2Laser spectrometry: Technique

and apparatus

Chapter 2

24

Set-up

25

2. Laser spectrometry: Technique and

apparatusThis chapter will give an extensive description of the principles and present set-up for

measuring the stable isotopes in water by means of laser spectrometry (LS). It is partly based on

previously published material (Kerstel 1999, Van Trigt 2001a, Kerstel 2001b). In Chapter 6 some

future developments of the apparatus as well as the method will be described.

2.1 Measurement principle

The newly developed method for measuring stable isotopes in water is based on direct

absorption laser spectrometry (LS). For most relatively small molecules the room-temperature, low

pressure, gas phase, infrared spectra reveal absorptions due to individual ro-vibrational transitions

(“lines”) that can each be uniquely assigned to one of the various isotopic species present. The

absorption intensities of the isotopomer lines, relative to that of a line belonging to the most

abundant isotopic species, can be used to calculate the relative isotope abundance ratio of interest.

The measurement of the absorption intensity profiles is done by recording the attenuation of a laser

beam with narrow spectral line width as a function of its wavelength.

2.1.1 Infrared spectrum of water

An extended section of the IR absorption spectrum of water is depicted in Figure 2.1.

Thousands of lines are plotted here; all four of the isotopomers of interest (i.e., 1H16O1H, 1H17O1H,1H18O1H, and 2H16O1H) are included in the figure. Their relative intensities are based on their

abundances in natural water.

The first challenge in the process of developing the desired laser spectrometric measurement

method is to identify a section in this range in which all of the isotopomers of interest have

transitions that are:

(1) of comparable intensities (thus a weak absorption line for the most abundant 1H1H16O, relative to

the absorption strengths of the other isotopomers)

(2) within a small spectral range (to make fast continuous scans possible) and

(3) without interference from other strong lines.

The second challenge is to find a reliable light source that is continuously tunable in the

selected section of the absorption spectrum.

Chapter 2

26

Figure 2.1: Overview of the high resolution near- and mid-IR H2O absorption spectrum for gaseous

natural water, in the range from 1 µm to 8 µm (10000 cm-1 to 1250 cm-1). All four of the

isotopomers of interest are included. The arrow shows the LS wavelength of about

2.7 µm (3664 cm–1).

An excellent section that satisfies all of these demands has been found from 3664.00 cm-1 to

3662.80 cm-1 (2.7293 µm to 2.7302 µm) and is shown in Figure 2.2. The most important lines in this

section are listed in Table 2.1. Note that this is an extremely small part of the spectral range

depicted in Figure 2.1.

0.0 100

5.0 10-20

1.0 10-19

1.5 10-19

2.0 10-19

2.5 10-19

3.0 10-19

1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0

Inte

nsi

ty (

cm/m

ole

c)

Wavelength (µm)2.73 µm

Set-up

27

Figure 2.2: Experimentally acquired spectrum of the lines of Table 2.1, and three other transitions

that are present in this section, for a natural water sample. The numbering of the lines shown here

will be used throughout this thesis. Note that the most intense line (#3) is more than 3 orders of a

magnitude weaker, in terms of transition strength, than the strongest lines in Figure 2.1.

The water absorptions around 2.7 µm are due to ro-vibrational transitions belonging

primarily to the ν1 (symmetric OH-stretching) and ν3 (antisymmetric OH-stretching) vibrational

bands. As an added bonus, the transitions in question have only relatively small temperature

coefficients. Reliable, accurate isotope ratio measurements can thus be performed without resorting

to complicated temperature stabilisation schemes, as will be demonstrated in this thesis.

In the case of a natural water sample, the 2HOH line (#7) shows the smallest absorption in

comparison to the other selected lines. This is actually an advantage in the case of enriched samples,

since the range of δ2H values encountered in practice is typically one order of magnitude larger than

that for the other isotopic species. The enriched water samples used in bio-medical studies yield2HOH extinction ratios that are comparable in size or even larger than those of the other lines (see

also Chapter 3). At the same time, the strength of line #7 is sufficient to study “natural” samples.

3662.6 3662.8 3663.0 3663.2 3663.4 3663.6 3663.8 3664.0

Ab

sorp

tio

n (

arb

. u

)

wavenumber (cm-1)

1

2

3

4

5

6

7

1H18O1H

1H16O1H

1H17O1H

2H16O1H2H16O1H

2H16O1H

1H16O1H

Chapter 2

28

Table 2.1: The ro-vibrational transitions used in this study.

wavenumber

(cm-1)

Intensity b)

(cm·molecule-1)

temp. coeff. c) at

300 K (K-1)

assignment d) Line

#

Isotopomer

3662.920 1.8·10-23 1.3·10-3 ν = (001) ← (000)

J = 515 ← 514

2 1H18O1H

3663.045 7.5·10-23 4.4·10-3 ν = (100) ← (000)

J = 624 ← 717

3 1H16O1H

3663.321 6.4·10-23 -1.5·10-3 ν = (001) ← (000)

J = 313 ← 414

5 1H17O1H

3663.842 1.2·10-23 -3.4·10-3 ν = (001) ← (000)

J = 212 ← 313

7 2H16O1H

a) All values are taken from the HITRAN 1996 spectroscopic database (Rothman 1998).

b) The intensities are for a natural water sample with abundances: 0.998, 0.00199, 0.00038, and

0.0003 for 1H16O1H, 1H18O1H, 1H17O1H, and 2H16O1H, respectively.

c) The temperature coefficients give the relative change with temperature in absorption intensity of

the selected transitions. They are calculated using the HITRAN 1996 database. See also

Equation 2.4.

d) The notation for the vibrational bands is (ν1,ν2,ν3), whereas the rotational levels are identified by

the three quantum numbers JKaKc.

2.1.2 Spectrometry

The spectroscopic isotope ratio measurement relies on the fact that the attenuation of a

laser beam of initial intensity I0 passing through a gaseous sample is directly related to the number

of molecules absorbing at the frequency ν of the laser radiation. The relation between the

transmitted intensity I(ν) and the molecular density n is given by the Lambert-Beer law (Demtröder

1981):

I I e I e f n l( ) ( ) ( )ν α ν ν ν= ⋅ = ⋅− − ⋅ − ⋅ ⋅0 0

0S (2.1)

The quantity α(ν) will be referred to as the absorption coefficient. Further, S is the line strength, f(ν-

ν0) the normalised line shape function and l the optical path length. In the case of a Doppler

broadened line with a half-width at half-maximum (HWHM) of ΓD, the line shape function takes on

the value f(0) = [√(ln(2)/J)]/ΓD at centre frequency ν0. Given a typical line strength of

2·10–23 cm/molecule for the rotational lines of interest and a gas cell filling of about 10 µl (10 mg)

Set-up

29

water in a 1 litre volume (resulting in a pressure broadened line width of 0.008 cm-1), one calculates

a relative attenuation (I0 - I(ν0))/I0 of about 73% for an optical path length “l” of 20.5 m in the

multiple-pass cell. Not accidentally, this is very close to the optimal value, providing the highest

signal-to-noise ratio (S/N). This can be seen as follows: Assume that the measurement of the power

entering the gas cell, as well as the measurement of the signal transmitted through the gas cell, are

inflicted with a measurement error δI that is independent of the signal level (this will be the case if

detector and/or amplifier noise is the limiting noise factor). The S/N of the measurement of the

absorption coefficient at line centre, α(ν0) ≡ S·f(0)·n·l , then equals:

S NI I

I I II

I/

( )( )

( )( )

ln( )

= = ⋅⋅ +( ) ⋅

α να ν

νδ ν ν

0

0

0 0

0 0

0

0∆(2.2)

It is straightforward to show that the maximum S/N is obtained for I(ν0)/I0 = 0.28, corresponding to

an absorption coefficient of 1.28. In fact, if one demands that the S/N be larger than 50% of this

maximum value, I(ν0)/I0 should be between 0.048 and 0.71 (i.e., the attenuation should be between

29% and 95%, or the absorption coefficient between 0.33 and 3.0). This implies that for any given

combination of path length and line strength a one-order magnitude range of molecular densities can

be accommodated. This is important, as we want to have the ability to work with strongly enriched

samples. As mentioned before, the 2HOH line can become 10 times more intense in certain

biomedical applications (See also Chapter 3).

In a spectroscopic measurement, the isotope ratio (or rather its deviation from that of a

well-defined standard), is obtained in a way illustrated in Figure 2.3. Here, two spectral features are

present in the region scanned by the laser, of which one belongs to the most abundant isotopic

species a (i.e., H16OH), the other to the less abundant species x (in this case H18OH, but it may as

well be H17OH or 2HOH).

The curve labelled “r” in Figure 2.3 represents the spectrum of a reference water (working

standard). The spectrum of the (unknown) water sample is given by the curve “s”. Both spectra have

already been converted from transmittance to absorption coefficient by the application of

Equation 2.1. The “super-ratio” of the peak intensities αz = α(ν0,z) now yields:

α αα α

xs

as

xr

ar

xs

as

xr

ar

xr

ar

xs

as

xs

as

xr

ar

n n

n n

( )( ) =

( )( ) ⋅

( )( ) ⋅

( )( )

S S

S S

Γ ΓΓ Γ

(2.3)

There is no dependence on the optical path lengths in the sample and reference cells as

these are necessarily the same for both isotopic species. The line widths and their temperature

Chapter 2

30

dependence are for most practical purposes the same for both isotopic species. The line strength S

depends on the number of molecules in the lower state of the ro-vibrational transition and is

therefore in general temperature dependent (it also includes the effect of induced emission, which,

however, is negligibly small in our case). The first two factors on the right-hand side in Equation 2.3

will therefore reduce to unity only if the two gas cells are kept at the same temperature. However, if

one allows for a small temperature difference between the sample and reference gas cells, say

∆T = Ts – Tr, then this factor will in first order equal:

S S

S S

S S

S S S

S

S

Sxs

as

xr

ar

xr

ar

xs

as

xs

as

xr

ar

xr

x

r

ar

x

r

T T T TT

( )( ) ⋅

( )( ) ≈

( )( ) ≈ +

−

Γ ΓΓ Γ

∆11 1( ) ( )

∂∂

∂∂

= + −[ ]1 ζ ζx a T∆ (2.4)

in which ζ represents the temperature coefficient, as shown in Table 2.1. These are

relatively small in the case of the absorption lines used in this study. Consequently, only passive

control of the gas cell temperature is needed.

0

0.5

1

1.5

2

2.5

3662.85 3662.9 3662.95 3663 3663.05 3663.1 3663.15 3663.2

αααα (

arb

. u.)

Wavenumber (cm-1)

r

sαααα

xs

ααααa

r

ααααx

r

ααααa

s

νννν0,x

νννν0,a

Figure 2.3: Two spectral features, the smaller one belonging to a less abundant isotopomer “x” (in

this case H18OH), the bigger one to “a” (here H16OH). “s” is the spectrum of a sample, while “r”

represents a reference water. Their line intensities are a direct measure of the abundance.

Set-up

31

In general, the isotope ratio of a sample is given by xR=nx/na, see also Equation 1.1.

However, it is customary to use xδ, the relative change in the isotope ratio with respect to that of a

standard water. Without loss of generality our reference water can be chosen to be this standard, in

which case (in accordance with Equation 1.2):

xx s

x rx a

s

x ar

RR

n nn n

δ ≡ − = −1 1( / )( / )

(2.5)

Again, it should be noted that the δ-values so-defined now refer to molecular, rather than

atomic isotope ratios. However, in Section 1.2.1 I was already concluded that the difference is much

smaller than our measurement precision. One can therefore neglect this principle difference.

Combining Equations 2.3 through 2.5 yields the expression for xδ we are after:

x xs

as

xr

ar x a Tδ

α αα α

ζ ζ=( )( ) ⋅ + −[ ]( ) −1 1∆ (2.6)

The relation with the δ-value without temperature correction, δ*, is then given by:

δ δ ζ ζ ζ ζ= ⋅ + −[ ]( ) + −[ ]* 1 x a x aT T∆ ∆ (2.7)

Therefore, the effect of a temperature difference between the gas cells would be that the calibration

curve, in which the measured δ-value is plot against the “true” value, shows both a zero-offset and a

slope different from unity.

2.2 System Description

As explained before, the system we developed is a direct absorption spectrometer. This

paragraph describes consecutively the laser system and its operation, the optical set-up, and the

measurement procedures. In the appendix with this chapter, all equipment is listed.

2.2.1 Laser system

The absorption spectrometer uses an infrared laser source, the Color Center Laser (or Farbe

Center Laser; FCL), which is optically pumped by a krypton ion laser.

Chapter 2

32

2.2.1.1 Krypton ion laser

For pumping the Color Center Laser (Section 2.2.1.2) with the Li:RbCL crystal, the light of a

krypton ion laser is the most suitable. It’s wavelength (647 nm) has the highest excitation efficiency

for this crystal. We have been using a commercially available Lexel Krypton laser. This laser is water-

cooled. Power consumption is about 25 A at 220V. The light output is intensity stabilised by means of

a feedback to the current. Although its maximum output power is up to 3 W, the laser was operated

at a modest 700 mW, thus considerably extending its lifespan.

2.2.1.2 FCL

The Color Center Laser is a unique tunable source of continuous wave (CW), single mode,

infrared laser light. It combines wide tuning characteristics with a narrow bandwidth. It’s gain

medium consists of solid alkali halide crystals, which contain point defects or color (F) centers

(Burleigh 1994). These can in their simplest form be described as electrons trapped in a “hole” in the

alkali halide lattice: Their characteristics are determined by the type and number of dopant cations

the trapped electron has as its neighbours.

