Triplicate aliquots (15 �L) of diluted test (hydrolysates or native proteins) or standard solutions were added to 45 �L sodium phosphate buffer (0.2125 M, pH 8.2) into a 96 well plate. TNBS reagent (45 �L) consisting of 0.05 % (w/v) TNBS (Sigma-Aldrich) in water was added to each well, followed by incubation at 50 °C for 60 minutes in a thermostated chamber covered with aluminium foil to exclude light. The reaction was stopped by the addition of 0.1 N HCl (90 �L) to each well and the absorbance values were measured at 340 nm using a multilabel plate reader (Victor, Perkin Elmer, Waltham, MA, USA). 2.3. Detection of milk hydrolysates with immunodetection

Most of the methods employed for a fast detection of the antigenicity of milk traces in food products are based on immunodetection techniques such as dot blot, ELISA or Western blot techniques. However, it has to be noted that the antigenicity or antibody binding capacity as assessed by such immunological methods that usually employ IgG or IgY raised in animals is clearly distinct from human IgE antigenicity. The different immunological methods were applied in this project to determine their efficiency when applied to the detection of peptides from hydrolysates. 2.3.1. Immunodetection of milk hydrolysates by dot blot analysis Milk protein hydrolysates were diluted and equal quantities of proteins (1.5 µg) were spotted in triplicate onto a nitrocellulose membrane (GE-Healthcare, Uppsala, Sweden). After drying, the membranes were saturated at room temperature for 1 hour with diluted Sea Block Blocking Buffer (Pierce Biotechnology, Inc., Rockford, IL, USA) devoid of milk proteins. The membranes were rinsed 3 times 10 minutes in TBS/0.1 % Tween 20 before being incubated for 1 hour in a 1/5000 antibody solution (either rabbit anti-CN or a mixture of rabbit anti-�-LG/goat anti-�LA antibodies or anti-rabbit LF/ anti-goat Ig) in Sea Block Blocking Buffer/TBS/0.1 % Tween 20. The membranes were rinsed 3 times 10 minutes and subsequently incubated for 1 hour in fluorescent labelled secondary antibody solution (donkey anti-rabbit Alexa fluor 647 and/or donkey anti-goat Alexa fluor 555 from Molecular probes (Paisley, UK)) diluted 10000 times in Sea Block Blocking Buffer/TBS/0.1 % Tween 20. The membranes were rinsed 3 times in TBS/0.1 % Tween 20, then inserted into a 96 well-plate device (Perkin Elmer, Waltham, MA, USA) to measure the emitted fluorescence with a multilabel plate reader (Victor, Perkin Elmer).


β-LG or α-CN specific Ig

Avidin peroxydase Substrate

Signal

BB

B

B Biotinylated β-LG or CN

Competition hydrolysate / Biotinylated β-LG or Na-CN

SignalInhibition signal

Ig specific milk allergen

Milk Milk allergenallergen

milk allergen specific Ig

Enzyme labelled IgSubstrate

Signal

Sandwich ELISAIndirect competitive ELISA



Signal

BB

B

B Biotinylated β-LG or CN







Signal



Signal

BBBB

BB

BB Biotinylated β-LG or CN







Signal

Sandwich ELISAIndirect competitive ELISA

The fluorescence was measured at the excitation/emission wavelength specific for the Alexa fluor 647 (620/680 nm) and Alexa fluor 555 (530/ 580 nm). 2.3.2. ELISA

Three kits (total milk, CN and β-LG) from two different commercial suppliers were used to assess the residual antigenicity of the different milk hydrolysates. Hydrolysates made from skimmed milk were tested with the commercial kit targeting total milk proteins while specific CN and β-LG kits were used to analyse the CN and WPC hydrolysates respectively. The kits characteristics are summarised in Annex 2. Both the CN and β-LG kit are indirect competitive ELISAs while the total milk kit is a sandwich ELISA with the schematic principle depicted in Figure 2.

Figure 2: ELISA systems for the analysis

of milk derived protein hydrolysates

The analyses with different ELISA systems were performed according to the manufacturer’s instructions. The protein hydrolysates were diluted in the dilution buffer provided in the different kits to obtain values in the calibration range. Standards that served for establishing the calibration curves were analysed in parallel to the diluted samples hydrolysates. The concentrations of milk, CN or β-LG were extrapolated from the standard curves and were further corrected by the appropriate dilution factor. The production of hypoallergenic formulae involves an extra process step consisting in the elimination of the residual intact milk proteins. Ultrafiltration of the hydrolysates through membranes with a cut off sufficient to eliminate the intact milk proteins (molecular weight in the range of 14-25 kDa) was performed. Aliquots of 2 ml of milk hydrolysates were centrifuged at 3000 x g in ultrafiltration devices (Sigma Aldrich, St Louis, MO, USA) with a cut off of 10 kDa. The collected fractions were further submitted to ELISA to determine the impact of ultrafiltration on the detection of milk peptides. 2.4. Detection of milk hydrolysates by electrophoresis and western blotting

Electrophoresis allows the determination of the molecular size distribution of the emerging milk derived peptides and the residual proteins within a gel. Therefore the different hydrolysates were separated with 1D electrophoresis on the XCell SureLock Mini-Cell electrophoresis system (Invitrogen, Carlsbad, CA, USA) connected to a Power Pac 200 power supply (Bio-Rad Laboratories, Hercules, CA, USA). Prior to electrophoresis, 4 µl of the hydrolysates collected at different time points were diluted in 5 µl Tricine SDS sample buffer (2X) consisting of 450 mM


Tris HCl; 12 % glycerol; 4 % SDS; 0.0025 % Coomassie blue G; 0.0025 % phenol red pH 8.45) supplemented with 1 µl of 10 X dithiothreitol (500mM). Diluted samples (15 µl) were loaded on the mini Tris-tricine 12 % precast gels (80*70*1.0 mm) from Invitrogen designed for the separation of low molecular weight molecules. The electrophoresis was carried out in Tricine-SDS buffer (10 mM Tris; 10 mM Tricine; 0.01 % SDS pH 8.3) at 150 V until the dyes reached the bottom of the gel. Mini-gels were removed from the cassettes and either fluorescently stained with Sypro ruby or equilibrated in the transfer buffer for Western blot analysis. The protein bands were visualised with Sypro ruby fluorescent staining specific for the detection of total proteins according to the supplier's procedure (Invitrogen). Briefly the gels were fixed in a mixture of 50 % methanol and 7 % glacial acetic acid before being stained with Sypro ruby overnight. After being washed with a solution of 10 % methanol/ 7 % glacial acetic acid and rinsed with water, the gels were scanned at the excitation/emission wavelengths of 450 nm/610 nm respectively with Typhoon 9400 system (GE Healthcare) at 50 μm resolution. When submitted to Western blotting detection, the gels were equilibrated immediately after electrophoresis in the transfer buffer containing 10 % methanol, 24 mM Tris and 194 mM glycine. The proteins and hydrolysates separated in the gels were electrotransferred onto low fluorescence PVDF membranes (GE Healthcare) with a semi dry blotting system (GE Healthcare). After transfer and saturation in diluted Sea Block Blocking Buffer (Pierce Biotechnology) for 1 hour, the membranes were treated in the same manner as described for the dot blot experiment (see 2.3.1) with washes and dilution of antibodies performed in TBS buffer pH 7.4, 0.5 % Tween 20. For the detection the membranes were scanned with the Typhoon scanner at the wavelengths corresponding to the fluorescent dyes (Alexa fluor 555 (530/ 580 nm) and Alexa fluor 647: (620/680 nm)). 2.5. Detection of milk hydrolysates with a proteomic approach.

2.5.1. Capillary electrophoresis-UV (CE-UV) The hydrolysates were characterised with CE-UV and mass spectrometry (MS) that give detailed information of the complexity of the hydrolysates and can provide the identification of the milk-derived peptides. Analyses were carried out with a CE apparatus (P/ACE™ MDQ, Beckman Instruments, Fullerton, CA, USA) equipped with both a photo diode array and selectable-wavelength UV/Vis detector (200, 214, 254 and 280 nm filters included), set up at 200 nm for the detection of milk-derived peptides. The CE instrument was controlled by the Beckman 32 Karat™ Software. The bare fused-silica capillary (55 cm with 75 μm i.d) was purchased from Polymicro Technologies (Phoenix, Arizona, USA). The detection length to the UV detector was around 40 cm. Before first use, the capillary was conditioned by rinsing for 20 min with 0.1 M NaOH followed by water for 10 min and separation buffer (100 mM formic acid pH 2.5) for 10 minutes. Injections were made hydrodynamically (at the anodic end using N2) at a pressure of 3450 Pa (0.5 psi) for 4 s. All separations were made under a running voltage of 20 kV for about 35 minutes. Between runs, the capillary was flushed for 3 min with 0.1 M sodium hydroxide, then for 3 min with deionised water (Millipore, Bedford, MA, USA), and finally for 5 min with the separation buffer (100 mM formic acid pH 2.5). 2.5.2. Capillary electrophoresis-ESI-MS To perform CE-MS experiments, the CE apparatus was coupled with an orthogonal electrospray interface (ESI) to the MS detector (LCQ Deca, Thermofinnigan, USA) as represented in Figure 3. The hydrolysates were injected in a bare fused silica capillary (L: 88 cm; ID: 50 µm) and separated under a 30 kV voltage with a 100 mM formic acid pH 2.5 running buffer. The peptides


MS

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eluted from the capillary were sprayed into the mass spectrometer with a coaxial sheath-flow (50 % methanol/ water/ 0.05 % formic acid) before acquisition of the mass spectra and fragmentation pattern in the positive mode. Peptide sequences were determined after analysis of the mass spectra data with Mascot Distiller software and homology searches in the Swissprot database. Figure 3: Schematic principle of CE-MS

2.5.3. Nanoelectrospray quadrupole time-of-flight tandem mass spectrometry (nano-ESI Q-TOF MS/MS) Milk protein hydrolysates dialysed through membranes with a cut off of 500 Da (Interchim, Montluçon, France) and ultrafiltered through the centrifugal devices (Sigma) were analysed by capillary LC-MS/MS. The samples were separated on a capillary flow-liquid chromatography system (Waters, Manchester, UK) coupled on-line to a nanoelectrospray quadrupole time-of-flight mass spectrometer (Q-TOF Ultima Global, Waters, Manchester, UK). The hydrolysates were 10 times diluted, desalted and preconcentrated on a precolumn LC Packings C18 capillary cartridge (300 μm id, 150 mm length, 5 μm particles size from Sunnyvale (CA, USA) before being separated on a C18 High-loading capacity capillary column (Grace Vydac with 150 μm id, 150 mm length, 3 μm particles size, 190 Å porosity). Separation of the samples occurred under a 1 μl/ min flow and a gradient of solvents A: 97 % water, 3 % acetonitrile, 0.1 % formic acid and B: 97 % acetonitrile, 3 % water, 0.1% formic acid. Basically, the peptides were eluted using a two-step linear gradient (0-5 min: 95 % A; 5-115 min: 5-100 % B; 115-135 min: 100 % B; 135-140 min: 0-95 % A). Mass spectra in full scan mode were acquired in the positive mode within a m/z range of 200-1500. The fragment ion spectra were processed using the software Mass Lynx version 4.0 (Waters) that converts MS/MS raw data into peak lists that allows searching in the Swiss-Prot/TremBL database with the software Protein Lynx Global Server 2.1. Possible modifications (carboxymethylation of cysteine, oxidation of methionine) were considered in the sequence search. Peptide sequences were assigned a peptide score which is a measure for the confidence of the sequence identification. A peptide score of 20 or above gives a probability of 95 % to assign the correct sequence.



3.1. Production of milk hydrolysates

Eighteen hydrolysates were obtained by hydrolysis of the 3 sources of milk proteins with the 5 different selected enzymes, and a combination of 2 of them. Those hydrolysates were characterised by 12 different time points (ranging from 5 minutes to 6 hours) and 3 series of 3 to 4 controls at t0 (22 samples corresponding to the adjustment of pH and heat treatment before enzymatic digestion). Thus, 238 samples differing in protein source and degree of hydrolysis were generated in this study to be characterised and to be used to study the detection of milk-derived peptides. 3.2. Milk hydrolysates characterisation

3.2.1. Protein content of the hydrolysates The protein content of all milk hydrolysates (CN, WPC and Milk), as determined by nitrogen content assessment is summarised in Table 2. The total nitrogen content is expressed as a mass fraction of nitrogen. The protein concentration (C) expressed in mg/ml (Table 2) was deduced from the nitrogen content by using a conversion factor of 6.38, which is specific for milk proteins. 3.2.2. Degree of hydrolysis The degree of hydrolysis is an index often used to characterise the hydrolysates. The hydrolysis degree expressed in a percentage corresponds to the proportion of peptide bonds from the protein that is effectively cleaved by the enzymes. The degree of hydrolysis is estimated as follow: with where C corresponds to the protein concentration at time t of hydrolysis (Ct) or before hydrolysis (Ct0) and CLeu-NH2 to the concentration of free amino groups at time t or 0, and Htot characteristic for whey and casein being 8.7 and 8.2 meq.g-1 of proteins respectively. The number of cleavages (H) was estimated from the measurement with the TNBS method estimating the amount of free amino groups released (CLeu-NH2) during the enzymatic cleavage. This amount of free amino group was deduced from the calibration curve established with the serial dilution of L-leucine (Annex 3). The degree of hydrolysis for all the samples collected is reported in Table 2. The evolution of the hydrolysis degree of milk proteins digested with either trypsin or the mixture of proteases (A and O) from B. amyloliquefaciens and S. orizae can be observed in Figure 4.

Total number of peptide bonds in the protein substrate (H tot)

Number of peptide bonds cleaved (H) DH = 100x

CLeu-NH2, t Ct C0

CLeu-NH2, 0H = meq.g-1


Figure 4: Time course of A: trypsin and B: the combination of proteases (A and O) from B. amyloliquefaciens and S. orizae digestion of skimmed milk proteins.

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Time Hydrolysis Hydrolysis Hydrolysis (min) N C (mg/ml) degree N C (mg/ml) degree N C (mg/ml) degree

5 CA5 0,54 34,13 0,00 WA5 0,43 27,12 0,89 MA5 0,43 27,69 0,00protease 10 CA10 0,68 43,07 0,00 WA10 0,44 28,33 0,85 MA10 0,51 32,41 2,44B. amyloliquefaciens 20 CA20 0,67 42,55 0,00 WA20 0,46 29,48 3,12 MA20 0,49 31,26 0,29(A) 30 CA30 0,58 36,81 0,26 WA30 0,49 31,13 4,55 MA30 0,44 28,07 2,72

40 CA40 0,52 33,43 0,39 WA40 0,50 31,84 4,34 MA40 0,49 31,33 0,6450 CA50 0,56 35,73 0,00 WA50 0,53 33,94 4,91 MA50 0,43 27,69 4,3260 CA60 0,68 43,13 0,00 WA60 0,55 34,96 5,23 MA60 0,49 31,07 3,07

120 CA120 0,57 36,37 0,00 WA120 0,58 36,94 5,26 MA120 0,50 31,58 0,67180 CA180 0,71 45,04 0,00 WA180 0,59 37,45 7,39 MA180 0,52 32,86 1,44240 CA240 0,61 38,60 0,00 WA240 0,60 37,96 3,81 MA240 0,49 31,45 2,66300 CA300 0,73 46,57 0,00 WA300 0,61 38,60 8,31 MA300 0,48 30,62 2,82360 CA360 0,78 49,70 0,23 WA360 0,61 38,98 6,17 MA360 0,50 32,03 2,01

5 CO5 0,68 43,45 1,52 WO5 0,36 22,97 2,75 MO5 0,31 19,59 5,6310 CO10 0,56 35,60 2,70 WO10 0,35 22,20 6,72 MO10 0,45 28,71 4,09

protease 20 CO20 0,47 29,67 6,38 WO20 0,36 22,84 11,19 MO20 0,41 26,41 4,68A. Orizae 30 CO30 0,49 31,20 7,36 WO30 0,36 23,22 10,66 MO30 0,45 28,84 4,44(O) 40 CO40 0,48 30,62 7,97 WO40 0,47 29,99 9,06 MO40 0,42 26,92 5,86

50 CO50 0,50 31,71 10,99 WO50 0,36 23,22 13,34 MO50 0,41 26,16 14,0460 CO60 0,51 32,41 8,84 WO60 0,37 23,80 10,75 MO60 0,46 29,48 9,98

120 CO120 0,55 35,28 12,95 WO120 0,39 24,75 18,97 MO120 0,40 25,46 21,26180 CO180 0,58 36,69 12,26 WO180 0,41 26,41 21,14 MO180 0,43 27,63 18,27240 CO240 0,60 38,54 13,36 WO240 0,40 25,58 24,91 MO240 0,46 29,09 18,88300 CO300 0,64 40,58 16,18 WO300 0,43 27,56 31,94 MO300 0,50 32,16 13,45360 CO360 0,67 42,49 22,97 WO360 0,46 29,09 15,75 MO360 0,48 30,50 17,13

Trypsin 5 CT5 0,69 43,96 3,70 WT5 0,59 37,77 2,52 MT5 0,51 32,28 2,86(T) 10 CT10 0,58 37,20 2,53 WT10 0,57 36,49 2,64 MT10 0,54 34,58 4,13

20 CT20 0,51 32,47 4,70 WT20 0,55 35,15 4,49 MT20 0,50 31,58 4,1730 CT30 0,58 36,88 3,63 WT30 0,54 34,45 5,51 MT30 0,49 31,13 4,2840 CT40 0,64 41,09 4,21 WT40 0,58 36,88 6,34 MT40 0,51 32,28 3,9850 CT50 0,62 39,36 4,22 WT50 0,58 37,20 4,51 MT50 0,50 31,90 4,5960 CT60 0,65 41,15 3,83 WT60 0,53 33,56 6,74 MT60 0,51 32,79 4,71

120 CT120 0,60 38,41 2,92 WT120 0,55 34,77 10,39 MT120 0,49 31,39 4,91180 CT180 0,60 38,15 5,52 WT180 0,53 33,81 9,29 MT180 0,49 31,13 5,38240 CT240 0,56 35,73 4,29 WT240 0,58 36,88 5,48 MT240 0,49 31,39 6,25300 CT300 0,60 38,41 5,42 WT300 0,61 38,79 7,79 MT300 0,53 33,81 5,13360 CT360 0,59 37,39 6,58 WT360 0,60 37,96 3,87 MT360 0,49 31,26 4,93

Bromelain 5 CB5 0,52 32,98 4,02 WB5 0,49 31,20 3,75 MB5 0,45 28,84 2,80(B) 10 CB10 0,64 41,02 0,79 WB10 0,47 30,18 4,02 MB10 0,51 32,47 2,71

20 CB20 0,50 32,16 2,60 WB20 0,49 31,07 2,36 MB20 0,45 28,84 4,9730 CB30 0,59 37,83 0,59 WB30 0,51 32,54 6,26 MB30 0,49 31,07 3,5640 CB40 0,34 21,95 5,18 WB40 0,50 32,16 8,44 MB40 0,50 31,58 4,3450 CB50 0,57 36,11 1,85 WB50 0,52 32,92 8,57 MB50 0,46 29,48 6,1060 CB60 0,66 41,79 0,89 WB60 0,53 33,56 6,56 MB60 0,49 31,07 5,36

120 CB120 0,56 35,47 3,12 WB120 0,50 31,84 11,17 MB120 0,51 32,41 6,76180 CB180 0,56 35,54 4,72 WB180 0,53 33,56 12,17 MB180 0,51 32,35 4,59240 CB240 0,55 34,90 3,43 WB240 0,52 33,30 12,13 MB240 0,51 32,47 5,91300 CB300 0,58 37,07 2,83 WB300 0,52 33,37 11,86 MB300 0,51 32,35 6,23360 CB360 0,58 36,75 4,34 WB360 0,51 32,47 9,91 MB360 0,52 33,18 4,98

Pancreatin 5 CP5 0,67 42,55 11,85 WP5 0,56 35,92 5,46 MP5 0,53 33,81 8,37(P) 10 CP10 0,67 42,62 8,22 WP10 0,55 35,03 14,97 MP10 0,49 31,39 16,79

20 CP20 0,53 34,01 11,89 WP20 0,62 39,30 14,76 MP20 0,51 32,22 16,9130 CP30 0,68 43,64 8,73 WP30 0,60 37,96 24,19 MP30 0,51 32,28 17,2240 CP40 0,64 41,02 11,76 WP40 0,58 36,88 31,51 MP40 0,50 31,77 16,8750 CP50 0,74 47,47 12,38 WP50 0,58 36,88 25,87 MP50 0,53 33,69 15,3560 CP60 0,67 42,87 16,56 WP60 0,57 36,37 31,54 MP60 0,48 30,88 23,96

120 CP120 0,68 43,07 17,02 WP120 0,64 40,77 29,21 MP120 0,53 33,75 26,07180 CP180 0,67 43,00 20,66 WP180 0,56 35,47 39,42 MP180 0,53 33,62 28,16240 CP240 0,69 44,28 25,31 WP240 0,59 37,64 38,52 MP240 0,53 33,75 24,67300 CP300 0,77 49,13 20,41 WP300 0,60 38,28 42,04 MP300 0,51 32,28 31,15360 CP360 0,71 45,43 24,22 WP360 0,52 33,11 41,34 MP360 0,51 32,35 28,15

protease 5 CA/O5 0,54 34,45 0,89 WA/O5 0,47 29,99 3,85 MA/O5 0,49 31,01 0,69B. amyloliquefaciens 10 CA/O10 0,57 36,05 7,78 WA/O10 0,49 31,20 12,00 MA/O10 0,52 33,24 7,56+ 20 CA/O20 0,59 37,64 9,05 WA/O20 0,51 32,67 13,92 MA/O20 0,49 31,39 10,69protease 30 CA/O30 0,61 38,73 10,85 WA/O30 0,55 34,90 14,72 MA/O30 0,52 33,30 11,41A. Orizae 40 CA/O40 0,60 38,54 12,14 WA/O40 0,57 36,11 18,66 MA/O40 0,53 33,56 12,54(A/O) 50 CA/O50 0,62 39,30 14,93 WA/O50 0,59 37,51 18,18 MA/O50 0,53 34,01 15,86

60 CA/O60 0,63 40,00 10,76 WA/O60 0,59 37,90 16,23 MA/O60 0,53 33,62 15,39120 CA/O120 0,62 39,81 13,75 WA/O120 0,60 38,54 21,47 MA/O120 0,53 33,56 19,95180 CA/O180 0,67 42,49 18,20 WA/O180 0,60 38,09 24,83 MA/O180 0,51 32,67 19,57240 CA/O240 0,67 42,87 21,66 WA/O240 0,60 38,54 26,31 MA/O240 0,52 32,92 24,06300 CA/O300 0,69 44,02 16,45 WA/O300 0,60 37,96 33,87 MA/O300 0,55 35,09 25,08360 CA/O360 0,50 31,90 31,74 WA/O360 0,60 38,54 29,48 MA/O360 0,55 35,03 27,24

Enzymes Protein content Protein content Protein contentMilk (M)WPC (W)Casein (C)

Label Label Label

Table 2: Protein content and hydrolysis degree of CN, WPC and milk hydrolysed by a variety of enzymes with increasing hydrolysis times.


As illustrated in Figure 4 and noticed in Table 2, the degree of hydrolysis generally increases with increasing hydrolysis time. Additionally, depending on the enzyme used for the hydrolysis and their cleaving specificities, the extent of hydrolysis differs. The degree of hydrolysis determined after digestion with the exoprotease S. orizae cannot be directly compared to the data collected for the other hydrolases (endoproteases) since the exoprotease releases many free amino groups from the N terminal of the protein while leaving the core of the protein almost intact. Figure 4 shows the effect of combining this enzyme with the protease from B. amyloliquefaciens. These proteases that are both used in food industry act in synergy to improve the degradation of milk proteins. From the determination of the degree of hydrolysis, we conclude that all tested enzymes efficiently hydrolysed milk proteins. 3.3. Detection of milk hydrolysates with immunodetection

3.3.1. Residual antigenicity of milk hydrolysates by dot blot The dot blot technique highlights the immunoreactivity of the hydrolysates by the detection of a spot that reflects the interaction between the antigenic "protein, peptides" and the specific antibody. Denaturation and hydrolysis are expected to decrease the amount of antibody binding sites (Figure 5). Figure 5: Antibody detection of conformational and linear epitopes on a native, denatured or digested allergenic protein. The different WPC and milk hydrolysates were tested for their antigenicity in a multiplex semi-quantitative dot blot developed to simultaneously detect the presence of β-LG and α-LA or LF/Ig with antibodies labelled with 2 different fluorescent dyes while CN hydrolysates were analysed by a simplex dot blot with anti-CN antibodies. The average of the absolute intensities and their standard deviation obtained by analysis of samples in triplicates are presented in Table 3. An example of the multiplex dot blot detection carried out on WPC hydrolysed with trypsin (WT) is shown in Figure 6. As expected, increasing the hydrolysis time is associated with a reduction of immunoreactivity of the whey protein (β-LG and α-LA). After 2 hours trypsin treatment, the detection becomes negligible. This reflects the progressive degradation of βLG and αLA into peptides and specifically the breakage of β-LG and α-LA epitopes that are no longer detected by the specific antibodies directed towards those proteins.

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Figure 6: Dot blot analysis of β LG and α LA in WPC hydrolysates at different hydrolysis times.

For CN hydrolysates, the decrease in signal is less obvious. This can be explained by the fact that CNs have a destructured conformation which favours the existence of linear epitopes that remain longer intact compared to the conformational epitopes. Inversely, WPCs presenting a globular structure have mainly conformational epitopes that are destroyed during hydrolysis and progressively reduce the capacity of detection by the antibodies specific to those epitopes as described in Figure 5. 3.3.2. ELISA Performance

3.3.2.1. Total hydrolysate

With regard to the extensive use of commercial ELISA kits for the detection and quantitation of food allergens, it was of interest to determine the performance of such kits that are specific for milk allergens (total milk, �-LG and CN) to detect milk-derived peptides emerging from the enzymatic digestion. Peptide reactivity was thus determined in the hydrolysates with increasing proteolysis time. The quantities of antigenic molecules detected in the hydrolysates were estimated by using calibration curves generated with standards specific for each ELISA kit. The quantity detected in all hydrolysates were expressed in ppm (± SD) and listed in Table 3. Table 3: Immunodetection of CN, β-LG, α-LA, LF, Ig with commercial ELISA kits and dot blot techniques.