Laser action of a FCL is based on a four-level scheme (see Figure 2.4): The ground state (1) is

excited to (2) by absorption of light from a pump laser, after which rapid (10-12 s) non-radiative

relaxation occurs. The system is now in the so-called relaxed excited state (3, RES, stable for about

100 – 200 ns) and in practice it remains there until it is de-excited by the stimulated emission of

laser action. The state it decays to (4) experiences once again a very rapid non-radiative transition

back to the ground state (1), thus creating a population inversion between (3) and (4). These levels

are substantially homogeneously broadened, meaning that the positions of the energy levels of the

different active centers are fluctuating in time, due to interruptions of the dipole oscillations by

collisions (Milonni, 1988). This fact enables the laser to be continuously tunable over a wide range of

wavelengths.

Most laser active color center crystals need to be operated at cryogenic temperatures. The

first reason for this is to reduce or avoid the diffusional mobility of the color centers in the alkali

halide crystals that can lead to complex (re)combination of F centers and therewith diminishing laser

action, i.e., to avoid degradation of the crystal. The second reason is that cryogenic operation

ensures that the equilibrium population of state (4) is essentially zero (giving population inversion

with respect to state (3) and that the fluorescence quantum efficiency of the system is large. To

achieve and keep cryogenic temperatures for the 2 mm thick crystal, also when illuminated by a

pumping laser (up to a few watts), it is attached to a cold finger that is in contact with a dewar

containing liquid nitrogen (77 K).

Set-up

33

Figure 2.4: Typical energy level diagram for the laser action of color centers.

We have used a RbCl crystal, doped with Li+-ions built into a Burleigh FCL-20 series laser.

This active medium provides a continuous tuning range from 2.65 µm to 3.4 µm with an output

power that may exceed 20 mW. We have operated the laser routinely at about 12 to 15 mW. The

pump laser output power current is accordingly relaxed, resulting in a longer lifetime of the Kr+ laser

tube.

The laser system is able to lase at many different wavelengths. To ensure single frequency

operation and tunability, a number of elements is placed in the cavity (Figure 2.5). The first, coarse

tuning element is a gold-coated grating that acts as both a cavity end mirror and output coupler. It is

rotated using a stepper motor. The second element is an intracavity tunable etalon (ICE), consisting

of two Littrow prisms. It is used at Brewster’s angle to avoid reflection at the outside surfaces. The

air gap separation is controlled by a piezoelectric element. The third and finest tuning element is a

piezoelectric translator, which displaces the (other) cavity end mirror. To operate the laser on just a

single mode and to tune it completely continuously, the grating and the ICE transmissions are made

Chapter 2

34

to follow the cavity mode, whose frequency is in turn determined by the cavity length (the position

of the end mirror). The mode spacing is about 295 MHz. The maximum length of a continuous scan

is determined by the range of the piezoelectric controllers. This is 6 to 8 GHz (~ 0.25 cm-1) for the

end mirror piezo and about 90 GHZ (~ 3 cm-1) for the ICE piezo. In Paragraph 2.2.2 a more detailed

description of scanning the FCL will be given.

Figure 2.5: FCL cavity in CW frequency configuration.

The FCL has a line width of approximately 3 MHz. When scanning the laser, the etalon

chamber is evacuated to better than 10-3 mbar. The laser requires only occasional re-adjustments; in

practice, this is only needed when deliberate changes to the optical layout are made.

2.2.2 Scanning of the FCL

In order to scan (tune) the laser wavelength (frequency), the cavity length is adjusted by

applying a voltage to the end-mirror piezo actuator. At the same time the ICE and the grating are

made to follow the cavity mode in a feed-forward manner. The stepsize of a single grating step is

accurately known by calibration. The ICE, however, suffers from severe hysteresis and it is therefore

necessary to actively lock the ICE to the cavity mode, in a feed-back loop.

The cavity end-mirror is not used over it’s entire range, but rather returned to its original

position every ~295 MHz (the cavity mode spacing). This can be done without introducing a

detectable discontinuity in the scan. In contrast, when the ICE needs to be returned to its starting

position, the laser does not always return to exactly the same cavity mode (i.e., frequency). At this

point, the wavelength meter and/or the 8 GHz Free Spectral Range (FSR) spectrum analyser need to

be consulted in order to assure a continuous frequency scan. Fortunately, the laser can be tuned

Set-up

35

over more than 3 cm-1 before the upper limit of the ICE piezo voltage is reached, and this is more

than sufficient for our purpose. Scanning of the FCL has previously been described by Kerstel (1991),

and references therein.

The laser scanning is controlled by a personal computer. The application we use for this

purpose is written using the LabVIEW graphical programming language. The application also takes

care of recording, transfering and saving of the data.

2.2.3 Optical lay-out and set-up

The final optical layout is shown in Figure 2.7. Some other approaches we have tried are

described in Paragraph 2.7.

The system has been set-up on a dedicated optical table equiped with a clean-air laminar

flow hood. To further avoid dust contamination the table is protected with plastic curtains. Its

position in the room is chosen in order to minimise the transmission of floor vibrations to the table.

All windows and beam splitters are 1º or 2º wedged to avoid interference of the beams reflecting

from the front and back surface.

The output of the FCL is first split into two beams by means of a 90% beamsplitter. The

largest part of the power is directed to the wavelength meter, the ICE feedback detector (see 2.2.2)

and two external etalons (150 MHz and 8 GHz FSR). The wavelength meter directly measures the

wavelength of the output laser beam (with a precision of ±0.02 cm-1) and receives about 6 mW of

total laser power. The ICE feedback detector receives about 3 mW. Both external etalons need about

1.5 mW.

The remaining 10% (~ 1.2 mW) of the laser power is directed towards the experiment. At

present we have four gas cells in use. To minimise problems with absorptions of atmospheric water

vapour, each beam travels the same distance through air before arriving at the detector. Moreover,

power must be measured separately for each gas cell and the four power-measurement beams must

have the same length as the signal-measurement beams. To meet these requirements, the main

beam travels diagonally across the optical table while at four positions wedged uncoated windows

are positioned which pick off a few percent of the main beam (each typically 10 µW). Their positions

are chosen in order to make all of the path lengths equal. Because we pick off such a small part of

the main beam, it is possible to do so sequentially. It is not necessary to have exactly the same

amount of light for each cell and since there is sufficient light available, we are only restricted by

space and budget in the number of parallel measurement lines (gas cells).

For alignment purposes, an red (633 nm) He/Ne laser is used. By means of a flipping mirror

it is possible to overlap the IR and the red beam. Since the index of refraction is slightly different for

IR and red light and the main beam passes through a number of wedged uncoated windows, the

beams do not follow exactly the same paths: The angles at which the beams leave one of the optical

Chapter 2

36

components differ slightly. To correct for this it is necessary to place the wedged uncoated windows

for light pick off at alternating angles in the beam.

The set-ups following the split off of the main beam are equal for the four gas cells. A lens

with a focal length of 1 m focuses the beam in the middle of the gas cell (or, rather, at the entrance

hole to reduce beam cut-off). Subsequently, the beam is split again in (1) a beam (90% of the

power) that is directed towards the cell via two mirrors to be able to steer the beam in three

dimensions and (2) a beam (10%) that is led directly to an InAs detector. The light emerging from

the gas cell is focussed at the same detector that measures the laser power arriving at the gas cell

entrance. For both the signal and power beams, the same 50 mm focussing lens is used. Both beams

(signal and power) can be distinguished by modulation of their amplitudes at different frequencies

using separate optical choppers. The intensities of the beams can be recovered by using phase

sensitive detection, using two different digital signal processing (DSP) lock-in amplifiers (LIAs).

The gas cells are equipped with two gold-coated mirrors that are basically sphere segments

with a radius of 0.5 m. They are used in the Herriot scheme (Herriot 1964, Altmann 1981). Because

of the mirror shape and alignment, the cells refocus the light after every reflection. One mirror has

an entrance hole at 22 mm from the centre. The beam is led into the cell through this hole. A circular

pattern builds up in the cell. The beam leaves the cell again after 47 reflections (48 passes),

resulting in a 20.5 m path length. See Figure 2.6 for a visual impression. The intensity of the

outgoing beam is decreased, due to non-ideal mirror reflectivities. The ratio between the intensity of

in- and outgoing beams is given by Rn, with R as the mirror reflectivity (typically 98%) and n the

number of reflections. For example, for 47 passes and 98% reflectivity, ideally 39% of the light

passes the cell. In practice, the magnitudes of the power and signal beams are about the same when

arriving at the detector.

Figure 2.6: Open multiple pass gas cell. The beam of a red He/Ne laser on one of the gas cell mirrors

and the beams in air are shown, operated in the multiple-pass mode as described in the text. The

beams are made visible by condensing water in air produced with liquid nitrogen. On the mirror the

round spot pattern can clearly be observed.

Set-up

37

Careful alignment of the gas cells (distance of the mirrors and their tilt and correct steering of the

incoming beam) is absolutely necessary (1) to get the desired path length, (2) to avoid the loss of

light at the edges of the mirrors and (3) to avoid interferences associated with overlapping reflection

spots.

Figure 2.7: Lay-out of the optical system. The optical path of the four signal and four power beams is

very closely equal (in the present set-up about 267 cm).

2.2.4 Operation

Both external etalons are used in spectrum analyser (scanning) mode to monitor the single

mode performance of the laser. Their information is stored along with the spectra in the form of a

signal proportional to the mirror piezo voltage at which transmission through the etalon occurs

(Kerstel 1991).

The IR detectors are thermo-electrically cooled InAs photovoltaic devices with an active area

of 2 mm diameter. Their output signals (one for each gas cell) are amplified with home-built pre-

amplifiers. The output signal is used as the input of a DSP LIA to retrieve both the signal and power.

The DSP LIAs we have presently in use (EG&G 7265), are able to demodulate the incoming signal at

both the signal and power modulation frequencies as long as one of the modulation frequencies is

equal to the internal LIA oscillator frequency. This is achieved with an optical chopper that is able to

follow the imposed frequency. This double-modulation, one-detector, source compensation technique

reduces the effects of detector non-linearity and (temperature induced) responsitivity changes. In

addition, since we require only one LIA per gas cell, temperature drifts of the amplifiers are largely

Chapter 2

38

cancelled in the signal to power ratio. The choppers have typical modulation frequencies are around

1 kHz, the usual LIA settings are 200 mV full scale, 50 ms time constant and a dynamic reserve of

24 dB/oct.

As mentioned before, scanning of the FCL is performed by a LabVIEW application (National

Instruments). It offers the possibility, amongst others, to set the scan range, scan speed and

stepsize and then calculates the desired output voltages for the tunable elements based on earlier

calibrations. It also sets the laser to its desired single mode position prior to the beginning of the

scan (using the 8 GHz external etalon signal and wavelength meter readings) and it controls the

on/off-switch of the ICE feed-back loop. During the scan the LIAs store their output simultaneously

in their own internal 32k data point buffer memory. These buffers are divided into three parts: One

for the signal, one for the power and one for an external input (16-bit resolution A/D converter

input; e.g., for the external etalon signals). The LIAs serve as D/A converters as well by translating

the voltages set by the computer to output voltages needed for scanning the laser. Also the TTL

pattern for the grating stepper motor is generated by one of the LIAs. After completing one scan

(typically 2000 – 5000 laser steps), the memory buffers are read by the computer and written to file.

A scan with 8 MHz stepsize (giving ~5000 values over the selected spectral range) typically takes

2.5 minutes. Finding the single mode position and reading the data from the internal memory buffer

together takes typically one minute. Thus, one measurement series (typically 8 scans at this

resolution) takes about 30 minutes.

2.2.5 Measurement procedures

The gas cells are made of stainless steel, the tubes of glass and they have a volume of about

1 l. Attached to the glass tubes is a small compartment (~1 ml) separated from the main volume of

the cell by a valve. These compartments are filled with dry N2 prior to each sample introduction.

Using a 10 µl syringe, liquid water samples are injected through a silicon membrane (“septum”).

After retraction of the syringe the valve is opened, letting the water evaporate into the multiple-pass

cell. This results in a gas cell pressure of about 13 mbar (the room temperature saturated vapour

pressure is about 32 mbar). After exactly 5 minutes the valve is closed again. This procedure avoids

problems with the vacuum integrity of the septum and with freezing of the water during injection.

Before each sample introduction the gas cell and its septum compartment are thoroughly cleaned by

a pump-flush-pump cycle (using dry N2 at about 1.5 bar). In a typical measurement, 8 to 15

individual laser scans are recorded before a new sample is introduced. Stepsizes of about 8 MHz to

16 MHz are used. This way a measurement, including sample introduction and gas cell evacuation

takes about 45 minutes.

One cell is always reserved for the working standard, the others for calibration standards

and samples. The working standard and calibration standards are waters with a well-known isotopic

Set-up

39

composition with respect to the internationally accepted calibration material “Vienna Standard Mean

Ocean Water” (VSMOW, see also Chapter 1).

The signal attenuation is between 25 and 90% for each of the selected transitions and

natural water samples. The lines are pressure broadened to about 0.008 cm-1 (~ 240 MHz; HWHM).

To avoid cross-contamination of the gas cells they are separated with cryogenic traps made

out of glass. The traps are connected to a common pump line and simultaneously pumped.