Production and detection of potentially allergenic peptides derived from milk enzymatic hydrolysates by proteomic and immunochemical approaches I-17 / 42

Label ppm SD OD SD Label ppm SD OD SD OD SD OD SD OD SD Label ppm SD OD SD OD SD OD SD OD SDCA5 18470 1403 72 10 WA5 12033 539 305 94 232 64 5 0 40 0 MA5 229 14 188 4 131 2 9 0 47 1CA10 20499 1452 57 6 WA10 12659 560 386 29 287 20 6 0 40 2 MA10 180 13 181 15 124 6 8 1 43 1CA20 22732 1513 63 8 WA20 13742 597 353 46 265 32 7 0 39 1 MA20 200 13 170 12 111 7 7 0 38 2CA30 23703 1542 69 4 WA30 13198 579 354 50 261 34 6 1 38 1 MA30 186 13 176 9 119 6 8 0 40 1CA40 14374 1328 63 4 WA40 11867 534 316 34 241 24 9 0 47 0 MA40 173 13 163 2 113 1 8 0 40 1CA50 20838 1461 65 3 WA50 12094 541 241 59 180 40 8 0 46 1 MA50 168 13 166 5 118 1 13 6 46 5CA60 19950 1438 55 4 WA60 10900 503 256 51 191 32 9 1 48 2 MA60 159 12 169 18 121 9 36 18 70 21CA120 19528 1428 62 1 WA120 9799 469 285 43 207 27 9 0 51 2 MA120 133 12 170 6 127 5 21 9 56 10CA180 17656 1386 57 3 WA180 15092 645 366 18 246 12 11 2 57 5 MA180 115 12 161 2 115 2 7 0 40 1CA240 18573 1405 85 1 WA240 13284 581 266 65 186 37 10 0 51 1 MA240 107 12 177 1 119 2 7 0 39 1CA300 22857 1517 67 1 WA300 14084 609 314 40 215 22 10 0 52 2 MA300 125 12 177 14 116 8 7 0 41 5CA360 19762 1433 65 3 WA360 12190 545 290 22 203 13 12 1 61 3 MA360 175 13 159 18 106 10 7 0 36 1CO5 12803 351 45 1 WO5 1529 89 62 2 63 0 17 0 44 0 MO5 92 12 169 8 129 6 11 1 48 1CO10 7120 345 31 3 WO10 1492 89 51 2 56 1 16 1 42 1 MO10 111 12 144 12 109 9 10 2 43 2CO20 3176 352 9 0 WO20 1317 89 52 3 57 2 16 0 43 1 MO20 98 12 142 6 112 5 11 3 45 3CO30 2770 354 8 1 WO30 1032 89 50 3 55 2 16 2 43 2 MO30 109 12 125 5 103 3 10 2 44 2CO40 2537 354 7 0 WO40 920 90 39 9 49 4 17 1 46 3 MO40 113 12 152 6 118 5 9 1 46 4CO50 2337 355 8 0 WO50 986 90 41 1 50 0 22 4 54 6 MO50 118 12 156 6 117 6 9 0 43 2CO60 2370 355 8 0 WO60 785 90 34 2 48 1 23 6 57 10 MO60 122 12 158 4 114 7 8 1 41 4

CO120 1682 358 8 0 WO120 529 90 34 2 48 1 18 1 51 0 MO120 79 12 169 2 122 2 8 1 41 3CO180 1794 422 8 0 WO180 470 90 41 2 51 1 13 0 43 1 MO180 60 12 145 9 114 6 8 1 40 3CO240 1254 424 7 0 WO240 436 90 41 2 50 1 13 0 41 1 MO240 59 12 127 17 107 6 7 1 39 3CO300 1316 359 8 1 WO300 418 90 39 4 49 2 13 1 41 2 MO300 59 12 107 19 94 5 7 1 39 2CO360 1339 424 9 0 WO360 380 91 34 4 47 2 13 1 41 1 MO360 70 12 111 18 101 6 7 0 41 2

CT5 2727 490 39 1 WT5 8150 160 103 2 84 2 17 3 47 5 MT5 302 13 107 2 86 1 5 0 37 1CT10 2160 416 44 5 WT10 8475 163 78 6 73 3 15 1 45 2 MT10 274 12 76 4 67 1 5 0 34 1CT20 2027 416 36 4 WT20 7241 152 54 1 64 1 17 2 49 4 MT20 222 11 48 3 58 2 5 0 33 0CT30 1964 417 27 4 WT30 5940 141 43 3 62 2 17 5 51 8 MT30 217 11 38 3 57 2 5 0 34 1CT40 1803 417 29 8 WT40 4996 135 35 7 57 5 13 1 45 2 MT40 206 11 32 4 54 2 11 7 39 6CT50 1722 418 22 2 WT50 4240 132 27 3 53 1 13 1 53 9 MT50 190 10 23 2 49 3 21 6 48 5CT60 1791 417 22 1 WT60 4142 131 22 2 50 2 12 0 42 1 MT60 185 10 23 1 53 1 25 17 55 16

CT120 1819 417 23 1 WT120 2591 127 18 1 51 2 13 0 44 1 MT120 148 10 8 0 49 1 14 5 46 5CT180 1672 418 16 1 WT180 2220 126 15 2 49 2 12 0 41 2 MT180 142 10 6 0 49 1 5 0 36 1CT240 1691 418 16 1 WT240 1909 126 14 1 49 1 14 1 47 7 MT240 157 10 5 0 44 0 5 0 34 1CT300 1604 418 16 1 WT300 1720 126 14 0 48 0 14 1 45 1 MT300 123 9 4 0 42 1 4 0 33 0CT360 1473 419 18 1 WT360 1672 127 14 1 50 1 13 1 46 0 MT360 138 10 5 0 42 1 5 0 34 1CB5 174 1360 43 3 WB5 3632 255 286 17 228 11 12 1 56 3 MB5 23 9 150 1 102 1 5 0 38 1CB10 2344 1326 29 1 WB10 2955 252 279 25 227 16 11 0 54 1 MB10 6 10 160 9 104 5 5 0 36 0CB20 1335 1341 27 2 WB20 2451 250 268 22 226 16 12 1 60 2 MB20 0 0 133 17 92 9 5 0 35 0CB30 1385 1340 27 1 WB30 1677 250 201 25 184 19 10 0 55 2 MB30 0 0 138 18 97 9 5 0 34 1CB40 716 1351 17 1 WB40 1324 251 151 14 142 10 25 8 96 17 MB40 0 0 149 17 104 9 4 0 33 1CB50 962 1347 17 2 WB50 1084 251 158 22 146 18 4 0 38 4 MB50 0 0 154 22 104 9 4 0 32 1CB60 2958 1318 22 2 WB60 866 252 177 16 160 11 118 20 267 52 MB60 0 0 162 39 114 18 4 0 34 0CB120 2165 1328 24 4 WB120 573 348 138 3 130 2 77 8 213 9 MB120 0 0 158 17 117 7 4 0 37 2CB180 - - 22 4 WB180 513 254 150 2 140 5 35 2 134 2 MB180 0 0 106 3 84 2 5 0 36 1CB240 2241 1327 24 4 WB240 472 254 146 7 137 9 20 2 95 12 MB240 0 0 120 8 92 5 4 0 34 0CB300 1501 1338 24 3 WB300 479 254 138 12 134 13 11 1 69 4 MB300 0 0 110 0 87 2 4 0 34 4CB360 1531 1338 23 3 WB360 464 254 122 25 128 22 10 4 61 10 MB360 0 0 113 2 87 2 4 0 32 1CP5 878 361 5 0 WP5 5862 157 265 26 192 20 7 0 42 0 MP5 0 0 120 8 83 4 7 4 36 4CP10 3419 352 6 0 WP10 5591 154 246 39 184 21 6 0 40 0 MP10 0 0 90 13 69 6 5 1 35 1CP20 1275 359 8 0 WP20 3690 138 181 28 145 17 5 0 37 1 MP20 0 0 42 3 58 2 6 1 37 0CP30 973 361 7 0 WP30 2026 132 158 24 130 13 5 0 37 0 MP30 0 0 25 1 56 1 7 1 39 1CP40 933 361 8 0 WP40 1493 131 145 6 119 5 5 0 35 0 MP40 0 0 20 0 59 3 5 0 38 1CP50 841 361 9 1 WP50 988 132 110 11 99 8 5 0 35 1 MP50 0 0 18 1 57 2 5 0 37 1CP60 837 361 7 1 WP60 776 132 100 7 96 6 5 0 37 1 MP60 0 0 16 0 56 3 5 0 38 2CP120 712 362 7 0 WP120 315 134 44 3 59 2 5 0 39 0 MP120 0 0 6 0 48 3 5 0 37 2CP180 1259 359 7 0 WP180 239 134 37 2 50 1 4 0 38 0 MP180 0 0 5 0 44 1 5 0 37 2CP240 571 363 7 0 WP240 261 134 33 2 44 1 4 0 36 1 MP240 0 0 4 0 44 3 5 0 37 2CP300 613 362 7 0 WP300 259 134 27 2 40 1 4 0 35 0 MP300 0 0 4 0 44 1 5 0 38 1CP360 622 362 7 0 WP360 247 134 38 1 46 1 4 0 36 0 MP360 0 0 4 0 46 3 5 0 39 1CA/O5 6025 404 37 4 WA/O5 10896 170 286 17 207 9 10 0 52 1 MA/O5 178 10 212 11 121 6 6 0 37 2

CA/O10 3397 411 17 2 WA/O10 4466 126 266 19 201 13 9 0 51 1 MA/O10 90 9 213 15 119 7 5 0 37 2CA/O20 2822 413 13 1 WA/O20 3459 124 214 108 171 75 8 0 50 2 MA/O20 28 9 223 5 126 3 5 0 38 2CA/O30 2476 414 12 1 WA/O30 2719 123 271 7 219 6 8 0 53 2 MA/O30 10 9 226 11 133 6 5 0 39 0CA/O40 2257 415 12 1 WA/O40 2082 123 312 21 246 14 8 1 52 4 MA/O40 3 9 125 22 81 9 5 0 42 3CA/O50 2045 416 12 2 WA/O50 1656 123 265 11 215 7 7 0 49 1 MA/O50 25 9 145 15 89 7 5 0 38 3CA/O60 1951 417 10 1 WA/O60 1262 123 259 34 219 21 9 0 56 3 MA/O60 0 0 151 9 91 3 5 0 37 3CA/O120 1657 418 8 1 WA/O120 586 125 207 5 207 5 8 0 53 1 MA/O120 0 0 136 5 88 2 5 0 35 2CA/O180 1529 495 9 0 WA/O180 385 125 155 7 183 11 8 0 52 2 MA/O180 0 0 119 10 82 4 4 0 35 2CA/O240 1598 494 9 0 WA/O240 281 126 106 13 142 14 7 0 49 2 MA/O240 0 0 120 9 84 3 4 0 34 2CA/O300 1554 419 9 0 WA/O300 236 126 98 10 141 12 7 0 51 2 MA/O300 0 0 134 6 93 3 4 0 35 2CA/O360 1649 494 11 1 WA/O360 247 126 98 4 142 4 7 0 51 1 MA/O360 0 0 116 11 88 7 4 0 37 1

IgDot blot with specific antibody raised against:

anti-CN antibodies β−LG α-LA LF Ig proteins ELISA β−LG α-LA Lfβ-LG ELISA Dot blot with specific antibody raised against: Milk total milkCasein Casein ELISA Dot blot with WPC


Figure 7: Time course detection of milk, CN, �-LG proteins present in milk (MT and MA/O), CN (CT, CA/O) and WPC (WT, WA/O) enzymatically digested with either trypsin or a mixture of proteases from B. amyloliquefaciens and S. orizae with ELISA kits.

Enzymatic hydrolysis WPC

0

2000

4000

6000

8000

10000

12000

5 10 20 30 40 50 60 120 180 240 300 360


β-L

G c

once

ntra

tion

(ppm

)

WT

WA/O

Enzymatic hydrolysis of Caseins

0

1000

2000

3000

4000

5000

6000

7000

5 10 20 30 40 50 60 120 180 240 300 360


αs-

CN

con

cent

ratio

n (p

pm)

CT

CA/O

Enzymatic hydrolysis of skimmed milk

0

50

100

150

200

250

300

5 10 20 30 40 50 60 120 180 240 300 360


Tota

l milk

con

cent

ratio

n (p

pm)

MT

MA/O


Figure 7 summarises the type of results presented in Table 3 concerning the evolution of the quantity of antigens (milk, CN and β-LG) detected in each type of hydrolysates with increasing hydrolysis time. The decrease of the detection of CN, β-LG and milk proteins as determined by ELISA test kits during hydrolysis is exemplified for CN (CT and CA/O), WPC (WT and WA/O), and milk (MT and MA/O) hydrolysates hydrolysed respectively with trypsin or the mixture of proteases derived from B. amilolyquefaciens and S. orizae. The results that are obtained by ELISA analysis are in agreement with the dot blot analysis. When the hydrolysis time increases, the antigenicity of the milk-derived hydrolysates decreases for all three milk protein sources. This is correlated to the gradual degradation of the antigenic proteins causing the decrease in signal. The reduction of the signal in CN hydrolysates is less pronounced than for WPC or milk hydrolysates. As mentioned above, the antibodies of the kits target intact proteins and it can be assumed that whey proteins with globular structures possess many conformational epitopes while the less structured CNs have mainly linear epitopes (Figure 5). Hydrolysis favours the unfolding of the proteins and thereby the destruction of conformational epitopes of the globular proteins explaining the strong reduction of ELISA signals for whey proteins compared to CNs. Therefore ELISA measures the disappearance of the proteins but does not detect the newly emerged peptides. 3.3.2.2. Ultrafiltered hydrolysates

To produce hypoallergenic formulae, enzymatic digestion is always followed by the elimination of residual undegraded proteins or large peptide fragments that can trigger immune reactions. The remaining “intact proteins” can be removed by submitting the hydrolysates to ultrafiltration by using a centrifugation device with a cut off of 10 kDa. CN and WPC hydrolysates after 5, 10, 20 or 40 minutes of proteolysis were ultrafiltered and subsequently analysed with CN and β-LG ELISAs to determine the immunoreactivity of milk derived peptides and not that of residual proteins. The detection (in ppm) of CN and β-LG in the hydrolysate samples before and after ultrafiltration as well as the percentage of signal loss are reported in Table 4. Figure 8 presents examples of the decrease of signal due to the elimination of residual intact proteins by ultrafiltration. After 5 minutes of hydrolysis the signal is drastically reduced by ultrafiltration suggesting that proteins are poorly degraded at this stage and those intact proteins or large protein fragments are detected in the sample before ultrafiltration (figure 8). Increasing the time of proteolysis reduces also the signal of detection in the ultrafiltered hydrolysates. More than 98% of the ELISA signal is lost when the hydrolysates are submitted to ultrafiltration revealing the poor detection of peptides by means of ELISA.