2.3 Calculations

This paragraph describes the necessary steps for calculating the isotope ratios from the

measured absorption spectra, principally based on Equation 2.1 and 2.5. The further correction and

calibration steps will also be described. In the first step the raw isotope ratios are calculated from the

spectra, in the following steps correction for pressure differences and zero-point are made and finally

calibration and normaliztion are performed.

2.3.1 Raw isotope ratio calculations

The first step on the way to determining the isotope ratios is to correct the gas cell

absorption spectrum for laser power variations. This is done by dividing each gas cell spectrum S

(reference and sample) by its accompanying power spectrum P (measured at the gas cell entrance),

to calculate the absorbance Α. Αpart from a constant term, A is equal to the absorption coefficient α

of Equation 2.1:

ASP

and ASP

samplesample

sampleref

ref

ref( ) ln(( )( )

), : ( ) ln(( )( )

)ν νν

ν νν

= − = − (2.8)

where ν again represents the laser frequency. The center of a spectral feature z (i.e., one of the ro-

vibrational lines belonging to the isotopic species z = H16OH, H17OH, H18OH, or 2HOH) is given by νz.

For each spectral feature (line) in the spectrum the corresponding section of the sample

absorbance Asample is fit to the sum of the reference absorbance Aref and a quadratic base-line:

A A Rsample refz z( ) ( ) ( )ν ϕ ν β β ν ν β ν ν ν= ⋅ + + ⋅ −( ) + ⋅ −( ) +0 1 2

2 (2.9)

This yields for each isotopic species a set of constants (ϕ, β0, β1, and β2) that minimises the

sum of the squared residuals [R(ν)]2 for ν in a selected interval of datapoints around the line center

νz.. This procedure is depicted graphically in Figure 2.8.

Chapter 2

40

Figure 2.8: Spectral features of interest in the selected part of the spectrum. The other lines are

removed, the base-line sections are as long as possible to determine their position. The upper plot

shows the residuals of the best possible fit, the lower plot shows the reference and sample spectrum,

corrected for laser power fluctuations. “i” is a measure for the laser frequency “ν”.

Since the experimental frequency calibration of the spectra is not perfect, the exact positions

of the spectral features are re-determined for each laser scan. The range over which the sample

spectral feature is compared to the corresponding line in the reference spectrum is fixed and

Set-up

41

determined by the position of the neighbouring lines (chosen to minimise the effects of overlap). It is

always relative to the line center. The isotope ratio is now calculated from:

x x

a

δ ϕϕ

= − 1 (2.10)

This is analogue to Equation 2.5. The subscript a refers to the most abundant isotopic species,

H16OH, while x refers to one of the rare species, H18OH, H17OH, or 2HOH. As mentioned before, these

molecular concentration δ-values are for most practical purposes equal to the corresponding values

based on atom concentrations. An important requirement is that the temperature of the gas cells is

supposed to remain the same. A constant temperature difference, however, can be corrected for by

proper calibration.

One of the most important advantages of the data analysis procedure is that non-linearities

and/or irregularities (such as a cavity mode-hop) in the frequency scan of the laser have no adverse

effect on the quality of the fit of Equation 2.9. If one were to determine the line intensities by

performing a line profile (Voigt) fit to each individual transition, frequency scale errors may

propagate through the line profile fit into the final δ–value (even though these should ideally cancel

in the ratio of line profiles).

The application that we use for performing the fit is written in (CodeWarrior) Pascal.

At this stage, we have obtained the raw δ value, for which we will write δ*.

2.3.2 Pressure dependence correction

Changing the amount of water in both the reference and sample cells from 8 µl to 12 µl per

gas cell (corresponding to pressures between approximately 11 mbar and 16 mbar) does not result

in a significant shift of the measured δ-values as long as the water vapour pressure in the two gas

cells remains equal. The effect of changing the quantity of water is that the line width (and the line

shape) changes due to pressure (collision) broadening (Demtröder 1981), but since the same change

occurs in both the sample and reference spectra, the effect cancels in the line intensity ratio (i.e., the

parameter ϕ in Equation 2.9).

However, a pressure difference between the two gas cells does have a significant effect on

the δ–values determined from Equation 2.10, even when the isotopic composition of sample and

reference waters is the same. This is shown in the upper half of Figure 2.9. Such pressure

differences occur in practice due to our inability to inject the 10 µl water samples with an accuracy

better than approximately 0.1 µl. The effect is that the line widths in the sample and reference

spectra can be measurably different.

Chapter 2

42

-40

-30

-20

-10

0

10

20

30

-100 -50 0 50 100

δ(18O)

δ(17O)

δ(2H)

δδδδ (‰

)

8

9

10

11

12

-100 -50 0 50 100

Sam

ple

Cel

l Am

ou

nt

(µl)

∆∆∆∆ΓΓΓΓ////ΓΓΓΓr (‰)

Figure 2.9: Experimentally determined apparent δ-values (upper half) for the different isotopomers

and the amount of water in the sample cell (lower half), both as a function of the line width

difference.

Set-up

43

In the upper half of Figure 2.9, the measured shift in the apparent δ’s, with respect to the

situation with 10 µl of water in each gas cell, is plot as a function of the relative average line width

difference ∆Γ/Γr. Here ∆Γ = Γs−Γr, with Γs and Γr the average line widths of the observed lines in the

sample and reference spectra, respectively. The bottom half of Figure 2.9 shows the experimentally

determined relation of ∆Γ/Γr with the amount of water in the sample gas cell (the reference gas cell

always contains 10 µl). Although the pressure broadening coefficients are in general dependent on,

among other factors, the rotational quantum number and the isotopic make-up of the molecule, they

are not expected to be sufficiently different to explain our observations. In fact, we have not been

able to establish any difference in pressure broadening coefficients for the four ro-vibrational lines of

Table 2.1, based on the spectra we recorded at pressures between 10 mbar and 36 mbar. For water

vapour pressures near 13 mbar (10 µl) we find experimental pressure broadening coefficients that

for all 4 lines are equal within one sigma to (0.31 ± 0.01)⋅10-3 cm–1/mbar.

The shift in the apparent δ’s determined for both δ17O and δ18O varies appreciably with the

amount of water injected into the sample cell, while at the same time δ2H changes much less and in

the opposite direction. The cause of the apparent shift is different and can be understood by

considering the differences between the isotopomers. Both the H17OH and H18OH lines, and to a

lesser extent also the H16OH line, are relatively near to other lines in the spectrum. This makes it

necessary to limit the range over which the least-squares approximation of Equation 2.9 is made

(see also Figure 2.9), to the extent that a very significant portion of the wings of the lines is cut-off.

In other words: At the extremes of the fitting range, the line intensity is still significantly different

from zero. Obviously, the larger the vapour pressure, the larger the line width and the more serious

this effect becomes. If the line widths in the sample and reference spectra are equal (same pressure,

temperature and isotope abundance ratios in the two gas cells) the fitting procedure should not

suffer too much. However, a difference in line width will lead to a systematic fitting error. Since the

calculation of the δ-value involves the (super–) ratio of rare and most abundant isotopic species line-

ratios, the two systematic errors associated with the line-ratio determinations may (partially) cancel,

especially if the two fits (rare and most abundant isotopic species) are carried out over a similar part

of the line shape. Clearly then, this is not the case for δ(17O) and δ(18O) where the H17OH and H18OH

lines are more severely truncated than the H16OH line. For δ2H the situation is slightly different. Since

the 2HOH line is much better isolated with respect to the H16OH line, a sufficiently large section of

the spectrum can be used to perform the fit of Equation 2.9, and the systematic error mentioned

above remains very small. In this case, the shift of the apparent δ is mostly due to the error made in

the H16OH line-ratio determination.

The observed apparent shifts in δ-values suggests a correction to the measured value, δ*, of

the form:

Chapter 2

44

δ δ γ *= + ⋅−Γ Γ

Γsample ref

ref

(2.11)

The value of γ was determined experimentally: γ(H18OH) = –0.248(16),

γ(H17OH) = –0.330(8), and γ(2HOH) = 0.016(17) where the values in brackets indicate the standard

deviation (Figure 2.9).

As will be discussed later, we can reproduce the experimental differential pressure

observations by numerical modelling of the data analysis procedure, while assuming equal pressure

broadening coefficients for all of the ro-vibrational lines. We will then see that Equation 2.11 is not

complete yet. The fact that the peak intensity influences the level of line cut-off means that changing

the concentration of an isotopomer has the same effect on the corresponding line as changing the

total amount of water. The later derived relation will be used for the routine measurements.

The gas cell pressure differential is determined for each series of scans by measuring the

relative difference in the (average) line widths in the sample and reference spectra. The value used

is the mean of the median line widths determined from the consecutive scans within a series. The

relative difference is then used to calculate the correction to the measured δ-value, accordingly to

Equation 2.11.

At this stage we have obtained the δ-values, corrected for pressure differences.

2.3.3 Filtering and calculation of mean values

Accidental outliers (all values removed from the median by more than twice the absolute

deviation) are removed (rarely more than 2 out of 15). The average value of the remaining

measurements is reported as the final result, together with its standard error. If, however, a

significant trend in the consecutive δ-values is observed, the end-point of the best (linear) fit through

the individual measurements, back interpolated to the moment of injection (opening of the valve) is

used as the final result. Especially for (highly) enriched samples this trend analysis procedure

provides us with better results in a shorter measurement time. It is then namely unnecessary to flush

the cells repeatedly with sample until a totally stable signal is reached (due to memory effect, see

Paragraph 2.5.4).

At this stage from all series of pressure-difference-corrected-δ-values we have obtained an average

value and an indication of its precision.

2.3.4 Zero point adjustment

We find values that are non-zero if we measure a water sample against itself. This is

probably due to reasons of alignment (i.e., beam cut-off or detector alignment changing with laser

frequency). Thus, all of the cells have a certain offset that differs for each cell and isotope. The value

Set-up

45

of the offset is typically between zero and 10‰ and can have both a positive or a negative sign. In

order to adjust the zero point and thus deduce the true δ-values, we have to apply a correction in

the form of:

δ ω δ ω= + ⋅ +( ), ,x cmeas

x c1 (2.12)

Where ωx, c represents the offset, depending on the isotopomer and sample cell of interest. Note that

this correction does not only remove the offset, (such as simple subtraction would do), but also

influences the slope. This is similar as the temperature difference dependency from Equation 2.7.

To be able to make a reliable zero point adjustment, frequent measurements of the offset

(e.g., working standard against working standard) are needed. The correction has proven to be

stable in time, provided the optical alignment is not (deliberately) changed.

At this stage we have obtained the non-calibrated δ-values.

2.3.5 Calibration and normalization

The last step in the process of the calculation of the final result is the calibration of the entire

system.

One of the local standards is mostly used as the working standard in the reference gas cell.

Consequently, the laser-spectrometer values are initially referenced to this material. These have to

be converted to values relative to VSMOW, ideally using the laser determined value of the working

standard with respect to VSMOW (or vice versa). Note that this inherently takes care of the zero-

point adjustment of the laser spectrometric δ–scale. We can, however, also use the known values of

the working standard to make this conversion, after the zero-point adjustment is completed. In order

to calibrate the instrument, we have to measure a series of local water standards (preferably

spanning the total expected range of the series of samples) that are well-characterised with respect

to VSMOW by repeated mass-spectrometer analyses in our laboratory. Alternatively, international

calibration and reference materials (SMOW, SLAP and GISP) can be used to create the calibration

curve. For δ18O and δ17O the calibration curves show a very good linear relation. For δ2H

measurements, however, a quadratic correction must be applied for high enrichments:

δ ξ δ ψ δcalibrated = + ⋅ + ⋅( ) ( )# #1 2 (2.13)

Where δ# represents the uncalibrated δ-value.

The quadratic contribution is not significant, except for δ2H enrichments above ~5000‰. In

IRMS a similar phenomenon is observed caused by so–called cross-contamination (Meijer 2000).

Chapter 2

46

The slopes of the calibration curves are in most cases significantly different from unity: Laser

spectrometry usually under-estimates the isotope abundance ratios. The magnitude of the deviation

is often the biggest for δ2H and has an observed maximum of 4% of the value. After careful

alignment, however, it is often much closer to zero and the sign can even change. We therefore

believe that this deviation must be due to residual etalon fringes (interferences) in the optical

system.

As has become apparent over the years in numerous international ring tests (e.g., Lippman

1999, Araguas–Araguas 2000), IRMS-based measurements too often exhibit calibration curves with

slopes smaller than unity, and in particular for 2H the deviations found are sometimes even larger

than the maximum deviation found in the present laser system. A pragmatic approach to these

problems, in which the δ–scales are defined by a linear calibration using two different calibration

materials (e.g., SLAP in addition to VSMOW), has been generally accepted, and in fact is

recommended by the IAEA (Coplen 1988). The same solution is applied to our laser-based method

by the approach described above. It is reliable since the reproducibility of the measurements turned

out to be good over an extended period of time.

At this stage, the calibration (“stretch”) factors are known, and one can easily calculate the final

δ–values from the mean values after zero-point correction, obtained in the previous section. The now

obtained values are the final results.

Set-up

47

2.4 Precision and accuracy of laser spectroscopy

The LS system has proven to be able to measure isotope ratios in both the natural (Kerstel

1999) and enriched regimes (Van Trigt 2001a). The text in this paragraph is based on parts of those

publications. The reader should realise that the measurements presented for the natural range are

not the most recent ones. They serve as a demonstration of the procedures described in the

preceding paragraphs. More recent measurement results in the natural abundance range will be

presented in Chapter 4.