Effect of ultrafiltration on ELISA detection

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

WT5 WT10 WT20 WT40Hydrolysis time of WPC with Trypsin

Con

cent

ratio

n β

-LG

(ppm

) 98,98%+/- 2,8 99,03%+/- 2,7

99,02%+/- 2,9

98,86%+/- 3,8

Ultrafiltration

Table 4: Effect of the ultrafiltration process of CN and WPC hydrolysates on the antigenic detection determined with ELISA.

ppm ± SD ppm ± SD % ± uncertainty (u)CAO5 6025 404 17 0,3 99,71 9,5CAO10 3397 411 14 0,3 99,59 17,1CAO20 2822 413 12 0,3 99,56 20,6CAO40 2257 415 11 0,2 99,51 26,0

CP5 878 361 4 0,2 99,55 58,0CP10 3419 352 7 0,2 99,80 14,5CP20 1275 359 7 0,2 99,43 39,8CP40 933 361 5 0,2 99,51 54,6CT5 2727 490 16 0,3 99,43 25,3CT10 2160 416 15 0,3 99,30 27,1CT20 2027 416 15 0,3 99,25 28,9CT40 1803 417 16 0,3 99,09 32,6WAO5 10896 170 18 2 99,83 2,2WAO10 4466 126 9 2 99,79 4,0WAO20 3459 124 8 2 99,77 5,1WAO40 2082 123 8 2 99,62 8,3

WP5 5862 157 11 2 99,82 3,8WP10 5591 154 9 2 99,84 3,9WP20 3690 138 8 2 99,78 5,3WP40 1493 131 7 2 99,52 12,4WT5 8150 160 83 4 98,98 2,8WT10 8475 163 82 4 99,03 2,7WT20 7241 152 71 3 99,02 2,9WT40 4996 135 57 3 98,86 3,8

Before ultrafiltration After ultrafiltration Signal lossHydrolysates

Figure 8: Influence of the ultrafiltration process of WPC tryptic digest on the detection of β-LG with ELISA.


3.4. Peptide antigenicity identified with electrophoresis and Western blotting

3.4.1. Milk protein standard ELISA analyses provide insight in the antigenicity of the milk hydrolysates. Electrophoresis, on the other hand, allows the visualisation of protein degradation products and peptides. This is illustrated in Figure 9 which shows the electrophoresis pattern of a standard mixture of β-LG variant A and β-LG variant B hydrolysed with B. amylolequefaciens protease. The enzymatic digestion of only two proteins (both with a molecular weight of 18 kDa) leads to the formation of a variety of proteolytic peptides and the progressive disappearance of the intact proteins (Figure 9). In the case of more complex matrices like WPC, CN and skimmed milk hydrolysates, the profile of the emerging peptides becomes more complex. Figure 9: Progression of the enzymatic digestion (with protease from B. amyloliquefaciens) of a standard mixture of β-LGA and β-LGB (at 5, 10, 20, 30, 40, 60, 120, 180, 240 300 and 360 minutes). 3.4.2. Total hydrolysates All hydrolysates were analysed by electrophoresis and Western blot. The gels and blots are attached in Annexes 4-6 but whey protein hydrolysed with the combination of B. amyloliquefaciens and S. orizae was taken as an example to illustrate the visualisation of the proteins and peptides during enzymatic digestion. As shown in Figure 10, already at five minutes of hydrolysis, peptide fragments could be detected. CN proteins were rapidly degraded and disappeared after 20-30 minutes of hydrolysis. The intensity of whey proteins: especially migrating at the molecular mass of β-LG and αLA decreased due to the degradation of those proteins into peptides intermediates with lower molecular weights. Several emerging peptides with a high intensity at the beginning of the

MW βLG 5’ 10’ 20’ 30’ 40’ 50’ 60’ 120180 240 300 360

3.49

26

1714.2

6.5

1.06

MW βLG 5’ 10’ 20’ 30’ 40’ 50’ 60’ 120180 240 300 360

3.49

26

1714.2

6.5

1.063.49

26

1714.2

6.5

1.06

26

1714.2

6.5

1.06

kDa


ELECTROPHORESIS MA/O

CN αs

β-LGk

LF

β

α-LA

BSA

Ig

Milk t0

Hydrolysis Time 5’ 360’MW

WESTERN BLOT MA/O

Milk t0


anti-β-LG

anti-α-LA

ELECTROPHORESIS MA/O

CN αs

β-LGk

LF

β

α-LA

BSA

Ig

CN αs

β-LGk

LF

β

α-LA

BSA

Ig

Milk t0


WESTERN BLOT MA/O

Milk t0


anti-β-LG

anti-α-LA

A

B

C

hydrolysis tend also to decrease likely due to their degradation into smaller peptides that are hardly detected by electrophoresis. The detection of β-LG by means of Western blotting reveals that β-LG progressively disappeared due to hydrolysis. It is possible to detect β-LG degradation products in the early stages of hydrolysis (Figure 10B). However, no degradation products could be detected with the antibodies after more than 10 minutes of hydrolysis. The emerging peptides from the protein hydrolysis were poorly detected likely due to the disappearance of the initial conformational epitopes present on β-LG. Also α-LA could be detected on the membrane with its specific antibodies which revealed also the presence of high molecular weight molecules in the early stages of the proteolysis. But, the detection of hydrolysates with the anti-α-LA antibody was inefficient which showed the limitation of western blot to assess the presence of milk-derived peptides in a sample. Figure 10: Electrophoresis of milk proteins hydrolysed (MA/O) by the protease mixture from B. amyloliquefaciens and S. orizae (A) and immunodetection of B: β-LG and C: α-LA after gel transfer by Western blot.

The detection of hydrolysis products was further investigated by 2D-DIGE electrophoresis, carried out according to the schematic principle described in Figure 11 (protocol in Annex 7) using sensitive fluorescent labelled dyes. As illustrated in the schematic procedure (Figure 11), a skimmed milk sample was stained with Cy5 while the hydrolysate fraction collected after 30 minutes of hydrolysis was labelled with Cy3. The two samples were mixed and run on the same IEF gel in the first dimension (separation according to the isoelectric point) before being separated in the 2nd dimension according to the molecular weight.


Figure 11: Principle of 2DE-DIGE for the simultaneous detection of total milk proteins and milk-derived peptides obtained after 30 minutes of hydrolysis

Figure 12: 2D-DIGE electrophoresis of milk proteins before (red) and after 30 minutes enzymatic hydrolysis (green). As seen in Figure 12, intact proteins from skimmed milk are detected in red while the proteolytic peptides released during enzymatic hydrolysis appear in green. After 30 minutes of hydrolysis, almost all milk proteins were degraded into peptides. However, with increasing hydrolysis time, the detection became unsatisfactory due to the comigration of the labelled peptides with the Dyes. Detection by the electrophoresis is therefore not suitable for the analysis of peptides derived from enzymatic hydrolysis of milk proteins.

pH 3 MW (kDa)

1,06

3,49 6,5

14,2

17

26,6

pH 10

SDS PAGE separation: 2nd Dimension

Isoelectrofocusing:

1rst Dimension

Peptide labelling

Hydrolysate

0 minutes (Cy5) 30 minutes (Cy3)

Mix labelled samples

pH 3 pH 10

SDS PAGE separation: 2nd Dimension

Isoelectrofocusing:

1rst Dimension

Peptide labelling

Hydrolysate

0 minutes (Cy5) 30 minutes (Cy3)

Mix labelled samples

pH 3 pH 10


3.4.3. Ultrafiltered hydrolysates As for ELISA, the effect of an ultrafiltration on the detection of milk derived peptides was visualised by 1D electrophoresis (Figure 13). In the non-ultrafiltered hydrolysates several bands specific to milk proteins were visible that progressively disappeared as the proteolysis proceeded. In contrast to this, in ultrafiltrated hydrolysate samples no proteins or peptides were visible. The absence of any peptide bands after ultrafiltration means that this procedure removes intact proteins and larger degradation products. The absence of peptides below 10 kDa at higher hydrolysis times suggests either that the detection system was not sensistive enough (with the use of Sypro ruby) or that the peptides had run out of the gel. Figure 13: Effect of ultrafiltration on the detection of milk derived peptides emerging by hydrolysis with the combination of proteases (from B. Amiloliquefaciens and S. orizae) (MA/O).

3.5. Peptide detection and identification by capillary electrophoresis and mass spectrometry

As demonstrated above, the detection of milk-derived peptide by means of immunological and electrophoretic techniques that target the antigenic proteins is clearly insufficient. The limitations of ELISA and electrophoresis/Western blot techniques for the detection of peptides, stress the requirement of other methods (proteomics). Capillary electrophoresis-mass spectrometry has the potential to be suited to confirm the presence of milk-derived peptides in hydrolysates by means of sequence identification. 3.5.1. Capillary electrophoresis-UV A capillary electrophoresis method was therefore used to detect the presence of milk-derived peptides. Hydrolysates collected at different times of hydrolysis were always tested in triplicate. The electrophoretic patterns (Figure 14) of milk-derived peptides in a mixture of β-LG variant A

M A/O

5’ 240’30’ 60’ 360’0

Hydrolysis Time

M A/O ultrafiltered (Cut off 10 kDa)

MW 5’ 240’30’ 60’ 360’

Hydrolysis Time

CN αs

β-LGk

LF

β

α-LA

BSA

Ig

M A/O

5’ 240’30’ 60’ 360’0

Hydrolysis Time

5’ 240’30’ 60’ 360’0

Hydrolysis Time


MW 5’ 240’30’ 60’ 360’

Hydrolysis Time

MW 5’ 240’30’ 60’ 360’5’ 240’30’ 60’ 360’

Hydrolysis Time

CN αs

β-LGk

LF

β

α-LA

BSA

Ig

CN αs

β-LGk

LF

β

α-LA

BSA

Ig

M A/O

5’ 240’30’ 60’ 360’0

Hydrolysis Time


MW 5’ 240’30’ 60’ 360’

Hydrolysis Time

CN αs

β-LGk

LF

β

α-LA

BSA

Ig

M A/O

5’ 240’30’ 60’ 360’0

Hydrolysis Time

5’ 240’30’ 60’ 360’0

Hydrolysis Time


MW 5’ 240’30’ 60’ 360’

Hydrolysis Time

MW 5’ 240’30’ 60’ 360’5’ 240’30’ 60’ 360’

Hydrolysis Time

CN αs

β-LGk

LF

β

α-LA

BSA

Ig

CN αs

β-LGk

LF

β

α-LA

BSA

Ig


360 minutes hydrolysis

5 minutes hydrolysis

and β-LG variant B hydrolysed with B. amylolequefaciens protease for 5 minutes overlapped well stressing the reproducibility of the method. This reproducibility was likely not altered by the complexity of the sample since the 3 electropherograms acquired at extended hydrolysis time (360 minutes) were identical (Figure 14). Figure 14: Electropherograms of 3 different injections of standard mixture of β-LGA and β-LGB hydrolysate at 5 and 360 minutes. The detection of milk derived peptides emerging from the digestion by the proteases from B. amyloliquefaciens and S. orizae by CE is illustrated in Figure 15. Milk samples with increasing hydrolysis time (0, 5, 60 or 360 minutes) were analysed under the same conditions. The electrophoretic pattern was drastically modified due to the hydrolysis. After 5 minutes of hydrolysis the intact proteins were no longer detected while a multitude of peaks characteristic of neoformed peptides became visible.


Figure 15: Electropherograms of milk digested with the mixture of proteases from B. Amiloliquefaciens and S. orizae before and at 5, 60 and 360 minutes of hydrolysis.