2.4.1. Measurements in the natural abundance range

We demonstrate the first successful application of infrared laser spectrometry to the

accurate, simultaneous determination of the relative 2H/1H, 17O/16O, and 18O/16O isotope abundance

ratios in water. The method uses a narrow line width color center laser to record the direct

absorption spectrum of low-pressure gas-phase water samples (presently 10 µl liquid) in the 3 µm

spectral region. It thus avoids the laborious chemical preparations of the sample that are required in

the case of the conventional isotope ratio mass spectrometer measurement. The precision of the

spectroscopic technique is shown to be 0.7‰ for δ2H and 0.5‰ for δ17O and δ18O (δ represents the

relative deviation of a sample’s isotope abundance ratio with respect to that of a calibration

material), while the calibrated accuracy amounts to about 3‰ and 1‰, respectively, for water with

an isotopic composition in the range of the Standard Light Antarctic Precipitation (SLAP) and Vienna

Standard Mean Ocean Water (VSMOW) international standards.

2.4.1.1 Experimental section

In order to calibrate the instrument, we measured the (IAEA) reference material GISP

(“Greenland Ice Sheet Precipitation”), as well as a series of local water standards that are well-

characterised with respect to VSMOW by repeated mass-spectrometer analyses in our laboratory

(see Table IV). The local standard “GS-23” was used as working standard in the reference gas cell.

Consequently, the laser-spectrometer (LS) values are initially referenced to this material. These have

been converted to values relative to VSMOW, using the laser spectrometrically determined value of

GS-23 with respect to VSMOW. This inherently takes care of the zero-point adjustment of the laser

spectrometric δ-scale.

In Figure 2.10 we present the resulting calibration curves for the three isotopic species. In

the case of 1H17O1H, the GS-32 local standard was excluded from the test. For all other water

samples (Meijer 1998):

1 117 18 0 5281+ = +[ ]δ δ( ) ( )

.O O (2.14)

Chapter 2

48

As the 2H-, and to a lesser extend the O-, measurements are afflicted with a large memory

effect (the influence of the previous sample on the current measurement), it turned out to be

occasionally necessary to inject 3 or more water samples before the measured δ-value reached its

final value. To minimise the influence of this memory effect on the calibration procedure, large steps

in δ-values between subsequent samples were avoided as much as possible. For the same reason,

Figure 2.10 includes data recorded both in increasing and in decreasing order of δ-value. In the

future, the gas cells may be operated at an elevated temperature in order to promote a quicker

water removal from the cells.

The calibration data of Figure 2.10 are fit to linear functions with variable slope. The RMS

value of the residuals gives a good indication of the over-all accuracy of the method, including all

effects of sample handling. The values are: 2.8‰, 0.7‰, and 1.3‰ for δ2H, δ17Ο, and δ18Ο,

respectively. The precision of the method is given by the standard error of the individual results of

one series of (typically) 15 laser scans. The current average values of these are: 0.7‰, 0.3‰, and

0.5‰, for δ2H, δ17Ο, and δ18Ο, respectively. In the case of 17O and 18O the precision can still be

improved by increasing the number of laser scans in one run (i.e., increasing the measuring time).

For δ(2H) the minimum standard error has already been reached at this point, indicating that the

precision in this case is limited by sample-handling errors, including memory effects and isotope

fractionation at the gas cell walls. In fact, extensive fractionation at the walls is to be expected, in

particular for hydrogen. However, such fractionation is only observable to the extent that the two

gas cells behave differently. If such is the case, injecting exactly the same water sample in both cells

will result in a δ-value significantly different from zero. This we do not observe. It should be noted

that fractionation between the liquid and gas phases of water is avoided by working at a

substantially lower pressure (13 mbar) than the saturated vapour pressure (32 mbar at room

temperature): all liquid water injected quickly evaporates inside the evacuated gas cell.

The slopes of the calibration curves are all different from unity: laser spectrometry under-

estimates the isotope ratios. It appears as if the sample is mixed with reference water (but not vice

versa, as cross-contamination would lead to a quadratic deviation, which is not observed, Meijer

2000). Although we have established that the sample introduction procedure cannot be blamed, we

have not yet been able to eliminate this residual effect (perhaps caused by memory effects in the

vacuum system).

Set-up

49

Figure 2.10. The calibration curves for a) δ2H, b) δ17O, and c) δ18O. The root mean square deviations

of the residuals are 2.8‰, 0.7‰, and 1.3‰, respectively.

Chapter 2

50

Table 2.2 SLAP δ-values (‰) (referenced to VSMOW).

Isotope Laser Spectrometera) Consensus Valueb)

δ(2H) -415.47 (0.85) -428.0δ(17O) -28.11 (0.23) -29.70δ(18O) -53.88 (0.37) -55.50

a) Based on 11 measurement series (or runs, each consisting of 15 individual laser scans) and

acquired over a one-month interval. The standard error is given between brackets.

b) Consensus value: recommended by the IAEA (Gonfiantini 1984). The δ2H value results from a

mixture of isotopically pure synthetic waters and is regarded to be correct in absolute terms. The

δ18O is the consensus value of 25 laboratories; the true value is likely somewhat more negative

(Meijer 2000). The δ17O value is based on the consensus δ18O value in combination with

Equation 2.14.

As has become apparent over the years in numerous international ring tests, IRMS-based

measurements too exhibit calibration curves with slopes smaller than unity, and in particular for 2H

the deviations found are often much larger than those of the present laser system. A pragmatic

approach to these problems, in which the δ-scales are defined by a linear calibration using two

different calibration waters (e.g., SLAP in addition to VSMOW), has been generally accepted, and in

fact is recommended by the IAEA (Gonfiantini 1984, Hut 1986). The same solution can be applied to

our laser-based method. Even more so, since the reproducibility of the measurements is rather good,

especially considering that the results of Figure 2.10 were gathered over an extended period of time

(about two months). This means that the system is now ready to be applied to the bio-medical

doubly-labelled water method to measure energy expenditure, as well as to the accurate

measurement of natural abundances, for which especially the δ2H determination is already

competitive.

The VSMOW-SLAP linear calibration and its results are summarised in the Tables 2.2, 2.3 and

2.4. In Table 2.2 the mean of the LS δ-values (referenced to VSMOW), that determined the scale

expansion factor, is compared with the respective IAEA consensus values for each of the isotopes. In

Table 2.3 the individual measurements for VSMOW and SLAP are presented, again referenced to

VSMOW and this time after linear calibration (i.e., the mean of these measurements equals the

corresponding IAEA consensus value). Finally, Table 2.4 confronts the LS results with the MS results

by comparing the current “best” values for a series of 7 water samples (including VSMOW and SLAP,

which define the linear calibration).

Set-up

51

Table 2.3: The results for VSMOW and SLAP, against VSMOW and scaled to the SLAP consensus

values as reported here in Table II, with in parentheses the standard errors (all in per mil points), as

well as the standard deviation.

Sample δ2H δ17O δ18O

VSMOW 1.17 (0.60) 0.49 (0.27) 1.25 (0.66)

VSMOW -1.63 (0.65) 0.25 (0.24) 2.11 (0.44)

VSMOW -0.07 (1.05) -0.22 (0.31) 0.35 (0.70)

VSMOW 0.23 (0.99) 0.29 (0.28) 0.70 (0.73)

VSMOW -0.09 (0.80) -0.09 (0.32) -1.00 (0.33)

VSMOW -1.41 (0.97) -0.28 (0.39) -1.66 (0.46)

VSMOW 1.30 (0.96) -0.66 (0.19) -1.82 (0.72)

VSMOW 0.49 (0.83) 0.22 (0.31) 0.07 (0.38)

Standard Deviation 1.07 0.38 1.40

SLAP -426.04 (0.47) -31.23 (0.18) -56.52 (0.33)

SLAP -426.21 (0.43) -30.00 (0.25) -56.35 (0.38)

SLAP -422.76 (1.55) -28.74 (0.28) -55.35 (0.43)

SLAP -426.30 (0.39) -29.52 (0.23) -55.55 (0.31)

SLAP -428.77 (0.29) -29.84 (0.22) -57.44 (0.52)

SLAP -429.92 (0.33) -30.73 (0.32) -55.73 (0.48)

SLAP -425.71 (0.80) -29.39 (0.38) -53.91 (0.46)

SLAP -430.83 (1.19) -28.61 (0.47) -55.70 (0.82)

SLAP -430.74 (0.51) -29.63 (0.55) -56.50 (0.56)

SLAP -432.60 90.39) -30.12 (0.28) -54.06 (0.54)

SLAP -428.11 (0.36) -28.88 (0.38) -53.38 (0.38)

Standard Deviaition 2.89 0.81 1.26

Chapter 2

52

Table 2.4: Laser spectrometry (LS) compared to mass spectrometry. The LS results are based on

between N = 4 and 11 δ-determinations (of 15 individual laser scans each), spread out in time over

a period of between 4 and 10 weeks. All values are expressed in per mil points. The standard error

of the mean values reported for the LS measurements is given in parentheses.

Mass Spectrometry Laser Spectrometry

Standarda) δ2H δ17O b) δ18O δ2H δ17O δ18O

VSMOW 0.0 0.0 0.0 0.0 (0.4) 0.0 (0.13) 0.0 (0.5)

SLAP -428.0 -29.70 -55.5 -428.8 (0.9) -29.7 (0.2) -55.5 (0.4)

GISP -190.0 -13.21 -24.76 -188.8 (0.3) -13.2 (0.3) -25.0 (0.5)

GS-23 -41.0 -3.36 -6.29 -41.4 (0.8) -3.3 (0.3) -6.7 (0.4)

GS-31 -257.8 -75.48 -137.3 -260.5 (0.4) -76.5 (0.9) -139.3 (0.2)

GS-30 -403.3 -127.55 -227.7 -405.4 (0.8) -128.0 (0.4) -232.5 (0.5)

GS-32 -91.5 --- -56.84 -98.6 (0.5) -46.9 (0.10) -58.0 (0.5)

a) The VSMOW and SLAP values for δ2H and δ18O are those recommended by the IAEA (Gonfiantini

1984). The reference material GISP has the consensus values: δ2H = –189.7 (1.1)‰ and

δ18O = –24.79 (0.09)‰. The Groningen GS local standards have been established by repeated mass

spectrometric analysis in our laboratory over a period of several years. GS-23 is a natural water;

GS–30, GS-31, and GS-32 are synthesised.

b) The δ17O values of those water samples that exhibit a natural relation between the 17O and 18O

abundance ratios (i.e., all except GS-32) have been calculated from: (1+ δ17O) = (1+ δ18O)λ, with

λ = 0.5281 (0.0015).

2.4.1.2 Summary of measurements in the natural enrichment range

We have shown that laser spectrometry presents a promising alternative to conventional

mass spectrometric isotope ratio analysis of water. In particular, the laser based method is

conceptually very simple and does not require cumbersome, time-consuming pre-treatments of the

sample before measurement. This excludes an important source of errors. Moreover, all of the three

isotope ratios, 2H/1H, 18O/16O, as well as 17O/16O (virtually impossible by means of IRMS), are

determined at the same time without requiring different (chemical) pre-treatments of the sample.

The precision of the method is currently about 0.7‰ for 2H/1H and 0.5‰ for the oxygen

isotopes. We have shown a calibrated accuracy of about 3‰, respectively 1‰. Since the calibration

data were collected over an extended period in time it is expected that more frequent calibration will

enable us to achieve an accuracy closer to the intrinsic precision of the apparatus. In addition, the

calibration procedure will be improved by the simultaneous measurement of more than one standard

water (i.e., for natural abundance measurements one would use two local laboratory standards, one

Set-up

53

close to VSMOW in isotopic composition, the other close to SLAP). In particular, the standards should

be chosen each at one end of the expected range of δ-values, not near to one end as is the case

here for δ17O and δ18O.

Currently, the throughput is limited to about one sample per hour, comparable to that of the

original, conventional methods when both δ2H and δ18O are determined and the sample preparation

time is added to the actual IRMS time. With modest improvements in the detection (faster amplitude

modulation and a shorter lock-in time-constant) this can probably be increased by a factor of two,

the final limiting factor being the evacuation and flushing of the gas cells. However, the throughput

is most easily increased by the use of multiple gas cells, allowing the parallel measurement on many

more than just one sample. Considering the very modest demands on laser power, relative to the

output power of the available laser system, the number of gas cells is only limited by budgetary and

space constraints.

2.4.2 Measurements in the enriched range as applied in the

doubly labelled water method

We demonstrate the feasibility of using laser spectrometry (LS) to analyse isotopically highly

enriched water samples (i.e., δ2H ≤ 15000‰, δ18O ≤ 1200‰), as often used in the biomedical

doubly labelled water (DLW) method to quantify energy metabolism. See Chapter 3 fore detailed

information on the DLW method. This application is an important extension of the possibilities of a

recently developed infrared laser direct absorption spectrometer. The measurements on highly

enriched, small-size (10 µl liquid water) samples show a clearly better accuracy for the 2H/1H ratio.

In the case of 18O/16O, the same level of accuracy is obtained as with conventional isotope ratio mass

spectrometer (IRMS) analysis. With LS the precision is better for both 18O/16O and 2H/1H. New is the

ability to measure 17O/16O with the same accuracy as 18O/16O. A major advantage of the present

technique is the absence of chemical sample preparation. The method is proven to be reliable and

accurate and is ready to be used in many biomedical applications.

2.4.2.1 Experimental section

In the following section we will first discuss the preparation of the standards that are used

for calibration purposes, as well as the unknown samples used in this comparative study.

Subsequently, we will describe the experimental procedures and techniques for the isotope

measurements.

Standards

The only reliable way of obtaining “absolute” isotope standards is by gravimetrical methods.

For 2H, accurate gravimetrical preparation of standards is possible, thanks to the fact that isotopically

pure 2HO2H and 1HO1H are readily available. In fact, the 2H/1H abundance ratio of the calibration

Chapter 2

54

materials VSMOW and SLAP are known absolutely by way of gravimetrical mixing (Hagemann 1970,

De Wit 1980, Tse 1980).

For 18O and 17O the situation is not so simple: Neither is it possible to obtain 100% pure 16O,17O, or 18O containing water, nor it is possible to know the isotope composition with a high degree of

accuracy, although some efforts toward this goal have been published (Baertschi 1972, Li 1988,

Jabeen 1997, Gonfiantini 1995). It is possible, however, to construct a dilution series of working

standards while maintaining a well-known, linear relation between the enrichment levels of the

different isotopes. We prepared our working standards for this study by gravimetric mixing of a

distilled water with a certified heavily enriched water (18O = 94.5 and 17O = 19.2 atom %) and

almost pure D2O (2H = 99.9 atom %), and using a calibrated balance (Sartorius Analytic). The

independent 17O enrichment of the standards is a novelty, required here to test the unique capability

of our LS system to measure δ17O in addition to the usual δ18O and δ2H (see Kerstel 1999). A range

of enrichments was created from one “mother mixture”, to avoid an accumulation of errors. The

weighing uncertainties yield uncertainties for the linearity of the isotope ratio scale that are in all

cases smaller than the measurement accuracy of either the IRMS or the LS instrumentation (see

Table 2.5). We will come back to this point in the discussion.

Table 2.5: Calculated values of the gravimetrically mixed enriched standards.

δ2H (‰) δ 17O (‰) δ 18O (‰)

TLW-0 -41 (1) -3.1 (1) -6.3 (1)

TLW-1 1273 (10) 28.9 (6) 97.8 (5)

TLW-2 2585 (20) 60.9 (10) 201.8 (18)

TLW-3 5217 (50) 125.1 (20) 410.3 (20)

TLW-4 10820 (100) 261.7 (40) 854.3 (40)

The values rely on the specified enrichments of the commercial starting material. Errors are worst

case estimates of the effect of weighing uncertainty in the mixing process and are given in units of

the least significant digit.

Unknown samples

As unknown samples we used 51 vials of blood of Japanese quails (Coturnix c. Japonica)

obtained in a validation study of the DLW method against respiration gas analysis (Van Trigt 2001c).

All blood samples were distilled on a microdistillation column. Among the samples were backgrounds,

taken prior to the administration of enriched doubly labelled water, initials with expected values of

δ2H ≤ 15000‰, δ18O ≤ 1200‰, and δ17O ≤ 350‰, and finals with isotope enrichments between

the initial and background values.

Set-up

55

Isotope measurements

We measured all samples using both IRMS and LS. Samples were regularly alternated with

our working standards in order to calibrate the instruments and check their performance. The order

of the measurement of samples and working standards in both systems was determined such that

large steps in enrichment (read: memory effects) were avoided.

The IRMS measurements were carried out in four short periods (5-10 days) between

February and July, 2000. The LS measurements were carried out in 16 days in July, 2000.

Isotope Ratio Mass Spectrometry procedures

All samples were prepared and measured at the Centre for Isotope Research (CIO) using

routine procedures and standard equipment. For each water sample, four glass microcapillary tubes

were filled, each containing between 10 and 15 µl of water. The capillaries were flame sealed

immediately after filling. The use of these capillaries was dictated by the available instrumentation

and was in no way essential to the method. To obtain the isotope ratios, the capillary tube was put

in an on-line vacuum distillation system, mechanically broken and cryogenically frozen into a quartz

vial. The Epstein-Mayeda equilibration method (Epstein 1953) was used to determine δ18O of the

samples: 2 ml of CO2 gas of known isotopic composition was added to the vial, which was

subsequently kept in a thermostated water bath at 25ºC for at least 48 hours. After this, the

isotopically equilibrated CO2 was removed for IRMS analysis and the remaining water was led over a

uranium oven at 800ºC to produce H2 (Bigeleisen 1952). The 18O/16O and 2H/1H isotope ratios of the

CO2 and the H2 gases, respectively, were determined using dual-inlet isotope-ratio mass

spectrometers: a Micromass SIRA 10 for CO2 and a SIRA 9 for H2. In this way, we obtained four

independent isotope ratio determinations for both isotopes and for each sample.

Laser Spectrometry procedures

A detailed description of the LS method is available elsewhere (Kerstel 1999, Kerstel 2001b)

In brief, we measured the gas-phase direct absorption spectrum from a water sample in the 2.7 µm

region, determined the strength of the absorption of the different isotopomers, and compared these

to the absorption strengths of a simultaneously recorded reference water spectrum. To record these

spectra, a single mode Color Centre Laser (Burleigh) was scanned over the range from 3664.05 cm-1

to 3662.70 cm-1 in about 2500 steps. During the scan, both the laser power after passage through

the gas cells containing the water vapour and the laser power before the cells was measured using

phase-sensitive detection with amplitude modulation at about 1 kHz. Currently we have four gas cells

available. These are equipped with multiple pass optics to achieve an optical path length of about

20 m. The cells are made of stainless steel (mirror holders) and a glass tube; their volume is about

1 l. They show a memory effect (i.e., contamination with previously measured water) that amounts

to up to about 5% of the difference in enrichment levels between two samples. This implies that

generally the first measurement after a large step in enrichment (for example, 2000‰ for δ2H and

Chapter 2

56

300‰ for 18O) must be discarded. We tried to avoid such large enrichment steps by taking care of

the sample injection order; to this end we used the expected values from the biomedical experiment,

in agreement with common IRMS procedures (where the 2H preparation system produces even

larger memory effects: see Calibration). The glass tube of the cell is equipped with a valve that has a

small (1 ml) chamber behind it, the injection chamber. The injection procedure was the following:

After removal of the previous sample by evacuating the cells, we flushed all four of the cells

simultaneously with dry nitrogen gas. Cross-contamination between the cells was avoided by

cryogenic traps between each gas cell and the vacuum pump. After filling the cells with 1 atm of

nitrogen gas, the injection chambers were closed. The cells were then evacuated again, while in the

meantime we injected 10 µl of liquid water samples with syringes through rubber septa into all four

of the injection chambers. After closing the main pump valves the injection chambers were opened

and the water evaporated, along with the nitrogen, into the main volume of the cells. The final

pressure was about 13 mbar, well below the saturation vapour pressure of water at room

temperature. The laser started scanning after a five-minute waiting period to ensure that all of the

water had evaporated. The entire sample introduction procedure took fifteen minutes. One gas cell

was reserved for the reference water; of the other cells, one contained a working standard (thus,

giving us a permanent check against standards over the entire measurement period), and the two

remaining cells contained unknown water samples. As an extra precaution, the reference was treated

in the same manner as the samples and refreshed after every measurement to ensure its isotope

ratio could not change as a result of slow mixing with external water or isotope fractionation effects.

The infrared absorption spectra of the waters injected into the four gas cells were measured

simultaneously. For each injection, 12 successive scans were recorded, each taking about two

minutes. A full measurement, including injection and removal of the sample, takes around

40 minutes. The sample throughput for the LS is, thus, currently about 4 measurements (samples

and/or working standards) per hour. All samples and standards were injected and measured (at

least) five times to collect some statistical data and to be able to remove measurements affected by

memory effects. The exact procedure for calculating the raw, uncalibrated, δ-values from the

recorded spectra is straightforward and is described elsewhere (Kerstel 2001b).

Set-up

57

Figure 2.11: Squares represent the (a) δ2H and (b) δ18O IRMS measurements after application of the

known corrections. The solid line is the normalization curve obtained in a linear regression analysis.

Also shown are the residuals (measured value minus fit). The broken line is a least-squares fit to the

raw measurements.

Isotope Ratio Mass Spectrometry calibration

Calibration for both of the IRMS machines was maintained by daily tests with local reference

gases (one at natural abundance, the other enriched) as well as with several local water standards,

in addition to the standards that were specific for this project. For H2, the H3+-correction was

measured on a daily basis and in the current range amounted to up to 12% of the value measured.

Further, a correction for cross contamination up to 0.5% of the value was applied, as described

previously (Meijer 2000). Both of these effects are thought to be well-understood and can be

Chapter 2

58

quantified independently. Therefore, these corrections, together with the conversion from machine

reference gas to the VSMOW standard, were applied before the usual scale expansion correction

(normalization). In the case of the oxygen isotope ratio, corrections were applied for cross-

contamination (smaller than 1%), and the water correction (for the amount of oxygen in the added

CO2 causing dilution of the original oxygen in H2O; between 10 and 20%). Again, these corrections

were applied before conversion to the VSMOW scale and the final scale expansion or normalization.

The scale expansion correction for the H2 and CO2 IRMS machines was similar to the one

recommended by the IAEA for the natural range between SLAP and VSMOW (Gonfiantini 1984, Hut

1986). However, in the current enrichment range, the usual VSMOW-SLAP normalization would lead

to a large (and inaccurate) extrapolation and was, therefore, not applied. Instead, we used our

series of 5 gravimetrically determined standards to define the scale in a linear fit with equal

weighting factors. Unfortunately, the δ2H measurements involving the least enriched standard had to

be rejected because of an excessive memory effect in the H2-gas preparation system. Figure 2.11

shows the IRMS measurements before and after application of the known corrections mentioned

earlier. The figure also gives the residuals of a linear regression analysis. The slope of this fit is the

scale expansion factor, which is presented in Table 2.6.

Table 2.6: Normalization factors for IRMS and for the different sample cells in the case of LS.

IRMS Cell I Cell II Cell III

ξ(H218O) •102 2.01 (8) 1.60 (7) 1.33 (7) 1.60 (9)

ξ(H217O) •102 -- 3.5 (2) 3.99 (2) 3.3 (2)

ξ(2HOH) •102 3.2 (2) 1.3 (3) 0.5 (3) 0.2 (5)

ψ(2HOH) •103 - 1.6(3) 2.6(3) 2.5(4)

The errors between brackets represent one standard deviation in units of the least significant digit.

δ ξ δ ψ δcalibrated = + ⋅ + ⋅( ) ( )* *1 2, with δ* the measurement value after initial

corrections (see text). The quadratic term applies only to 2HOH.

Laser Spectrometry calibration

In contrast to IRMS, LS does not require large corrections of the raw measurement values.

The only correction applied before scale normalization was due to the effect on the final

measurement of small pressure differences between the gas cells. This correction has been

described in detail in the literature (Kerstel 1999, Kerstel 2001b) and, with proper sample

introduction, amounts to no more than 2‰ and 6‰ in terms of the δ-values for the oxygen isotope

ratios (δ17O and δ18O) and δ2H, respectively. Note that this is much smaller (~0.1%) than the

corrections that were applied in the mass spectrometer case. Again, the gravimetric working

Set-up

59

standards were used to determine the correct scale expansion factors, now also for δ17O. It turned

out that for 17O and 18O, a linear normalization is sufficient, but for 2H a second order correction was

needed to reduce the residuals of the measurements at higher enrichments. The normalization

factors for the three sample cells differed slightly. For all three of the measurement cells, the

normalization plots and corresponding residuals are given in Figure 2.12. The scale expansion factors

are listed in Table 2.6, together with the corresponding IRMS corrections.

2.4.2.2 Results and discussion

From Table 2.6 it is evident that IRMS requires a still substantial scale expansion. For both18O and 2H, IRMS initially underestimates the true isotope ratios. The magnitude of the scale

expansion factor found here in the high enrichment regime is similar to the one found in the natural

isotope abundance range (VSMOW-SLAP normalization). Although this normalization has become

common practice, the underlying physics is not understood. That no quadratic component is

necessary to obtain a good fit in the normalization process may simply be due to the missing data at

the lowest end of the scale.

Despite the very different and conceptually much simpler measurement technique, LS turns

out to need a quantitatively similar normalization (see Table 2.6). Surprisingly, the scale expansion

factor for 17O is nearly twice as large as for 18O, whereas the opposite might be expected if residual

isotope fractionation effects were to blame (Meijer 1998). Moreover, fractionation effects are, in

general, much larger for 2H than for 18O and certainly when compared to 17O, are in apparent

contradiction to the data. Therefore, we strongly believe that the results indicate that our series of

gravimetric standards contain 2% to 4% less 17O than calculated from the specifications provided by

the supplier of the starting material. To a lesser extent, the same may be true for 18O. This should

not surprise us, considering the difficulty in determining the absolute oxygen isotope concentrations

(see Standards).

In any case, for the DLW application, the absolute value of the isotope ratios is not

important: the calculated energy expenditure depends on the ratio of initial and final isotope

concentrations (above background) and requires only a good linearity of the scale. The latter is

assured by the calibration and normalization procedure carried out here.

The normalization factors of the sample gas cells are sensitive to the optical alignment

causing small differences between the three sample gas cells. This is almost certainly due to residual

etalon fringes (interference effects) in the optical system that persist despite the use of

antireflection-coated, wedged optics and careful alignment.

Chapter 2

60

Accuracy

A good measure of the accuracy of the entire sample handling and measurement procedure

is the root-mean-square (rms) value of the residuals of the standards (i.e., calibrated measurement

value minus gravimetric value).