T0

T 5 min

T 60 min

T 360 min


The multitude of peptides detected in the electropherograms after extensive hydrolysis confirmed that capillary electrophoresis is a suitable method to assess the presence of milk-derived peptides this in contrast to ELISA and electrophoresis/western blotting techniques. Furthermore, when coupled to mass spectrometry, CE is likely a suitable method for the identification of milk derived peptides. 3.5.2. Nanolectrospray quadrupole time-of-flight tandem mass spectrometry (nano-ESI Q-TOF MS/MS) To assess the possibility to detect milk-derived hydrolysates by CE-MS, the mass spectrometric detection and identification of milk-derived peptides was performed with nanoLC-ESI-Q Tof. This can ascertain the capacity of confirmatory methods like CE-MS and LC-MS to detect and identify the sequence of peptides in ultrafiltrated hydrolysates. Milk hydrolysates formed after proteolysis with proteases from B. amyloliquefaciens and S. orizae were analysed by LC-MS. Peptides detected and identified in hydrolysates harvested after 5, 30, 60, 240 and 360 minutes of hydrolysis are listed in Table 5. As depicted in Table 5, many peptides originating from CNs can be identified in the hydrolysates. However, αs1-CN and β-CN were repeatedly found in all hydrolysates. With regard to whey proteins, β-LG is the only protein detected and identified unambiguously in the different hydrolysates. Some of the peptides identified possessed some modifications that are highlighted in Table 5. The fragmentation pattern was used for the determination of the peptide sequence (Figure 16) and the peptide score allows to determine the good confidence that the peptides defined in Table 5 are effectively present. Figure 16: Fragmentation pattern of an ion characteristic of �s1 casein peptide.

The detection and identification of peptides in samples that were digested for a long time and had been ultrafiltered confirmed the suitability of this type of techniques to assess the presence of milk-derived peptides in food matrices. Table 5: Milk-derived peptides identified by nanoLC-ESI Q Tof.


hydrolysis time Protein m/z charge ladder scorstart end Sequence Modificationαs1CN 997,141 2 20,202 15 31 (L)SRPKHPIKHQGLPQEVV(N) Carbamyl N-TERM (N-TERM) S for A (1), V for L (17)

499,286/91-2 39,2157 23 31 (K)NQGLPQEVV(N) Methyl N-TERM (N-TERM) N for H (1), V for L (9)996,617 1 40 24 31 (H)QGLPQEVV(N) SMA N-TERM (N-TERM) V for L (8)997,567 1 42,2222 24 31 (H)QGLPQEVV(N) SMA N-TERM (N-TERM), Deamidation Q (1) V for L (8)806,463 1 58,9744 41 47 (V)APFPEVF(G)455,274 3 36,5079 96 106 (H)IQKEDVPSERY(L)682,439 2 31,746 96 106 (H)IQKEDVPNKRH(L) N for S (8), K for E (9), H for Y (11)497,764 2 46,6667 99 106 (K)DDVPSERY(L) Methyl N-TERM (N-TERM) D for E (1)497,764 2 46,6667 99 106 (K)EDVPSERY(L)612,354 2 26,9841 124 134 (Q)LQVVPNSAEER(L) Dehydration ST (7) Q for E (2), V for I (3)

βCN 735,42 3 33,3333 44 59 (K)KIKKFQSKEQQQTEDE(L) Myristoyl K (4) K for E (3), K for E (8)998,609 1 52,9412 82 90 (I)PNSLPQNIP(P) Methyl N-TERM (N-TERM), Deamidation N (2), O18 (C-TERM)810,042 2 33,3333 88 102 (Q)NIPPLTQTPVVVPPF(L)752,993 2 25,9259 89 102 (N)IPPLTQTPVVVPPF(L)810,064 2 34,6667 90 102 (I)PPLTQTPVVVPPF(L) Myristoyl N-TERM (N-TERM), Hydroxyl DKNP (2), Deamidation Q (5)753,031 2 39,1304 91 102 (P)PLTQTPVVVPPF(L) Myristoyl N-TERM (N-TERM)754,034 2 33,3333 91 102 (P)PLTQSPVVVPPF(L) Myristoyl N-TERM (N-TERM), Hydroxyl DKNP (6) S for T (5)753,052 2 52,9412 94 102 (T)RTPVVVPPF(L) Myristoyl N-TERM (N-TERM), Palmitoyl CST (2) R for Q (1)855,532 1 46,6667 95 102 (Q)TPVVVPPF(L)603,371 1 70,3704 124 128 (E)VPYPK(Y) V for M (1), Y for F (3)964,159 2 21,8391 140 154 (S)LTLTDVEHLHLPLPL(L) Myristoyl N-TERM (N-TERM), 13C L (3) H for N (8)552,431 1 77,7778 150 154 (H)LPLPL(L)652,404 1 54,5455 152 157 (P)LPLLQS(W) Dehydration ST (6)1081,69 1 47,3684 180 189 (S)LSQAKVLPIP(Q) Hydroxyl DKNP (5) A for S (4), I for V (9)587,343 2 54,386 192 201 (K)AVPYPQRDLP(I) Methyl CDEHKNRQ (8), O18 (C-TERM) L for M (9)603,371 1 70,3704 193 197 (A)VPYPQ(R)815,486 1 63,6364 193 198 (A)IPYPRR(D) Methyl CDEHKNRQ (6) I for V (1), R for Q (5)

β−LG 554,357 1 55,5556 44 48 (S)DIALL(D) 13C L (4), O18 (C-TERM) A for S (3)623,354 2 36,5079 141 151 (R)SPEVDDEALEK(F) Methyl N-TERM (N-TERM) S for T (1)623,354 2 36,5079 141 151 (R)TPEVDDEALEK(F)

αs1CN 499,315 3 25,3333 19 31 (K)HPIKHQGLPQEVV(N) Methyl N-TERM (N-TERM) V for L (13)499,317 2 43,1373 23 31 (K)NQGLPQEVV(N) Methyl N-TERM (N-TERM) N for H (1), V for L (9)560,312 1 70,3704 41 45 (V)APFPE(V)806,453 1 74,359 41 47 (V)APFPEVF(G)455,254 3 44,4444 96 106 (H)IQKEDVPSERY(L)497,761 2 55,5556 99 106 (K)DDVPSERY(L) Methyl N-TERM (N-TERM) D for E (1)497,761 2 55,5556 99 106 (K)EDVPSERY(L)994,55 1 62,2222 99 106 (K)EDVPTEKY(L) Methyl CDEHKNRQ (6) T for S (5), K for R (7)547,793 2 56,1404 125 134 (L)DIVPNSAEER(L) Pyrrolidone carboxylic acid N-TERM (N-TERM), Dehydration ST (6) D for E (1)789,449 1 74,359 194 200 (S)FSDIPNP(I)

αs2CN 591,342 1 70,3704 190 194 (F)ALPQY(L)βCN 735,374 3 30,303 43 59 (N)KKIEKWQNEEQQQTEDE(L) Methyl CDEHKNRQ (9) W for F (6), N for S (8)

998,576 1 64,7059 82 90 (I)PNSLPQNIP(P) Methyl N-TERM (N-TERM), Deamidation N (2), O18 (C-TERM)810,018 2 33,3333 88 102 (Q)NIPPLTQTPVVVPPF(L)810,047 2 28,7356 88 102 (Q)NIPPVSRTPVVVPPF(L) V for L (5), S for T (6), R for Q (7)753,005 2 30,8642 89 102 (N)IPPLTQTPVVVPPF(L)855,07 2 36 90 102 (I)PPLTRTPVVVPPF(L) 13C L (3), Palmitoyl CST (6) R for Q (5)753,026 2 42,029 91 102 (P)PLTQTPVVVPPF(L) Myristoyl N-TERM (N-TERM)855,57 1 68,8889 95 102 (Q)SPVVVPPF(L) Methyl N-TERM (N-TERM) S for T (1)855,52 1 68,8889 95 102 (Q)TPVVVPPF(L)696,97 2 41,2698 104 114 (L)QPEVLGVSKVK(E) Myristoyl K (9), Amidation C-TERM (C-TERM) L for M (5)487,624 3 52,6316 121 130 (K)NKEMPFPKYP(V) Myristoyl K (8) N for H (1)487,97 3 43,8596 121 130 (K)NEEMPFPKYP(V) Myristoyl K (8) N for H (1), E for K (2)603,36 1 70,3704 124 128 (E)VPYPK(Y) V for M (1), Y for F (3)964,133 2 23,2323 138 154 (S)RSLTLTDVENLHLPLPL(L) Dehydration ST (2), Methyl CDEHKNRQ (9) R for Q (1)552,402 1 77,7778 150 154 (H)LPLPL(L)1081,66 1 63,1579 180 189 (S)LSQAKVLPIP(Q) Hydroxyl DKNP (5) A for S (4), I for V (9)553,366 1 70,3704 186 190 (V)LPVPQ(K)587,301 2 50,8772 192 201 (K)AVPYPQRDMP(I)603,36 1 70,3704 193 197 (A)VPYPQ(R)

kCN 633,411 1 70,3704 47 51 (Y)IPIQY(V)652,386 1 70,3704 77 81 (F)LPYPY(Y)815,476 1 63,6364 77 82 (F)LPYPYY(A)

β−LG 701,404 2 43,4783 140 151 (V)RTPEVDDEALEK(F)623,341 2 46,0317 141 151 (R)SPEVDDEALEK(F) Methyl N-TERM (N-TERM) S for T (1)623,341 2 46,0317 141 151 (R)TPEVDDEALEK(F)

5 min

30 min


hydrolysisProtein m/z charge ladder scostart end Sequenceαs1CN 997,6298 1 43,1373 23 31 (K)NQGLPQEVV(N) Methyl N-TERM (N-TERM) N for H (1), V for L (9)

810,0313 2 23,8095 37 47 (L)RFWIAPFPEVF(G) Myristoyl N-TERM (N-TERM) W for F (3), I for V (4)659,395 1 75,7576 40 45 (F)VAPFPE(V)560,3181 1 70,3704 41 45 (V)APFPE(V)806,4699 1 74,359 41 47 (V)APFPEVF(G)455,2588 3 39,6825 96 106 (H)IQKEDVPSERY(L)455,2811 3 36,5079 96 106 (H)IQKEDVPSEKY(L) Methyl CDEHKNRQ (9), Methyl C-TERM (C-TERM) K for R (10)1094,138 2 28,2828 118 134 (K)KYKVPQLEIVPNSAEER(L) Isobaric 116 (KY) (2), Acetyl K (3), Deamidation Q (6)1094,606 1 42,1053 125 134 (L)DIVPNSAEER(L) Pyrrolidone carboxylic acid N-TERM (N-TERM), Dehydration ST (6) D for E (1)547,7737 2 45,614 125 134 (L)DIVPNSAEER(L) Pyrrolidone carboxylic acid N-TERM (N-TERM), Dehydration ST (6) D for E (1)672,8778 2 23,1884 125 136 (L)DIVPNSAEERLH(S) Pyrrolidone carboxylic acid N-TERM (N-TERM), Dehydration ST (6) D for E (1)491,2724 2 31,3725 126 134 (E)IVPNAAEER(L) Pyrrolidone carboxylic acid N-TERM (N-TERM) A for S (5)548,8212 2 43,1373 126 134 (E)IVPSSAEER(L) SMA N-TERM (N-TERM), Dehydration ST (5) S for N (4)

αs2-CN 591,3587 1 70,3704 190 194 (F)ALPQY(L)β−CN 735,4044 3 37,6344 44 59 (K)KIKKFQSQEQQQTEDE(L) Myristoyl K (4) K for E (3), Q for E (8)

1022,718 2 21,5054 87 102 (P)QNIPPLTQTPVVVPPF(L) Palmitoyl CST (7), Methyl CDEHKNRQ (8)810,0305 2 31,0345 88 102 (Q)NIPPLTQTPVVVPPF(L)810,0645 2 45,3333 90 102 (I)PPLTQTPVVVPPF(L) Myristoyl N-TERM (N-TERM), Hydroxyl DKNP (2), Deamidation Q (5)753,0274 2 47,8261 91 102 (P)PLTQTPVVVPPF(L) Myristoyl N-TERM (N-TERM)773,459 1 64,1026 103 109 (F)LQPEVMG(V)552,4252 1 77,7778 150 154 (H)LPLPL(L)553,8874 2 47,3684 182 191 (S)QSKVLPVPQK(A) Deamidation Q (1), Dehydration ST (2)978,6829 1 77,7778 183 190 (Q)AKVLPVPQ(K) SMA N-TERM (N-TERM) A for S (1)586,6648 3 22,6667 189 201 (V)PQKAVPYPQRDMP(I) Carbamyl N-TERM (N-TERM), Lipoyl K (3)587,3187 2 50,8772 192 201 (K)AVPYPQRDMP(I)587,3229 2 57,8947 192 201 (K)AVPYPQRDLP(I) Methyl CDEHKNRQ (8), O18 (C-TERM) L for M (9)587,3704 2 61,4035 192 201 (K)AVPYPQRDLP(I) Methyl CDEHKNRQ (7), O18 (C-TERM) L for M (9)587,3697 2 57,8947 192 201 (K)AVPYPQRELP(I) O18 (C-TERM) E for D (8), L for M (9)595,3394 2 49,1228 192 201 (K)AVPYPQRDMP(I) Oxidation M (9)815,4808 1 57,5758 193 198 (A)IPYPRR(D) Methyl CDEHKNRQ (6) I for V (1), R for Q (5)815,4993 1 57,5758 193 198 (A)VPYPRR(D) Methyl N-TERM (N-TERM), Methyl CDEHKNRQ (6) R for Q (5)588,2441 2 33,3333 193 201 (A)IPYPQRDMP(I) Carbamyl N-TERM (N-TERM), Hydroxyl DKNP (2) I for V (1)

κ−CN 521,3264 2 41,1765 66 74 (Q)QKPVALIHN(Q) Hydroxyl DKNP (2), 13C L (6) H for N (8)815,4744 1 57,5758 77 82 (F)LPYPYY(A)997,6078 1 54,902 174 182 (V)IESPPKINT(V) Amidation C-TERM (C-TERM) K for E (6)773,4763 1 69,697 177 182 (S)PPEVST(V) Isobaric 114 (N-Term) (N-TERM) V for I (4), S for N (5)

αs1-CN 796,5188 1 63,6364 18 23 (P)RHPIKY(Q) Pyrrolidone carboxylic acid N-TERM (N-TERM) R for K (1), Y for H (6)806,4416 1 74,359 41 47 (V)APFPEVF(G)1163,344 2 18,018 110 128 (Y)LERLVRLKKYKVPQLEIVP(N) O18 (C-TERM) R for Q (3), V for L (5)1094,618 2 25,2525 118 134 (K)KYKVPQLEIVPNSAEER(L) Glycation N-TERM (N-TERM), Gamma-carboxyglutamic acid E (8), Dehydration ST (13)876,5716 1 56,4103 119 125 (K)YKVPQLE(I)1094,62 1 45,614 125 134 (L)DIVPNSAEER(L) Pyrrolidone carboxylic acid N-TERM (N-TERM), Dehydration ST (6) D for E (1)547,7897 2 45,614 125 134 (L)DIVPNSAEER(L) Pyrrolidone carboxylic acid N-TERM (N-TERM), Dehydration ST (6) D for E (1)672,8702 2 31,8841 125 136 (L)DIVPNSAEERLH(S) Pyrrolidone carboxylic acid N-TERM (N-TERM), Dehydration ST (6) D for E (1)491,271 2 27,451 126 134 (E)IVPNAAEER(L) Pyrrolidone carboxylic acid N-TERM (N-TERM) A for S (5)672,8778 2 23,8095 126 136 (E)IVPNSAEERLH(S) Phosphoryl STY (5)616,3289 2 33,3333 127 136 (I)VPNSAEERLH(S) Phosphoryl STY (4)

β−CN 692,3965 3 29,0323 43 58 (N)KKIEKWQNEEQQQTED(E) Methyl CDEHKNRQ (10) W for F (6), N for S (8)692,3965 3 29,0323 43 58 (N)KKIEKWQNEEQQQTED(E) Methyl CDEHKNRQ (9) W for F (6), N for S (8)692,3885 3 30,1075 43 58 (N)KKIEKWQSKEQQQTED(E) Acetyl K (5) W for F (6), K for E (9)735,391 3 24,2424 43 59 (N)KKVEKFQSEEQQQTEDE(L) Methyl CDEHKNRQ (4), Phosphoryl STY (8) V for I (3)735,3946 3 35,4839 44 59 (K)KIKKFQSEQQQQTEDE(L) Myristoyl K (4) K for E (3), Q for E (9)810,063 2 40 90 102 (I)PPLTQTPVVVPPF(L) Myristoyl N-TERM (N-TERM), Hydroxyl DKNP (2), Deamidation Q (5)753,036 2 42,029 91 102 (P)PLTQTPVVVPPF(L) Myristoyl N-TERM (N-TERM)680,9294 2 42,029 143 154 (L)TDVENLHLPLPL(L)680,9294 2 46,3768 143 154 (L)TDVKNLHLPLPL(L) Deamidation N (5) K for E (4)1073,652 1 33,3333 147 154 (E)NLYLPLPL(L) SMA N-TERM (N-TERM), O18 (C-TERM) Y for H (3)552,4128 1 77,7778 150 154 (H)LPLPL(L)553,8753 2 50,8772 182 191 (S)QSKVLPVPQK(A) Deamidation Q (1), Dehydration ST (2)659,4076 1 69,697 185 190 (K)VLPVPE(K) 13C L (2) E for Q (6)587,3004 2 45,614 192 201 (K)AVPYPQRDMP(I)587,37 2 61,4035 192 201 (K)AVPYPQRDLP(I) Methyl CDEHKNRQ (8), O18 (C-TERM) L for M (9)595,338 2 49,1228 192 201 (K)AVPYPQRDMP(I) Oxidation M (9)815,4838 1 57,5758 193 198 (A)IPYPRR(D) Methyl CDEHKNRQ (6) I for V (1), R for Q (5)

κ-CN 816,4927 2 20,2899 71 82 (A)LINNRFLPYPYY(A) Carbamyl N-TERM (N-TERM), Hydroxyl DKNP (4) R for Q (5)815,4702 1 57,5758 77 82 (F)LPYPYY(A)997,6108 1 58,8235 174 182 (V)IESPPKINT(V) Amidation C-TERM (C-TERM) K for E (6)

αs1-CN 747,9896 2 28 25 37 (Q)GLPQEVLNENLLR(F)747,9896 2 36 25 37 (Q)GLPQEVLNKNLLR(F) Deamidation N (8) K for E (9)485,8195 2 42,2222 30 37 (E)VLNENLLR(F)970,6812 1 53,3333 30 37 (E)VLNKNLLR(F) Deamidation N (3) K for E (4)806,463 1 69,2308 39 45 (F)FVAPFPE(V)659,4 1 75,7576 40 45 (F)VAPFPE(V)564,0057 3 31,0345 40 54 (F)VAPFPEVFGKEKVNK(L) Deamidation N (14) K for E (15)446,6179 3 42,8571 95 105 (K)HIQKEDVPSEK(Y) Methyl CDEHKNRQ (10), Methyl C-TERM (C-TERM) K for R (11)682,417 2 42,8571 96 106 (H)IQKEDVPNKRH(L) N for S (8), K for E (9), H for Y (11)626,3361 3 16,129 126 141 (E)IVPNSAEERLHSMKEG(I) Phosphoryl STY (5)626,6832 3 16,129 126 141 (E)IVPNSAEERLHSMKEG(I) Deamidation N (4), Phosphoryl STY (5)549,8738 2 46,6667 160 167 (Y)FYPKLFKR(F) K for E (4), K for R (7), R for Q (8)550,303 2 37,7778 160 167 (Y)FYPELFRQ(F)550,3151 2 55,5556 160 167 (Y)FYPELFKR(F) K for R (7), R for Q (8)

αs2-CN 738,4523 1 75,7576 189 194 (K)FALPQY(L)β−CN 773,4542 1 53,8462 103 109 (F)LQPEVMG(V)

425,2708 3 47,0588 122 130 (H)RELPFPKYP(V) SMA N-TERM (N-TERM) R for K (1), L for M (3)737,4735 2 33,3333 142 154 (T)LTDVENLHLPLPL(L)737,4735 2 34,6667 142 154 (T)LTDVKNLHLPLPL(L) Deamidation N (6) K for E (5)441,6148 3 27,5362 180 191 (S)LSQSKVLPVPQK(A) Deamidation Q (3), Dehydration ST (4), Hydroxyl DKNP (5)662,4345 2 44,9275 180 191 (S)LSQSKVLPVPQK(A)442,2916 3 27,5362 180 191 (S)MSQSKVLPVPQK(A) Pyrrolidone carboxylic acid N-TERM (N-TERM) M for L (1)442,2931 3 33,3333 180 191 (S)LSQSEVLPVPQK(A) E for K (5)587,3143 2 50,8772 192 201 (K)AVPYPQRDMP(I)587,3456 2 52,6316 192 201 (K)AVPYPQRDLP(I) Methyl CDEHKNRQ (8), O18 (C-TERM) L for M (9)587,3779 2 35,0877 192 201 (K)AVPYPRRDVP(I) O18 (C-TERM) R for Q (6), V for M (9)

κ-CN 521,3292 2 47,0588 66 74 (Q)QKPVSLINH(Q) 13C L (6) S for A (5), H for N (9)508,3095 2 50,8772 99 108 (Q)VLSNTVPAKS(C)508,8376 2 43,8596 99 108 (Q)ILSSTVPAKS(C) Methyl N-TERM (N-TERM) I for V (1), S for N (4)

β−LG 990,6786 1 56,8627 17 25 (A)LIVTQTLKG(L) Methyl CDEHKNRQ (8), O18 (C-TERM) L for M (7)485,806 2 49,0196 48 56 (L)LDAQSAPLR(V)

60min

240min

360min

Modification


4. CONCLUSION

A large panel of milk hydrolysates were made with the use of food grade enzymes commonly employed by the food industry. Different methods that are available for the detection of food allergens were tested to assess their performance towards milk hydrolysates. The immunological methods ELISA, dot blot and Western blot showed strong limitations in their capacity to detect milk-derived peptides. After hydrolysis the detection of immunoreactive peptides assessed with those techniques was clearly reduced while ultrafiltration completely abolished the detection. This confirmed the need of alternative methods. Capillary electrophoresis appears to be a promising technique for the detection of peptides. In addition this technique gives the possibility to identify the sequence of the peptides when CE is coupled to MS detection. We have shown that CE indeed allowed the detection of milk derived peptides after extended hydrolysis and after ultrafiltration of the hydrolysates. Furthermore, it was possible to detect and identify the peptide sequences of such hydrolysates by means of mass spectrometry (with the ESI-Q-Tof) which confirms the potential of CE-MS compared to the commonly used immunological methodologies. The next step will be to optimise the interface of the capillary electrophoresis-mass spectrometry to further develop the methodology aimed at a detection of milk-derived peptides in food matrices. A proposition for such a project was submitted and accepted by the scientific committee and will be performed in 2008.

ACKNOWLEDGEMENTS

We are grateful to Marcel Brohée for supports with the ELISA analyses and Hubert Chassaigne and Jorgen Nørgaard for analysis with the nano ESI-Q-Tof.


REFERENCES

1. Sicherer, S.H. and Sampson, H.A., 9. Food allergy., J. Allergy Clin. Immunol., 117, (2, Supplement 2), S470, 2006.

2. Sampson, H.A., Update on food allergy., J. Allergy Clin. Immunol., 113, (5), 805, 2004. 3. Barnig, C., et al., Allergy to cow milk proteins without accompanying allergy to sheep

milk proteins in an adult, Rev. Fr. Allergol. , 45, (8), 608, 2005. 4. Restani, P., et al., Use of immunoblotting and monoclonal antibodies to evaluate the

residual antigenic activity of milk protein hydrolysed formulae., Clin. Exp. Allergy., 26, (10), 1182, 1996.

5. Villadoniga, C., et al., Monitoring immunoreactivity reduction of whey proteins hydrolysates by latex agglutination, Enzyme Microb. Technol., 40, (3), 481, 2007.

6. Sinha, R., et al., Whey protein hydrolysate: Functional properties, nutritional quality and utilization in beverage formulation., Food Chem., 101, (4), 1484, 2007.

7. Korhonen, H. and Pihlanto, A., Bioactive peptides: Production and functionality., Int. Dairy J., 16, (9), 945, 2006.

8. Hernandez-Ledesma, B., et al., Identification of bioactive peptides after digestion of human milk and infant formula with pepsin and pancreatin., Int. Dairy J., 17, (1), 42, 2007.

9. Chirico, G., et al., Immunogenicity and antigenicity of a partially hydrolyzed cow's milk infant formula., Allergy., 52, (1), 82, 1997.

10. Bruel, H., et al., L'allergie neonatale aux hydrolysats de proteines de lait de vache : y penser aussi chez le premature., Rev. Fr. Allergol., 41, (5), 510, 2001.

11. Kyprianou, M., Commission directive 2007/68/EC, Official Journal of the European Union, (11), 11, 2007.

12. Adler-Nissen, J., Determination of degree of hydrolysis of food protein hydrolysates by trinitrobenzenesulfonic acid., J. Agric. Food Chem., 27, (6), 1256, 1979.


ANNEXES

Annex 1: Composition of milk powders. Spray dried Na-CN WPC

Emulsifier, stabiliser, whipping agent and protein enricher in liquid dietetic formulae, health food products various dairy products and other spray dried emulsions. Excellent emulsifying and stabilizing properties.

Native, soluble Made from fresh sweet whey, Manufactured by ultrafiltration and spray drying. High protein content, balanced amino spectrum, is ideal for sport drink mixes and nutraceutical applications. Functional properties (water binding, emulsification, viscosity, gelation) used in all kinds of bakery, ice cream and meat processing applications.

physical and organoleptic Aspect: Free flowing, low density white powder

Odour: Milky Taste: Neutral, bland Bland, milky Chemical Protein .(on DS) moisture Ash & minerals Fat Carbohydrate pH (10 % dispersion 20° C)

90% 5% 4% 0.8% 0.2% (lactose) 6.8

min 75 % 5 % 3 % 6 % 6 % 6.4

Nutritional energy value 1609 kJ/100 g Microbiological standard plate count 100/g max. 50 000/g

yeasts & moulds <10/g < 50/g Coliforms < 10/g Staphylococcus aureus neg. in 1 g neg. in 1 g Salmonella neg. in 50g neg. in 25g mineral content (mg/100 g product) Ca Mg K Na Cl p

100mg 5 15 1.45g 100mg 0.74g

395 65 665 220 85 285

Amino Acid Spectrum Essential Amino Acids Thr Val Met Ile Leu Phe Lys Trp Semi Essentials Asp Ser Glu Pro Gly Ala Cys Tyr His Arg

g/16gN 4.6 7.4 3.0 5.8 10.1 5.4 8.3 1.4 7.3 6.3 22.3 10.5 1.9 3.1 0.4 5.8 3.2 3.8

(g/100 g protein) 7 5,7 1,7 6,4 10,3 3,10 8,7 2,4 10,5 4,8 17,6 5,9 1,8 4,9 2,3 2,9 1,7 2,3


Annex 2: Characteristics of the commercial ELISA kits. ELISA kits Veratox®

Total milk allergen quantitative test

Biokits Casein Assay kit

Biokits �-LG Assay kit

target Total milk Casein (CN)

Beta-Lactoglobulin (�-LG)

supplier Neogen Tepnel

detection of

Bovine CN/caseinates Bovine �-LG

Use quantitative analysis of food products (juices, cake mixes,

cookies, sauces and sorbets) for the presence of milk proteins CN

and whey at very low concentrations (ppm) in uncooked and cooked foods

Type sandwich ELISA indirect competitive ELISA Range of

quantitation limit of

quantitation

2.5-25 ppm 1.6 to > 25 ppm extracted and diluted sample (1/100 in total) is between 1.6-25.6 ppm or 2-32

ppm milk protein and 8-128 ppm milk powder

2.5-40 ppm �-LG (50-75 and 800-1200 ppm

milk powder)

Detection Limit

1 ppm < 2 ppm < 2 ppm

Specificity CN and WP CN �-LG

Reading 650 nm 450 nm


Annex 3: Calibration curve from the Leucine standard

Calibration curve of TNBS determination

0

0,2

0,4

0,6

0,8

1

1,2

0 2E-05 4E-05 6E-05 8E-05 0,0001 0,0001 0,0001Leucine equivalent Concentration

Abso

rban

ce a

t 340

nm


Annex 4: A: Electrophoresis of Na-CN hydrolysed with protease from B. amyloliquefaciens (CA), protease from A. orizae (CO), the combination of both proteases (CA/O), trypsin (CT), pancreatin (CP) and bromelain (CB). B: western blots of the gels shown in A in which CN proteins were detected by α-CN antibodies.