For the IRMS measurements on the working standards, the rms values of the residuals, as

they appear in Figure 2.11, increase in size with enrichment. For δ18O, the values increase from

about 1‰ to 3‰ over the range of enrichments studied here, whereas for δ2H, the rms values of

the residuals increase from 17‰ to 68‰ (note that the measurement of the lowest enrichment

standard was not included).

The rms values of the residuals of the LS measurements, as they appear in Figure 2.12, are

also increasing in size with enrichment. Their values range from about 1.5‰ to 3.5‰ for 18O, from

3‰ to 55‰ for 2H, and from 1‰ to 2‰ for 17O. Especially if one excludes the measurement at

the highest enrichment level (which appears to break with the trend established at the lower

enrichment levels), LS performs significantly better for 2H than IRMS.

For both IRMS and LS, all unknown samples are corrected and normalised as described for

the standards.

In Figure 2.13 we directly compare IRMS and LS, for all measured samples (standards and

unknowns). From the preceding, it may be clear that over the range spanned by the standards, the

two methods agree within their precisions. However, at the even higher enrichment levels

encountered in the δ2H measurements of the unknown samples, the LS method gives slightly higher

values than IRMS. This may indicate that IRMS, just as LS, needs a quadratic component in its

normalization of the δ2H scale in addition to the one already applied for cross-contamination.

Precision

The precision is given by the standard deviation (SD) of repeated measurements on the

same sample (standards as well as unknowns). Their values increase with increasing enrichments,

just as the rms values do. The SD of the IRMS measurements ranges from about 1‰ to 5‰ for

δ18O, and from 5‰ to 100‰ for δ2H. For the LS measurements, the range for δ18O is from 1‰ to

4‰ and for δ2H from 5‰ to 60‰. LS can also measure δ17O, and its precision ranges from 1‰ to

2‰. These are essentially the same numbers as those obtained in the previous section for the

accuracy, which indicates that the calibration procedure is not limiting the overall accuracy of the

method.

Set-up

61

Figure 2.12: Squares represent the (a) δ2H, (b) δ18O, and (c) δ17O LS measurements after application

of the known differential pressure correction. The solid lines are the normalization curves obtained in

a linear regression analysis (three, one for each sample cell, but overlapping at the current scale).

Also shown are the residuals (measured value minus fit).

Chapter 2

62

Figure 2.13: (a) δ2H and (b) δ18O values of all LS measurements vs the corresponding IRMS values

as well as their differences (residuals). Circles represent the measurements of working standards;

squares give the measurements of unknown samples. Each point represents the mean of repeated

runs (LS, 5; IRMS, 4) involving the same sample, the error bar gives the corresponding standard

deviation, and the solid line represents the line with unity slope (y=x).

Further improvements

In principle, the ability to measure δ17O with the LS system, could be used to extend the

DLW method to a triply labelled water (TLW) method. The idea is to use the known difference in

fractionation behaviour between 17O and 18O to estimate the fractional water turnover by means of

evaporation (as opposed to water loss due to, e.g., urine). This has been shown to work with tritium

as the third isotope, but this has not found widespread acceptance because of the radioactive nature

Set-up

63

of this isotope (Haggarty 1988). Unfortunately, however, we estimate that the required accuracy of

the oxygen isotope measurements is almost one order of magnitude beyond our current level.

Although the memory effect of the LS method is smaller than that encountered with H2-gas

production by reduction of water over uranium, as used in our IRMS laboratory, it is still limiting the

ultimate accuracy for δ2H, as well as δ18O, measurements, especially at high enrichment levels. We

expect that this effect can be reduced dramatically by moderate heating of the gas cells (up to 40˚C

or 60˚C). We are currently making preparations to do so.

The sample throughput can be further improved by automation of water injection and

evacuation sequence and/or by increasing the number of gas cells. The laser provides enough power

to add many more cells and this is relatively cheap when compared to the costs of an IRMS system.

The only preparatory step used is the distillation of blood samples prior to measurement. In

the IRMS sample preparation system, this is usually done in an on-line set-up, which can easily be

connected to our gas cells, as well. That would eliminate the extra labour of off-line distillation and a

possible source of errors. The degree of enrichment that can be measured with the LS method for 2H

is currently limited to about 15000‰. In biomedical experiments on small animals exhibiting very

high water turnover rates, initial enrichments for deuterium of up to 50000‰ are sometimes

encountered. With so much 2HOH present in the gas cell, the absorption of the corresponding

transition will make the sample optically practically black, leading to a serious decrease in accuracy

of the 2H/1H isotope ratio determination. However, by switching to a nearby and much weaker 2HOH

absorption, we should be able to extend our measurement range upward to values satisfying

biomedical requirements in all cases and with acceptable accuracy.

The most fundamental improvement would be the replacement of the FCL laser system with

a diode laser. This would not only have technical advantages, which would be expected to lead to

improved precision and higher sample throughput, but would also result in a more compact and

cheaper apparatus. We are currently investigating the possibilities of using such a diode laser.

2.4.2.3 Summary of measurements in the enriched regime

The LS system is a reliable tool for measuring the stable isotopes in water from biomedical

applications in a wide range from natural up to 15000‰ for δ2H, 1200‰ for δ18O, and 350‰ for

δ17O. The accuracy and precision of isotope ratio determinations with LS are comparable to those of

IRMS for δ18O and are clearly better for δ2H. Sample throughput of the LS apparatus (30 to 40

measurements per day) is comparable to that of our IRMS laboratory but can be increased easily and

at moderate cost. The biggest advantage of the new system is its conceptual simplicity and the

absence of chemical sample pretreatments that are necessary with the traditional IRMS method. Also

new is the possibility of measuring 17O, which conceivably may be used in a triply labelled water

method, once further improvements in accuracy have been made.

Chapter 2

64

2.5 Current status

In this paragraph, the limiting factors of the system and the causes for the mentioned

measurement uncertainties are described, together with some of the minor and major improvements

that can be made to the LS set-up.

The existing drawbacks of the current LS set-up can roughly be divided into three groups:

The laser (apparatus) related problems, the isotope (fractionation) related ones and the problems

with the memory effect of the system. Some relatively easy improvements to the set-up can be

made. These will especially reduce fractionation and memory effect.

2.5.1 Apparatus related

In most experiments, we have performed 8 to 15 subsequent scans in each series (separate

sample introductions) with about 8 MHz or 16 MHz step sizes. The results suggest that the limit in

precision (~0.6‰ for δ2H, ~0.5‰ for δ18O and ~0.3‰ for δ17O for natural samples and to 60‰,

4‰ and 2‰, respectively for enriched samples as described in Chapter 3) for both 17O and 18O may

not always be reached yet. In other words, performing more scans might slightly improve the single

measurement (series) precision of a series for the oxygen isotopes. Thus, the apparatus itself is the

limiting factor. The precision for deuterium measurements, however, is limited by fractionation

problems as will be discussed in the next paragraph. We have chosen to make this number of scans

as the best compromise between measurement time and precision.

The greatest limitations of the measurement system come from the color center laser (FCL).

Tuning through adjustments of the macroscopic elements in the cavity gives rise to amplitude and

frequency noise on the output. Therefore it is necessary to divide out the noise, using a separate

power detector. Many of the mechanisms, which are responsible for the output noise, are at least

dependent on temperature (but other variables may also be important). They effect the mode quality

of the laser beam and the characteristics of a scan and therewith the measurement results. The rest

of the set-up can be sensitive to the laser alignment as well. Beam–splitters with parallel surfaces

can cause optical interferences (“fringes”). Although all these have been replaced by wedged optics,

some residual fringes are sometimes observed, probably coming from the laser itself (caused by

feedback) or the gas cells. If the position or amplitude of these interferences changes in time (e.g.,

temperature induced), the measurement will be influenced. Gas cell alignment is stable, as is

detector alignment. Although the procedure to fit the recorded spectra is in first order approximation

insensitive to some of these effects, a dependence is observed. However, if all precautionary

measures are being taken, the system is very stable and routine measurements can be performed.

Set-up

65

The above limitations all influence the precision of the method. The speed with which

measurements can be done, however, is also limited by the apparatus. As described in Chapter 2,

the FCL needs to be scanned by tuning three different elements at the same time. With the present

computer interface the scan speed is limited to about 25 steps/s. A typical scan with a step size of

about 8 MHz thus takes about 3 minutes. Improvements in computer software and interfacing can

slightly reduce the time needed for a single scan. Moreover, the sample throughput could be

increased by automating the sample introduction and pumping procedure. It will then be possible to

build a continuously working system.

2.5.2 Fractionation related

In contrast to the 17O and 18O measurements, the data suggest that increasing the number

of scans within a series will not yield a higher precision for 2H abundance measurements. In the

latter case, the fractionation that occurs is the limiting factor, instead of the noise of the

measurement system. Fractionation can occur during or after introduction of the sample in the gas

cell, but we may assume that all gas cells behave in the same way, since their design and

preparation are the same. Possible cross-contamination of the different gas cells is effectively

prevented by the use of separate cryogenic traps for each cell. Consequently, fractionation must be

due to sample handling (and sample introduction). In the current measurement scheme, all samples

are removed and refreshed after each series, including the local standard in order to avoid any

problems with vacuum integrity of the reference cell. Not replacing the local standard after every

series could lead to an improvement in precision.

In order to be able to measure pure blood samples, an improvement could be made by

building a system to introduce the samples directly from their capillaries into the gas cells, without

using a syringe. This on–line distillation will eliminate the distillation and sample introduction steps

and might thus prevent any fractionation in this step. The variability in the introduced amount of

water must then be adjusted or corrected for.

Several factors can influence the mode quality and scanning behaviour of the FCL. Possible

factors are variability in temperature, humidity and air pressure, and vibrations of the floor/building

or the cooling water pump. These, but probably also other differences in the scan or beam

characteristics (e.g., single mode quality) cause differences in the scan to scan measured δ-values,

and thus influence the obtained precision within a series.

Obviously, the optical set-up is always aligned with great care. Besides the laser, the other

elements in the beam can cause problems too, for example by way of optical interferences

(“fringes”). As described before, this is avoided by using wedged optics everywhere. Furthermore,

drifts and uncertainties in δ-values due to vibrations or back reflections of optical elements, are other

possible sources of errors.

Chapter 2

66

Long term drift from the set-up might also cause a change in the measured values, thus

causing a lower accuracy over an extended period. Since there are so many factors that influence

precision, it is very hard to quantify their individual contributions.

For the spectral region we selected, it turns out that uncertainties increase considerably at

enrichment levels higher than about δ2H ≥ 15000‰, δ18O ≥ 1200‰, δ17O ≥ 1000‰. In this case,

the absorptions in the gas cell become too strong to be able to measure the intensity of the

transmitting light accurately (see Equation 2.2). In addition, for H218O and H2

17O increasing overlap

with neighbouring lines becomes more problematic. These high enrichments are sometimes used in

biomedical applications. To be able to measure δ2H in samples with such high enrichments, we can

use the two small lines (#4 and #6 in Table 2.1). Their intensity at natural abundance levels is low

enough to permit a 50-fold increase.

2.5.3 Cell offsets

Extensive isotope fractionation effects for adsorption-desorption processes at the walls are to

be expected, in particular for hydrogen. However, such fractionation is only observable to the extent

that the two gas cells behave differently. Only due to such a difference, injecting exactly the same

water sample in both cells (with the same sample history) would result in a δ-value significantly

different from zero (“offset”). As described before, we do indeed observe offsets between cells, but

since we do not find a fixed relation between the 17O and 18O offsets (as one would expect if

fractionation effects are the cause) it can be excluded. Thus, the cause of these offsets must be

something else. Moreover, the fractionation of 2HOH would likely be about 8 times larger than that of

H18OH as it is in many equilibrium processes (Chapter 1). Consequently, the precision for 2H would

be 8 times worse than for 18O, but that is not observed. Both observations proof that the gas cells do

not behave differently from each other as far as their wall-fractionation is concerned. As mentioned

before, we have reason to believe that different optical alignments are the reason of the observed

offsets. It should be noted again that fractionation between the liquid and gas phases of water is

avoided by working at a substantially lower pressure (13 mbar) than the saturated vapour pressure

(32 mbar at room temperature): All injected liquid water quickly evaporates inside the evacuated gas

cell.

In the case of 17O and 18O, the precision can still be improved (although not by much) by

increasing the number of laser scans in one run (i.e., increasing the measurement time). For δ2H the

minimum standard error has already been reached at our normal working conditions, indicating that

the precision in this case is limited by other errors instead of the intrinsic precision of the apparatus.

These can be accounted for by differences in the (long term) sample history of the different cells,

which can after all introduce different behaviour of the cells. This so-called memory effect will be

discussed in the next paragraph.

Set-up

67

The introduction procedure could cause the accuracy to become worse than the

measurement precision as well, if, for example, the injection syringes introduce a memory effect or if

the vacuum integrity of the septum is not perfect. Since these effects, if they exist at all, are of a

highly variable nature, it is hard to quantify them. We do not have evidence, however, that they

would be limiting at all.

2.5.4 Memory effect

In contrast to what is discussed in the previous paragraph, the gas cells will not behave

equally in the case that the sample history of the sample and reference cell has been different.

Inherent to the nature (“sticky”) of the water molecule, the LS measurements are inflicted with a

serious memory effect, in particular in the case of δ2H. We can define the memory effect as the

interaction of the newly introduced sample with water that remained in the gas cell after the

preceding measurement (mostly adsorbed on the walls of the gas cell). It basically leads to a mixing

of “new” and “old” water in the gas phase of the sample cell. The stickyness of the water molecule is

also the reason that attempts to measure the isotope abundance ratio of a water sample directly

using IRMS, were only marginally successful (Wong 1984). In order to reduce this problem in our

set-up, we make sure that no large steps in isotope enrichment of the samples is made in successive

measurements.