CTMW 5’ 20’ 40’ 60’ 5h3ht0

1,063,496,5

17

26,6

14.2

20

30

90

CBCP

1,063,496,5

17

26,6

14.2

20

30

90

MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,496,5

17

26,6

14.2

20

30

90

MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

CTMW 5’ 20’ 40’ 60’ 5h3ht0

1,063,496,5

17

26,6

14.2

20

30

90

CTMW 5’ 20’ 40’ 60’ 5h3ht0

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

CBCP

1,063,496,5

17

26,6

14.2

20

30

90

MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,496,5

17

26,6

14.2

20

30

90

MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

CBCP

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

MW 5’ 20’ 40’ 60’ 5h3ht0MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,496,5

17

26,6

14.2

20

30

90

MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

COCA CAOMW 5’ 20’ 40’ 60’ 5h3ht0

1,063,496,5

17

26,6

14.2

20

3090

1,063,496,5

17

26,6

14.2

20

3090

MW 5’ 20’ 40’ 60’ 5h3ht0MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

COCA CAOMW 5’ 20’ 40’ 60’ 5h3ht0

1,063,496,5

17

26,6

14.2

20

3090

1,063,496,5

17

26,6

14.2

20

3090

MW 5’ 20’ 40’ 60’ 5h3ht0MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

CAOMW 5’ 20’ 40’ 60’ 5h3ht0MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,496,5

17

26,6

14.2

20

3090

1,063,496,5

17

26,6

14.2

20

3090

1,063,496,5

17

26,6

14.2

20

3090

1,063,496,5

17

26,6

14.2

20

3090

MW 5’ 20’ 40’ 60’ 5h3ht0MW 5’ 20’ 40’ 60’ 5h3ht0MW 5’ 20’ 40’ 60’ 5h3ht0MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

A

B

A

B


Annex 5: A: Electrophoresis of WPC hydrolysed with protease from B. amyloliquefaciens (WA), protease from A. orizae (WO), the combination of both proteases (WA/O), trypsin (WT), bromelain (WB) and pancreatin (WP). B: Western blots of the gels shown in A in which whey proteins were detected by β-LG and α-LA antibodies.

MW 5’ 20’ 40’ 60’ 5h3h

WO

t0

1,063,496,5

17

26,6

14.2

20

30

90

MW

t0

WAO

MW 5’ 20’ 40’ 60’ 5h3h

1,063,496,5

17

26,6

14.2

20

30

90

WA

t0MW 5’ 20’ 40’ 60’ 5h3h

1,063,496,5

17

26,6

14.2

20

30

90

anti-β-LG anti-α-LAt0MW 5’ 20’ 40’ 60’ 5h3h t0MW 5’ 20’ 40’ 60’ 5h3h

t0MW 5’ 20’ 40’ 60’ 5h3ht0MW 5’ 20’ 40’ 60’ 5h3h

t0MW 5’ 20’ 40’ 60’ 5h3h t0MW 5’ 20’ 40’ 60’ 5h3h

Electrophoresis

MW 5’ 20’ 40’ 60’ 5h3h

WO

t0

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

MW

t0

WAO

MW 5’ 20’ 40’ 60’ 5h3h

1,063,496,5

17

26,6

14.2

20

30

90

MW 5’ 20’ 40’ 60’ 5h3h

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

WA

t0MW 5’ 20’ 40’ 60’ 5h3ht0MW 5’ 20’ 40’ 60’ 5h3h

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

anti-β-LG anti-α-LAt0MW 5’ 20’ 40’ 60’ 5h3ht0MW 5’ 20’ 40’ 60’ 5h3h t0MW 5’ 20’ 40’ 60’ 5h3ht0MW 5’ 20’ 40’ 60’ 5h3h

t0MW 5’ 20’ 40’ 60’ 5h3ht0MW 5’ 20’ 40’ 60’ 5h3ht0MW 5’ 20’ 40’ 60’ 5h3ht0MW 5’ 20’ 40’ 60’ 5h3h

t0MW 5’ 20’ 40’ 60’ 5h3ht0MW 5’ 20’ 40’ 60’ 5h3h t0MW 5’ 20’ 40’ 60’ 5h3ht0MW 5’ 20’ 40’ 60’ 5h3h

Electrophoresis


1,063,496,5

17

26,6

14.2

20

30

90

t0MW 5’ 20’ 40’ 60’ 5h3h

WP

t0MW 5’ 20’ 40’ 60’ 5h3h

1,063,496,5

17

26,6

14.2

20

30

90

WB

t0MW 5’ 20’ 40’ 60’ 5h3h

1,063,496,5

17

26,6

14.2

20

30

90

WT

t0MW 5’ 20’ 40’ 60’ 5h3h t0MW 5’ 20’ 40’ 60’ 5h3h

t0MW 5’ 20’ 40’ 60’ 5h3h t0MW 5’ 20’ 40’ 60’ 5h3h

t0MW 5’ 20’ 40’ 60’ 5h3h t0MW 5’ 20’ 40’ 60’ 5h3h

anti-β-LG anti-α-LAElectrophoresis

1,063,496,5

17

26,6

14.2

20

30

90

t0MW 5’ 20’ 40’ 60’ 5h3h

WP

t0MW 5’ 20’ 40’ 60’ 5h3h

1,063,496,5

17

26,6

14.2

20

30

90

WB

t0MW 5’ 20’ 40’ 60’ 5h3h

1,063,496,5

17

26,6

14.2

20

30

90

WT

t0MW 5’ 20’ 40’ 60’ 5h3h t0MW 5’ 20’ 40’ 60’ 5h3h

t0MW 5’ 20’ 40’ 60’ 5h3h t0MW 5’ 20’ 40’ 60’ 5h3h

t0MW 5’ 20’ 40’ 60’ 5h3h t0MW 5’ 20’ 40’ 60’ 5h3h

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

t0MW 5’ 20’ 40’ 60’ 5h3h

WP

t0MW 5’ 20’ 40’ 60’ 5h3ht0MW 5’ 20’ 40’ 60’ 5h3h

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

WB

t0MW 5’ 20’ 40’ 60’ 5h3h

1,063,496,5

17

26,6

14.2

20

30

90

t0MW 5’ 20’ 40’ 60’ 5h3ht0MW 5’ 20’ 40’ 60’ 5h3h

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

WT

t0MW 5’ 20’ 40’ 60’ 5h3h t0MW 5’ 20’ 40’ 60’ 5h3h

t0MW 5’ 20’ 40’ 60’ 5h3h t0MW 5’ 20’ 40’ 60’ 5h3h

t0MW 5’ 20’ 40’ 60’ 5h3h t0MW 5’ 20’ 40’ 60’ 5h3h



Annex 6: A: Electrophoresis of milk hydrolysed with protease from B. amyloliquefaciens (MA), protease from A. orizae (MO), the combination of both protases (MA/O), trypsin (MT), bromelain (MB) and pancreatin. B: Western blots of the gels shown in A in which milk proteins were detected by β-LG and α-LA antibodies.

MA

MO

MAO

MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,496,5

17

26,6

14.2

20

30

90

MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,496,5

17

26,6

14.2

20

30

90

MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,496,5

17

26,6

14.2

20

30

90

MW 5’ 20’ 40’ 60’ 5h3ht0 MW 5’ 20’ 40’ 60’ 5h3ht0

MW 5’ 20’ 40’ 60’ 5h3ht0 MW 5’ 20’ 40’ 60’ 5h3ht0

MW 5’ 20’ 40’ 60’ 5h3ht0 MW 5’ 20’ 40’ 60’ 5h3ht0

Electrophoresis Anti-β-LG Anti-α-LG

MA

MO

MAO

MW 5’ 20’ 40’ 60’ 5h3ht0MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,496,5

17

26,6

14.2

20

30

90

MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

MW 5’ 20’ 40’ 60’ 5h3ht0MW 5’ 20’ 40’ 60’ 5h3ht0 MW 5’ 20’ 40’ 60’ 5h3ht0MW 5’ 20’ 40’ 60’ 5h3ht0



Electrophoresis Anti-β-LG Anti-α-LG


MT

MP

MB

MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,496,5

17

26,6

14.2

20

30

90

MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,46,5

17

26,6

14.2

20

30

90

MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,46,5

17

26,6

14.2

20

30

90

MW 5’ 20’ 40’ 60’ 5h3ht0 MW 5’ 20’ 40’ 60’ 5h3ht0

MW 5’ 20’ 40’ 60’ 5h3ht0 MW 5’ 20’ 40’ 60’ 5h3ht0

MW 5’ 20’ 40’

60’ 5h3ht0 MW 5’ 20’ 40’ 60’ 5h3ht0


MT

MP

MB

MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,496,5

17

26,6

14.2

20

30

90

MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,46,5

17

26,6

14.2

20

30

90

MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,46,5

17

26,6

14.2

20

30

90

MW 5’ 20’ 40’ 60’ 5h3ht0 MW 5’ 20’ 40’ 60’ 5h3ht0

MW 5’ 20’ 40’ 60’ 5h3ht0 MW 5’ 20’ 40’ 60’ 5h3ht0

MW 5’ 20’ 40’

60’ 5h3ht0 MW 5’ 20’ 40’ 60’ 5h3ht0


MB

MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,496,5

17

26,6

14.2

20

30

90

MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,496,5

17

26,6

14.2

20

30

90

1,063,496,5

17

26,6

14.2

20

30

90

MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,46,5

17

26,6

14.2

20

30

90

MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,46,5

17

26,6

14.2

20

30

90

1,063,46,5

17

26,6

14.2

20

30

90

MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,46,5

17

26,6

14.2

20

30

90

MW 5’ 20’ 40’ 60’ 5h3ht0

1,063,46,5

17

26,6

14.2

20

30

90

1,063,46,5

17

26,6

14.2

20

30

90



MW 5’ 20’ 40’

60’ 5h3ht0MW 5’ 20’ 40’

60’ 5h3ht0 MW 5’ 20’ 40’ 60’ 5h3ht0MW 5’ 20’ 40’ 60’ 5h3ht0



Annex 7: 2D-DIGE electrophoresis protocol 1. Sample Labelling. An aliquot of each sample (milk solution and milk hydrolysed for 30 minutes) corresponding to 40 µg proteins was evaporated to dryness. The samples were then resuspended in 2 µl (for milk hydrolysate) and 4 µl (for milk solution) of labelling buffer (pH 8.9) (30 mM Tris, 7 M urea, 2 M Thiourea, 4 % (w/v) CHAPS adjusted to pH 8.9 with HCl). The samples were subsequently labelled with 1 µl 5 times diluted CyDye either Cy5 (milk) or Cy3 (milk hydrolysate) for 30 minutes on ice in the dark. The labelling was stopped with 1 µl of 10 mM Lysine and the samples were incubated for another 10 minutes. 2. First dimension: IEF All solutions prepared were made without staining marker (Bromophenol blue) to avoid interference with peptide migration. To 5 µl of each labelled sample 5 µl of sample buffer (2X) was added and samples were mixed. Rehydratation buffer (up to 250 µl) was added to the mixture before distributing 125 µl in 2 different IPG strip cassettes. The 7 cm IPG strip gels were placed in the cassette before the addition of 160 µl of dry cover to avoid evaporation. Sample preparation Solution Reagent Quantity Final Concentration Urea (MW 60.06) 12 g 8 M CHAPS (MW 614.89) 1 g 4 % (w/v) Pharmalyte broad range pH 3-10 500 µl 2 % (w/v) DTT (MW154.2) 154 mg 40 mM Deionised water Complete 25 ml Urea Rehydratation stock Solution Reagent Quantity Final Concentration Urea (MW 60.06) 12 g 8 M CHAPS (MW 614.89) 0.5 g 2 % (w/v) Pharmalyte broad range pH 3-10 125 µl 0.5 %(w/v) Deionised water Complete 25 ml DTT (MW154.2) 7 mg for 2.5 ml aliquot IEF separation was performed according to the program below

Step and voltage mode Voltage (V)

Step duration (h:min)

Volt-hours (KVh)

Rehydratation - 12:00 - 1 Step and hold 300 00:30 0.2

2 Gradient 1000 0:30 0.3 3 Gradient 5000 1:20 4 Separation

4 Step and hold 5000 0:06-0:25 0:5-2:00 3. Second dimension: electrophoresis SDS Page After IEF, the strips were equilibrated 15 minutes in equilibration buffer (diluted sample buffer 4 X NuPAGE® LDS Sample Buffer consisting of 106 mM Tris HCl, 141 mM Tris base, 2 % LDS, 10 % glycerol, 0.51 mM EDTA to which 50 mM dithiothreitol was extemporaly added) The equilibrated 7 cm IPG gel strip was embedded at the top of a pre-cast NuPAGE Bis-Tris SDS-PAGE 12 % mini-gel (Invitrogen). Agarose solution (0.5 %) was added on the top of the IPG strip and the molecular weight marker was loaded in the marker well.


Electrophoresis was performed at 150 V in NuPAGE MES SDS running buffer (2.5 mM MES, 2.5 mM Tris Base, 0.005 % SDS, 0.05 mM EDTA, pH 7.3) until the front of the fluorescent dye arrived at the bottom of the gel . After electrophoresis, the gels were removed from the cassettes and scanned with the Typhoon 9400 scanner system at 50 μm resolution at the excitation excitation/emission wavelength specific for Cy5 and Cy3.

A N N E X E S

ANNEX 1: Guidelines and forms: applications for new projects

Call for proposals Exploratory Research 2007

Guidelines Layout • A proposal should be submitted before 17:00 September 15 th, 2006 using the attached application form

“Call for proposals - Exploratory research 2007”. Proposals submitted after this deadline will not be

considered.

• A proposal should contain a maximum of five pages (approval page not included).

• A proposal should be submitted both in an electronic form to the secretariat of the Scientific Committee

([email protected]) and as a signed paper copy by internal post to Guy Bordin.

A proposal should contain the following information:

1. Applicant details (including name of project co-ordinator)

2. Title of project

3. Current state-of-the-art

4. Rationale1

5. Objectives2

6. Scientific novelty of the project

7. Why should the research be carried out as exploratory research and not in the framework institutional

work?

8. Why should the JRC and in particular the IRMM carry out the project?

9. Work to be carried out, research methods/techniques, and list of expected deliverables (publications,

procedures, software, patents, etc).

10. Brief description of the scientific background of the team members and a list of three relevant

publications.

1 The rationale should be introduced e.g. as follows: "there is a need for...", "there is a problem with...", "European legislation requires that...", etc. 2 The objectives should therefore be presented e.g. as follows: "as a consequence of the rationale, the objectives are: to develop..., to produce..., to provide...," etc.

11. Name of institutional action to which the research proposal is linked and a brief description of the nature

of the link

12. Possible follow-up (e.g. institutional, competitive projects)

13. Resources: specific credits and person months. Specific credits should be fully justified.

14. Signature of unit head(s) (only for paper copy).

Guidance

• There should be a clear element of scientific research in the proposal; state-of-the-art studies are not

eligible.

• Furthermore an ER proposal should not immediately be interchangeable with an institutional project.

• It should allow the scientific risk inherent to all fundamental research.

• The proposal should clearly display the novelty components.

• The call is open to all IRMM scientific members of staff.

• Feasibility is a requirement (appropriate allocation of time, budget, staff)

• The criteria for selection are as follows (weighting factors are given in brackets):

1. Relevance to Institute's scientific activities and the JRC mission (0.1) 2. Scientific novelty (including new approaches) of the proposed research (0.4) 3. Quality of research plan (including in particular the adequacy of methods/techniques, the

resources (human and budgetary) and the time schedule). Proposals involving the use of equipment of different units should clearly state a user planning (0.3)

4. Contribution to integrate resources (e.g. trans-units projects, trans-institutes projects) and networking (0.2)

• The selection procedure will be performed as follows:

1) Evaluation of the written proposals by the IRMM Scientific Committee,

2) Auditions of the candidates by the IRMM Scientific Committee and

3) Final evaluation and selection of the proposals based on written proposals and auditions.

• For ER 2007 projects, the schedule will be as follows:

o Launch of call: 1st June 2006 o Deadline for submission of written proposals: 15th September 2006 o Auditions of all applicants: 2nd October 2006 o Final selection meeting of the SC: 3rd October 2006 o Deadline for the communication of the list of selected proposals: 6th October 2006

• The work should be carried out at IRMM, with existing major equipments.

• Each project should clearly identify a project co-ordinator. The project co-ordinator is responsible for the

smooth running of the project. He/she should therefore be working at IRMM during the duration of the

whole project.

• Joint proposals between IRMM units are strongly encouraged.

• The proposal should only cover work to be carried out from January to December 2007.

• The selected applicants will be invited to present their results during an IRMM workshop organised

during the first quarter of 2008.

• The selected applicants should also submit a final report of their research in the course of the second

quarter of 2008.

Resources The JRC can spend up to 6% of its budget on Exploratory research. For IRMM, this means a total of 10-12

person years and about 300 000 euros in specific credits. A typical project could therefore include about 1-3

person year with an “accompanying” amount of specific credits of up to 50 000 euros. These additional

credits will be specifically reserved for each action involved.

Call for proposals

Exploratory Research 2007

Application form

Project number: ER/2007/

To be sent to the secretariat of the SC before September 15th 2006 1. Applicant(s) details

Name(s): Name of project co-ordinator: Unit(s): 2. Title of the project

3. Current state-of-the-art

4. Rationale

5. Objectives

6. Scientific novelty of the project

7. Why should the research be carried out as exploratory research and not in the framework

institutional work? 8. Why should the JRC and in particular the IRMM carry out the project?

9. Work to be carried out, research methods/techniques, and list of expected deliverables (publications, procedures, software, patents, etc).

10. Brief description of the scientific background of the team members and a list of three relevant

publications

11. Name of institutional action to which research proposal is linked and a brief description of the nature of the link

12. Possible follow-up (e.g. competitive projects)

13. Resources: specific credits and staff allocation

13.a. specific credits Specify costs and allocate credits to the relevant action(s).

13.b. staff * allocation in person months (* project co-ordinator to be working at IRMM during 2007)

14. Approval of unit head(s)

Name: Date: Signature:

ANNEX 2: GUIDELINES AND FORMS: APPLICATIONS FOR PROLONGATION OF PREVIOUS PROJECTS

Call for prolongation of previous projects

Exploratory Research 2007 Guidelines

Layout • A proposal should be submitted before 17:00 September 15th, 2006 using the attached application form

“Call for prolongation of previous projects - Exploratory research 2007”. Proposals submitted after this

deadline will not be considered.

• A proposal should contain a maximum of five pages (approval page not included).

• A proposal should be submitted both in an electronic form to the secretariat of the Scientific Committee

([email protected]) and in a signed paper copy by internal post to Guy Bordin.

A proposal should contain the following information:

1. Applicant details (including name of project co-ordinator)

2. Title of project (should be different from that of the initial project)

3. Summary of the outcome and deliverables of the initial project

4. Objectives of the prolongation (including scientific novelty)

5. Why should the research still be carried out as exploratory research and not in other frameworks (e.g.

institutional work, competitive actions)?

6. Work to be carried out, research methods/techniques, and list of expected deliverables (publications,

procedures, software, patents, etc).

7. Name of institutional action to which the research proposal is linked

8. Possible follow-up (e.g. institutional, competitive projects)

9. Resources: specific credits and person months. Specific credits should be fully justified.

10. Signature of the unit head(s).

Guidance

• There should be a clear scientific justification in the application for the prolongation.

• “Application for the prolongation of a previous exploratory research project” does not mean “extension

of time to finish a previous project” with the same working plan. It means looking for further exploratory

developments, with further objectives and a new research plan.

• The call is open to IRMM scientific staff members who were laureates of the previous ER call.

• Feasibility is a requirement (appropriate allocation of time, budget, staff).

• The criteria for selection are as follows (weighting factors are given in brackets):

1. Justification for the prolongation in the frame of ER (0.25) 2. New objectives and scientific novelty (0.3) 3. Quality of research plan (including in particular the adequacy of the methods/techniques, the

resources (human and budgetary) and the time schedule). Proposals involving the use of equipment of different units should clearly state a user planning (0.3)

4. Contribution to integrate resources (e. g. trans-units projects, trans-institute projects) and networking (0.15)

• The selection procedure will be performed as follows:

1) Evaluation of the written proposals by the IRMM Scientific Committee,

2) auditions of the candidates by the IRMM Scientific Committee and

3) final evaluation and selection of the proposals based on the written proposals and auditions.

• For ER 2006 projects, the schedule will be as follows:

o Launch of call: 1st June 2006 o Deadline for submission of written proposals: 15th September 2006 o Auditions of all applicants: 2nd October 2006 o Final selection meeting of the SC: 3rd October 2006 o Deadline for the communication of the list of selected proposals: 6th October 2006

• The work shouldbe carried out at IRMM, with existing major equipement.

• Each project should clearly identify a project co-ordinator. The project co-ordinator is responsible for the

smooth running of the project. He/she should therefore be working at IRMM during the duration of the

whole project.

• Joint proposals between IRMM units are strongly encouraged.

• The proposal should only cover work to be carried out from January to December 2007.

• The selected applicants will be invited to present their results during an IRMM workshop organised

during the first quarter of 2008.

• The selected applicants should also submit a final report of their research in the course of the second

quarter of 2008.

Resources The JRC can spend up to 6% of its budget in Exploratory research. For IRMM, this means a total of 10-12

person years and about 300 000 euros in specific credits. A typical project could therefore include 1-3 person

year with an “accompanying” amount of specific credits up to 50 000 euros. These additional credits will be

specifically reserved for each action involved.

Call for prolongation of previous projects Exploratory Research 2007

Application form

Project number: ER/2007/

To be sent to the secretariat of the SC before September 15th 2006

1. Applicant(s) details

Name(s): Name of project co-ordinator: Unit(s): 2. Title of project (should be different from that of the initial project)

3. Summary of the outcome and deliverables of the initial project

4. Objectives of the prolongation (including scientific novelty)

5. Why should the research still be carried out as exploratory research and not in other frameworks (institutional work, competitive actions) ?

6. Work to be carried out, research methods/techniques, and list of expected deliverables (publications, procedures, software, patents, etc). 7. Name of institutional action to which the research proposal is linked

8. Possible follow-up (e.g. competitive projects)

9. Resources: specific credits and staff allocation 9a. specific credits

Specify costs and allocate credits to the relevant action(s).

9b. staff * allocation in person months (*project co-ordinator to be working at IRMM during 2007)

10. Approval of unit head(s) Name: Date: Signature:

ANNEX 3: SELECTED PROJECTS FOR THE YEAR 2007 Project Resources

Title Applicant(s) Persons (years)

Credits (KEuros)

Action

Production of uranium particle reference materials

R. Kips, R. Wellum,

Y. Aregbe

1.08 21 53102

A neutron source in the energy range between 8 and 14 MeV for Van de Graaff accelerators

G. Giorginis, V. Khryachkov, F.-J.

Hambsch, S. Oberstedt, N. Kornilov, G.

Lövestam

1.67 50 51401

Screening of existing trichothecene reference materials for the occurrence of masked (conjugated) mycotoxins

G. Buttinger, M. Eskola

0.50 21 33003

Measurement of neutron activation cross section curves using moderated neutron fields (NAXSUN) (PROLONGATION)

G. Lövestam, M. Hult,

P. Lindahl, S. Oberstedt,

V. Semkova

0.63 14 51401 51603

C6D6-EXTENDED : The use of a high efficiency array of C6D6 detectors for absolute capture cross section measurements in the thermal and epi-thermal energy region.

A. Borella, J. Gonzalez,

F. Gunsing, A. Plompen,

C. Sage, P. Schillebeeckx,

P. Siegler

0.38 35 51402

Quantification in GMO Certified Reference Materials (CRMs): towards a new approach for PCR performance quality control of DNA extracts

W. Broothaerts, P. Corbisier, S. Trapmann

1.00 50 15012

Metal solid phase extraction from natural, saline and waste waters using TiO2 nano-particles: method development

C. Quétel, I. Petrov,

E. Vassileva

0.50 12 22005

Investigation of possibilities to quantify allergenic proteins, in particular major peanut allergens in the presence of natural enzyme inhibitors.*

A. Muñoz-Piñeiro, R. Kral,

M. Dabrio, A. Van Hengel

0.88 50 15012

High temperature liquid chromatographic analysis of PAHs in foods

S. Szilagyi, L. Hollosi,

T. Wenzl

0.75 21 33004

Detection of allergenic peptides derived from milk hydrolysates by proteomic and immunochemical approaches.

V. Tregoat, L. Monaci,

A. Van Hengel

1.50 50 33004

* The report on the “” project was done during the 2008 exercise

European Commission EUR 24072 EN – Joint Research Centre – Institute for Reference Materials and Measurements Title: Exploratory Research at IRMM 2007 – Final Report Author(s): Compiled by the IRMM Scientific Committee Luxembourg: Office for Official Publications of the European Communities 2009 – 256 pp. – 21.0 x 29.7 cm EUR – Scientific and Technical Research series – ISSN 1018-5593 ISBN 978-92-79-13939-0 DOI 10.2787/1885

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