The adsorption of water on the walls of the gas cell is referred to as physisorption (Pulker

1984). From Figure 2.14, it appears that two distinct pools of remaining water (despite the pumping

and flushing procedures) can be distinguished, which mix or exchange isotopes with the new sample

at different time scales. We propose the following two mechanisms (which act at different time

scales). The first mechanism is the fast mixing with adsorbed water on the walls. It is a physical

process and the mixing with the “new” water occurs instantaneously on the time-scales of repeated

measurements and can be seen in Figure 2.14 as an offset of the first measurement in each series,

but it is mostly pronounced in the first series. Although not shown in this figure, the same process

occurs for 2H and 17O. The second mechanism that can be observed in Figure 2.14 is a slower

process acting on a time scale of hours. In our opinion, it must be due to the mixing with less

accessible, adsorbed, water molecules. It can be recognised in Figure 2.14 by the gradual rise

(trend) of the subsequent scans during the first measurement series. This mechanism is also

observed for all of the three isotopes.

The difference between both processes might be explained by assuming that a number of

molecular layers of water are adsorbed on the walls of the gas cell. These behave as a rigid structure

and only the upper layers are easily accessible and therewith available for the fast exchange. The

deeper layers must then be responsible for the slower processes.

Chapter 2

68

Figure 2.14: Repeated measurements of δ18O of VSMOW in time. The time axis is approximate. Note

that after the fourth series, the sample was left in the cell overnight and the time-axis is broken.

With each new series fresh sample and reference water was injected. The previous sample was

TLW–4: δ18O ≈ 850‰.

From Figure 2.14 it is clear that (for 18O) the memory effect has almost disappeared after

about 8 subsequent sample introductions. The same is true for 17O. Consequently, due to the slower

mixing mechanism with the less accessible layers, it is not sufficient to introduce a sample and

remove it immediately: Some waiting period (hours) must be respected for the system to reach full

equilibrium, but overnight equilibration is favourable (the right hand side of Figure 2.14).

Measurements suggest that the amount of water that remains in the cell, even after thorough

evacuation is about 7% of the 10 µl sample size that is most often employed. Indications exist that

the pumping procedure removes some water from the surfaces: Immediately after opening the gas

cell’s injection valve a peek in the gas cell pressure is observed. However, within seconds the

pressure drops to the final cell pressure. Probably some of the sample has found a free hydrophobic

position at one of the inner surfaces of the cell. Changing the glass tube of the cell, before making

the large step in enrichment has showed qualitatively that the memory effect is (also) caused by

adsorption onto stainless steel and not to glass adsorption only. It is in our set-up not possible to

0

10

20

30

40

50

60

0:00 1:00 2:00 3:00 20:00 21:00 22:00 23:00

δδδδ18O

(‰

)

Time of measurement (h)

Set-up

69

measure directly whether the glass plays an important part as well, but due to its material properties

this can be expected.

We propose an additional (third) mechanism for the memory effect for 2H. This involves a

chemical process, namely the exchange of hydrogen (and deuterium) atoms of the sample water

with the cell walls. The glass of which our gas cells are made of, has Si–O–H groups at its surface

and the hydrogen atom is exchangeable with a 1H or 2H atom of sample water, thus introducing an

additional memory effect. This mechanism acts on longer time-scales than the physisorption

processes, probably since the binding sites are not easily accessible for the water vapour of the fresh

sample (covered by layers of adsorbed water). This process is referred to as chemisorption. In

Figure 2.15 it is not easy to distinguish it from the physisorption process, but it is illustrated by the

fact that a larger number of series shows a significant memory effect compared to Figure 2.14.

Figure 2.15: Repeated measurements of δ2H of VSMOW in the same series as presented in

Figure 2.14. The previous sample was TLW–4: δ2H ≈ 10800‰. There is no evidence that the

memory of the cells has disappeared, even after eight subsequent sample replacements.

To be able to compare the behaviour of the memory effect of the two isotopes in more

detail, the individual measurement values of δ2H were divided by those of δ18O. See Figure 2.16. In

0

200

400

600

800

1000

1200

0:00 1:00 2:00 3:00 20:00 21:00 22:00 23:00

δδδδ2H

(‰

)

Time of measurement (h)

Chapter 2

70

the first series, δ2H/δ18O increases faster than the enrichment ratio of the previous sample

(δ2H/δ18O ~ 13) would suggest. However, after a few series, the ratio approaches the expected

value of 13. Within each series, the mixing ratio declines, indicating that the fast exchange proces for

δ2H decreases faster than that of δ18O. After the sample was left in the cell overnight, the mixing

ratios have (on average) values around the expected value, but the mixing ratio increases within a

measurement series. This is an indication for the slower mechanism caused by chemisorption, the

role of which becomes significant now the fast initial mixing is completed.

Figure 2.16: Ratio of δ2H and δ18O for the measurements in Figure 2.14 and 2.15. First, δ2H

increases relatively slower than δ18O. After the overnight waiting time, however, the increase in δ2H

is stronger. The horizontal line is indicating the enrichment ratio of the previous sample. The scatter

becomes larger in time, since the measured δ-values become close to zero.

In order to account for memory effects, the data analysis software checks whether the

subsequently measured δ–values show a clear trend. If such a trend is stronger than certain limiting

conditions, it is accepted as being real. A linearly back–extrapolated value to the moment of injection

is accepted as the series result, instead of the mean of the measurements in the series. This has

proven to yield better values, but the very fast component of the physisorption can not be corrected

for. Therefore, the first measurement after an enrichment step must be neglected after large

enrichment steps. However, it can be used to separate the two memory effects caused by

0

5

10

15

20

25

30

35

40

0:00 1:00 2:00 3:00 20:00 21:00 22:00 23:00

δδδδ2H

/ δδδδ1

8 O (

‰)

Measurement time (h)

Set-up

71

physisorption. In Figure 2.17, the natural logarithm of the back-extrapolated values of each series is

taken, and plotted against the series number. For 18O the series values reach values that do not

significantly deviate from zero after 1 or 2 series and the decrease is probably logarithmic. For 2H,

initially a similar decrease is observed, until the chemisorption effect gets a significant influence. Due

to this additional mechanism, the linear back-extrapolation does not work as well as for 18O. A

second process seems to become the limiting step.

Figure 2.17: Natural logarithm of the initial value of each series as calculated from linear back-

extrapolation. For 18O (squares), one process exists, for 2H (circles) a second process becomes

limiting after a few scans.

To reduce this complex memory problem, we apply a hydrophobic coating that is applicable

to both glass and stainless steel. The coating (commercially available, PS-200) contains molecules

with a polar head, which form covalent bonds to the silanol groups of the glass and the polar sites of

the stainless steel surfaces. The long apolar tail makes the coated surface hydrophobic. Application

of the coating only involves cleaning, shaking and rinsing steps of the material with readily available

chemicals and means. To our best knowledge, this is the best hydrophobic coating that is easy

applicable to both glass and steel. The manufacturer gives no further specifications, but for water in

liquid form we can visually observe an enormous effect of its application on a glass beaker.

-6

-4

-2

0

2

4

6

8

1 2 3 4 5

ln δ18O

ln δ2H

ln( δδδδ

-val

ue)

serie #

Chapter 2

72

Despite of the hydrophobic coating we still observe a memory effect in our measurements.

In fact, it is only decreased to about half of the magnitude without coating. It was shown, by

replacing an entire gas cell tube, that this is especially due to water adsorption at the stainless steel

parts of the cell. The effect is again more severe for 2HOH than for the oxygen isotopes, partly due

to the fact that its natural range is bigger and high enrichments are more common here, but

probably also to the fact that deuterium is actively incorporated (exchanged) in the surface of the

cell.

With increasing temperature, all of the exchange reactions are expected to speed up

(Deyhimi 1982, Morrow 1991). Working at elevated temperatures can thus reduce the equilibration

time of the physisorption and process, making less flushing procedures needed. Moreover, by

elevating the temperatures the evacuation procedure might become more efficient, thus leaving less

water behind in the cell. In addition, the chemisorption exchange process is also expected to speed

up, thus taking less time to fully equilibrate.

In the present set-up, the remaining memory effect is under control if we are carefull with

the order in which the samples are introduced. The largest step in enrichment that can be made

without flushing the cells with sample first, is estimated to be in the order of 2000‰ for δ2H and

500‰ for δ18O when already working in the highly enriched regime. When working in, or just above,

the natural abundance range, the largest steps that can be made are in the order of 200‰ for δ2H

and 50‰ for δ18O. These values differ from each other, since the errors (caused by memory effect)

must be compared to the measurement precision.

Again, one should keep in mind that in traditional IRMS sample preparation systems

(especially for 2H) severe memory effects occur as well. Still, the practical accuracy of the LS is

limited by the memory effect.

Note again that memory effects of both kinds would be totally unimportant for the

measurement result as long as the cells behave equal and have the same sample history. All

fractionation effects will then cancel out. In practice, however, the reference cell will hold the same

water over an extended period of time, while the contents of the sample cells often change.

2.5.5 Interference with other species

From the HITRAN 1996 database (Rothman 1998) we know that almost no other natural

occurring molecules absorb in the chosen spectral region. The only exception is 12C16O2, which shows

an absorption profile at 3663.851 cm-1, very close to a line of 2HOH (3663.842 cm-1, #7). The CO2

line has an intensity of 1.0.10-21 cm.molecule-1 (compared to 1.2.10-23 for the 2HOH line) and has

therefore in normal air (which contains ~2-3% H2O and ~0.04% CO2) about the same intensity as

the 2HOH line. Thus, we have to be careful to avoid contamination of CO2 in the gas cell. On the

other hand, if we calculate the maximum possible amount of CO2 in a typical LS water or blood

Set-up

73

sample, it is not a problem whatsoever (about three ordersof magnitude weaker line). The existence

of this CO2 absorption line should be kept in mind when we start injecting blood samples for

biomedical purposes in the near future.

2.6 Numerical simulations

To get an indication of the reliability and robustness of the described approach and

calculations, we have tested the total data analysis procedure on simulated data. To this end we

used synthesised sample and reference spectra. These numerical simulations let us easily isolate the

various possible sources of errors and may enable the identification of the physical effects that cause

the measured δ’s to deviate from the true values. In the next paragraph the influences of spectral

overlap will be discussed, the differential pressure effect and base-line and noise, determined by

simulation of the absorption spectra.

2.6.1 Spectral overlap

In order to investigate the effect of partially overlapping spectral features (lines), absorption

spectra were calculated with the line parameters of Table 2.1 (and the other lines present, see

Figure 2.2). The absorptions were simulated by a Voigt line profile (Whiting 1968) with a total half-

width-at-half-maximum (HWHM) of 0.008 cm-1 and a 0.0053 cm-1 HWHM Gaussian Doppler

contribution. These are typical values for the spectra as routinely measured. All of the line intensities

in the reference sample, as well as the intensity of the H16OH line in the sample, were kept constant,

while those of the other lines in the sample spectrum were systematically and individually changed to

simulate samples with a range of δ2H, δ17O and δ18O values. No noise was added to the synthesised

spectra. The results show that the input δ-values are very well recovered by the data analysis

procedure. The observed deviations ∆(δ) are small and proportional to the δ – v a l u e :

δ = δ∗ + ∆(δ) ≅ δ∗(1 − χ), where δ∗ represents the recovered δ–value. These ∆(δ) shifts reach values of

∆(δ2H) = –16‰ for δ2H = 10,000‰, ∆(δ17O) = –2.5‰ for δ(17O) = 1000‰, and ∆(δ18O) = –1.2‰

for δ(18O) = 1000‰. In principle, these corrections should be applied to all measurements, but since

they are small compared to other corrections and a cell-specific stretching is needed anyway, it can

be included in the stretching factor. Further, due to the proximity of the H17OH line to two smaller2HOH lines, and their overlap with the H16OH line, a (significant) cross-correlation between the

experimentally determined δ17O, δ18O and δ2H values is expected. Fortunately, the simulations show

that the data analysis procedure is quite insensitive to this effect. The largest effect is seen in the

simulations for δ2H, but even then the δ17O and δ18O values react to a change in δ2H from 0 to

10,000‰ with a shift of only 0.2‰ and 0.3‰, respectively. This is insignificant with respect to

other sources of error that play a role at such large enrichment levels.

Chapter 2

74

In conclusion it can be said that the fitting procedure is reliable and gives a good reflection

of the true values.

2.6.2 Differential pressure effect

The pressure dependence of the calculated δ–values was also simulated, at first for identical

sample and reference waters. As expected, no effect is observed of changing the Lorentzian

component of the line profile by ±20% (changing the total line width by roughly ±10% from

0.008 cm−1 HWHM), as long as the line widths in the sample spectrum are the same as the

corresponding line widths in the reference spectrum. The fitting procedure is thus insensitive to the

exact amount of water, which is injected. However, varying the line widths in the sample spectrum

by an amount ∆Γ=Γs−Γr, while keeping the line widths Γr in the reference spectrum fixed (thus

simulating different amounts of water in different cells), changes the calculated (apparent) δ-value.

The changes are in good agreement with the experimental observations (Figure 2.9).

-40

-30

-20

-10

0

10

20

30

40

-100 -50 0 50 100

δ(18O)

δ(17O)

δ(2H)

δ (

‰)

∆Γ/Γr (‰)

Figure 2.18: Dependence of the apparent δ-values from the line width difference between the

sample cell and the reference cell, derived from numerical simulations.

Set-up

75

Figure 2.18 shows the simulated slopes ∂(xδ)/∂(∆Γ/Γr) for the three isotopes. In this case,

both sample and reference gas cells contain water of identical isotopic composition. The calculated

slopes of Figure 2.18 are in reasonable agreement with the measured slopes of Figure 2.9. See also

Table 2.7.

In addition, the differential pressure induced δ-shifts turn out to be dependent on the

amount of isotopic enrichment. Since the samples in practice are occasionally strongly enriched, this

effect may be important. The corrections of Figure 2.18 were therefore re-calculated with simulated

spectra of strongly enriched samples (up to 1000%, 1000%, and 10,000‰ for δ17O, δ18O, and δ2H,

respectively). The changes in the slopes ∂(xδ)/∂(∆Γ/Γr) turn out to be proportional to xδ. Moreover,

the differential pressure correction approaches zero for an isotope-free sample, for which xδ = -1.

Thus: ∂(xδ)/∂(∆Γ/Γr) = γ⋅(1+xδ). As can be seen in Table 2.7, the simulated values of γ agree

reasonably well with those determined experimentally.

2.6.3 Realistic base-line and noise

In order to investigate the effect of (detector) noise and residual base-line modulations

(due to optical interferences), experimental empty gas cell spectra were added to the synthesised

spectra. The addition of realistic noise enables the determination of the intrinsic precision of the

method or apparatus. That is, without taking into account external effects, such as temperature

drifts, sample introduction errors, and isotope fractionation due to wall adsorption. Inclusion of the

experimentally observed base-line modulations lets us calculate the δ-shift, βcalc, based on this

account only (see Table 2.7). Note that these simulations are based on real measurements,

including all problems with the laser and optical system. The values for β can therefore be

considered as a reliable indication (value changes with short term alignment) for the values to be

expected. From Table 2.7, it can be seen that typical values for the offset, only due to laser and

optics, are around 1‰. Comparable values are always found in experiments, again indicating that

the cell-offset is not an isotope related phenomenon. Instead, alignment is very important for

reducing its absolute values. The typical uncertainties in this number, the standard deviation, are

up to 1‰ for the given set of data. This shows that noise is limiting the performance.

2.6.4 Round up

The results of these exercises can be summarised as follows:

δ β δ χ γ δ= + ⋅ −( ) − ⋅ +( )* *1 1∆ΓΓr

(2.14)

Chapter 2

76

where δ is the true δ-value of the sample (with respect to the particular reference used in the

measurement) and where δ* represents the measured, apparent δ-value of the sample. The

numerical values of the coefficients β, χ and γ are summarised in Table 2.7. For the correction of

the measurement results the latest experimentally determined values of the zero-offset β (since it

changes with alignment) and χ (since it can not be distinguished from the stretch factors) were

always used, but the calculated values of γ (since it is an intrinsic correction of our approach that is

quantitatively understood) were applied.

Table 2.7: Calculated correction coefficients

δ2HOH δH17OH δH18OH

βcalc -2.2 (8)·10-3 -0.1 (6)·10-3 -0.4 (6)·10-3

γexpt 0.016 (17) -0.330 (8) -0.248 (16)

γcalc 0.066 -0.270 -0.212

χcalc 1.6·10-3 2.5·10-3 1.2·10-3

The values in brackets represent one-sigma errors in units of the last digit. The superscripts “calc”

and “expt” refer to calculated and experimental determined values.

The intrinsic precision of the method is given by the standard deviation of β, which is

dependent on alignment. The best accuracy is determined by the values of χ and γ.

2.7 Other attempts to improve precision and accuracy

In this paragraph, some of the different set-ups and approaches that were tried will shortly

be described. These were not successful enough to integrate into the current system, but still worth

mentioning. Only more fundamentally different ideas are described here and not the regular

developments or automatisation or small modifications in, for example, settings in software or the

electronics. Most often, the results of the efforts to different approaches turned out to be not good

enough for our demands on precision. The mentioned attempts are not necessarily in chronological

order.

First, we have started with two gas cells. All of the early set-ups were too bulky to give room

to two more cells. Later, the focus was more on building a compact apparatus. The original idea to

split the main beam in 8 beams of equal intensity was to use three consecutive 50% beam splitters

(in total 6 beam splitters were used). The amount of light available for each gas cell was much

higher in that set-up, but interferences occurred: Wedged 50% beam splitters were not present.

Set-up

77

Moreover, a difference in the beams would exists as some were more often reflected, while others

had a higher number of transmissions through optical elements. Since the light intensity needed is

not a limiting factor, we have later chosen for a serial set-up to circumvent these problems, and thus

providing the possibility to easily enlarge the number of cells.

Originally, we scanned the laser over a spectral region at slightly higher wavelengths than

the section we have finally chosen. Since it appeared not to be necessary to use the stronger H18OH

absorption present in that section, we changed to the currently used region. The advantage is that

this spectral section is shorter and therefore it is easier to scan the laser neatly over the lines.

Originally, we used one chopper for the entire set-up, and a separate detector for each

power and signal channel. Positioning the elements was much easier in this set-up: No choppers are

needed close to the gas cells and the position of the power detectors is free. However, it turned out

that it was needed to cancel or reduce (temperature induced) responsitivity changes from the

detectors by dividing signal and power from the same detector, making separate optical choppers a

necessity. Stabilisation of the FCL output by a feed-back with the Krypton ion laser output power did

not work either, because of the same reason: If one detector signal was kept stable, the others were

not. The same problem arose again when trying to stabilise the FCL output by the use of an acousto-

optic modulator (AOM) and an electronic feed-back loop. On top of this the AOM introduced

additional problems, such as feed-back into the laser, interferences and a change of the polarisation

of the light. All ideas of stabilising the power of the laser beam were therefore rejected. It turned out

that dividing each gas cell signal separately by its own input power measured on the same detector

is the best solution.

The amount of water in the cells has been varied. It is possible to reduce the amount of

water to 3 or 5 µl, however with some loss of precision (Tinge 2001). The attempt to use more than

25 µl water (saturated) introduced problems with condensation of water vapour at the mirrors.

Another attempt was to remove the (10 µl) water sample periodically from the vapour phase

by freezing it with liquid nitrogen or a Peltier element. In this way, it would no longer be necessary

to scan the laser. Instead, the FCL could be put and kept on top of an absorption line and, by

consequently removing and re-introducing the water, isotope ratio measurements could be made.

However, the freezing of the water lasted too long and the results were not good at all (not

surprisingly since we know about the problems with the memory effect). The needed temperature

for efficient freezing was even lower than –40ºC, since the vapour pressure of ice is still too high at

moderate temperatures.

We tried to place the power detector for following the power changes due to the ICE

modulation inside the tuning arm chamber. The signal of this detector is used to electronically lock

the etalon to the cavity (see Paragraph 2.2.2). In principle, this change could improve the quality of

the laser scan, especially at frequencies where strong water absorptions occur, since it removes the

Chapter 2

78

influence of atmospheric absorptions. This modification seems to work, but has to be tested more

extensively.

The detectors have AR/AR coated wedged windows in order to prevent interference fringes.

With flat windows, the reflection of the second surface of the window back to the first and back

again could interfere with the directly transmitted beam. This effect is very small, but we have clearly

observed it with our first detector types and its magnitude is too large to neglect. From the moment

we started using wedged windows we do not observe it anymore. Still, to fully avoid interferences,

we have tried detectors with special 7.5 cm long tubes in between the detector surface and the

window. Because alignment turned out te be very problematic, these tubes have been removed

again.

2.8 Conclusions

In the last years at the Center for Isotope Research a totally new system, based on Laser

Spectrometry, has been developed. It is a very elegant and straightforward method, which is

theoretically well understood: The corrections for the pressure differential are quantitatively

reproduced by numerical simulations, the other described effects can at least be understood

qualitatively. The accuracy of LS after calibration and normalization depends on the enrichment level

of the sample, but it outperforms or at least competes with traditional methods for δ2H

measurements. For δ18O, however, only in the enriched regime it can compete with existing systems.

Its possibility to measure δ17O is, on the contrary, almost unique. Moreover, LS does not require

cumbersome, time-consuming pre-treatments of the sample before the actual measurement.

LS is currently able to measure three samples simultaneously for all of the important

isotopomers in typically 45 minutes, providing sample throughput competitive to traditional methods

using IRMS. The practical limit to the number of measurement lines that can simultaneously be used

is by no means reached yet. LS has shown to produce stable and reproducible results over an

extended period of time. It is therefore ready to be applied to many applications, to begin with the

biomedical doubly labelled water method in order to measure energy expenditure, and the accurate

measurement of natural isotope abundances in ice cores, in order to reconstruct the past climate.

Set-up

79

Appendix : Specifications present set-up

In this appendix all important equipment as used in the described LS system is listed.

Optical Table: Vibraplane model no. 5108-4896-11, Kinetic Systems, Boston, MA 02131, USA

Air cleaning system: 6 MAS 1200, Clean Air, Woerden, The Netherlands

Color Center Laser: FCL-20, serial no. N7261086, Burleigh Instruments, Inc., Fishers NY 14453, USA

Step motor: RS, type 4440-284, Gear box: RS, type 718-896, ratio 1:100, Control: Home built

External Ion Pump: Leybold-Heraeus 85172Br1

Ramp generators: RG-91, Burleigh Instruments, Inc.

Temperature controller: TC-238, Graseby Infrared

Sine generator: Home built

Summing amplifier: Home built

Laser cavity lock: Electronics designed and built by M. Giuntini of the European Laboratory for Non-linear

Spectroscopy (LENS, Firenze, Italy).

Detector: PbSe photodiode, Graseby Infrared, Orlando 12151, USA (for locking ICE to the cavity)

Kr+ laser: 3500 Krypton ion laser, Lexel Laser, Inc., Fremont, CA 94538, USA, 647 nm

Laser Power supply: 3500, Lexel Laser, Inc.

Laser Water Cooling: PD-2, Neslab Instruments, Inc., Newington, NH 03801, USA

He/Ne Laser: 633 nm, + 1 mW, type RC1, Limab

Power Meter: NOVA, Ophir Optonics, Ltd. Jerusalem, Israel (for alignment purposes only)

External 8 GHz etalon: SA-91 etalon assembly, SA-900 four-axis mount and DA-100 detector amplifier, Burleigh

Instruments, Inc.

External 150 MHz etalon: CF/CFT etalon, DA-100 detector amplifier, Burleigh Instruments, Inc.

CFT controller: RC-45, Burleigh Instruments, Inc.

Single mode monitor: Wavemonitor, home built

Wavelength meter (or wavemeter): WA-20IR, Burleigh Instruments, Inc.

Detectors: TE cooled InAs photodiodes 1A-020-TE2-TO66E with special mounted AR/AR coated 1º wedged

sapphire windows, Electro-optical systems, Inc., Phoenixville, PA 19460, USA

Temperature controller: Temperature controller PS/TC-1, Electro-optical systems, Inc.

Amplifiers: Home-built low noise amplifiers

Optical choppers:

651-1, EG&G Signal recovery, Workingham, UK, and model 650, Light chopper controller; SR540,

Chapter 2

80

Stanford Research Systems, Sunnyvale, CA 94089, USA and SR540 chopper controllers

Lock-in amplifiers:

7265 DSP lock-in amplifiers EG&G EG&G Signal recovery

128A, EG&G Princeton Applied Research

Computer: Apple Macintosh PowerPC G3, 266 MHz, 64Mb memory, 66 MHz bus

Software:

National Instruments LabVIEW 5.0.1f1 for Mac

NI-488.2 Configuration utility, revision 7.6.5

CodeWarrior for Macintosh

and a number of home written applications

Interfacing: National Instruments IEEE 488.2 GPIB board (PCI), revision G.

Gas cells:

Home built Herriot type multi-pass cells, operated in the 48 passes (20.5 m) configuration, possibility to tilt both

mirrors

Mirrors: concave (500 mm) mirrors (ø 50.8 mm) protected gold, one has drilled holes (ø 4.0 mm) @ 22 and 12

mm from the center, Molenaar optics, Zeist, The Netherlands

Windows: 2º wedged AR/AR coated CaF2, EKSMA, 2600 Vilnius, Lithuania

Valves: 26328-KA01-0001 / 1318, Demaco, Noord-Scharwoude, The Netherlands

Hydrophobic coating: Glasscad 18, PS-200, United Chemical Technologies, Inc., Bristol, PA 19007, USA

Syringes: 800 series,10 µl, Hamilton Company, Reno, NV 89520-0012, USA

N2: pure, PS-50-A, AGA Gas BV, Schiedam, The Netherlands

Optics:

Mirrors: CaF2, ø 25.4 mm, protected silver or gold, New Focus, Optilas, Alphen aan de Rijn, The Netherlands

and EKSMA

Lenses: CaF2, ø 25.4 mm, AR/AR, focal length from 5 mm to 2500 mm, EKSMA

Beam Splitters: CaF2, ø 25.4 mm, wedged @ 1º or 2º, different reflectivities, EKSMA

Windows: CaF2, ø 25.4 mm, wedged @ 1º or 2º, uncoated, EKSMA

Optical mounts: New Focus Hardware

Pumps: Drytel 31, Alcatel, 74009, Annecy, France

Cryogenic traps: Home built glass cryogenic traps, 45 cm diameter, connected to one main vacuum line (40

mm) and pump.