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Dr Simon R Gibbon AkzoNobel Research, Development & … Gibbon... · 2017. 12. 21. · Akzo formed...
Transcript of Dr Simon R Gibbon AkzoNobel Research, Development & … Gibbon... · 2017. 12. 21. · Akzo formed...
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Clever Characterisation a Different Approach HTE Dr Simon R Gibbon AkzoNobel Research, Development & Innovation [email protected]
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Contents
2 Clever Characterisation for Smarter Formulation
• AkzoNobel • AkzoNobel and Formulation • Reality of HTE • HTE Example 1 – Micro capsule formulation • HTE Example 2 – Polymer solubility
formulation • HTE Example 3 – Sealant elasticity formulation • Conclusions on Characterisation for HTE
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More than 350 years of history and cutting-edge innovation
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KemaNobel established in Sweden. Later, in 1984, KemaNobel merged with Bofors to form Nobel Industries, which in turn was acquired by Akzo in 1994 to create Akzo Nobel
Alfred Nobel founded Elektrokemiska Aktiebolaget, known as Eka. Today, Eka is part of our Pulp and Performance Chemicals business
Akzo formed following the merger of Dutch companies AKU and KZO
Akzo Nobel acquired ICI and changed its name to AkzoNobel
UK company Courtaulds, whose products include hi-tech industrial coatings, acquired by Akzo Nobel
Bofors forge founded in Sweden
Painter and decorator Wiert Willem Sikkens started making Sikkens lacquers in the Dutch town of Groningen
Clever Characterisation for Smarter Formulation
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The world of AkzoNobel*
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North America 15% Mature Europe 37% Asia Pacific 26%
Other countries 4% Emerging Europe 8% Latin America 10%
Revenue by end-user segment Buildings and Infrastructure 42% Transportation 16% Consumer Goods 17% Industrial 25%
Revenue by Business Area Decorative Paints 27% Performance Coatings 39% Specialty Chemicals 34%
Key regions by revenue
* All figures are based on year end 2014 Clever Characterisation for Smarter Formulation
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Paints, coatings and specialty chemicals Leading global paints and coatings company and a major producer of specialty chemicals Consistently ranked as one of the leaders in the area of sustainability Passionate about innovation, with 4,000 scientists at 130 laboratories Committed to society through our brands and hands-on community projects
5 Clever Characterisation for Smarter Formulation
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Our commitment to doing more with less
Sustainability
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Human Cities Making cities more human
Colo
r
Herit
age
Tran
spor
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Educ
atio
n
Spor
t and
leis
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Sust
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bilit
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AkzoNobel and Formulation
8 Clever Characterisation for Smarter Formulation
We make ingredients Speciality Chemicals • Functional Chemicals – chelates, ……. • Polymer Chemicals – anti-oxidants, crosslinking agents…… • Surface Chemistry – surfactants, inhibitors, ……. We use ingredients Performance Coatings • Marine Coatings – ships from oil tankers to ferrys • Metal Coatings – buildings, cans • Powder Coatings – furniture, cars, diggers, electrical cabinets, ……. • Protective Coatings – infrastructure, floating structures, ……. • Speciality Coatings – aerospace, yachts, mobile phones, …… Decorative Paints • Wall paints, wood paints, concrete paint, …….
Basically lots of formulation challenges
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Reality of HTE Why HTE? Sample Space
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297 Identified Raw Materials Blends of 2 gives 44000 combinations x16 - 4 Concentrations of each component x2 pHs (neutral and acidic) x2 processing conditions x4 Ingredient variables – high / low colour / flavour x5 replicates So, only 56.3million experiments to do No HTE - 8 experiments a day = 20,000years HTE - 1 minute an experiment = 107years
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20,000 Years + 1 Ice–Age 100 Years + 500 Years of Neglect = World Heritage Site
Clever Characterisation for Smarter Formulation
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Log (No of Samples)
Log(Information per sam
ple)
Something For Nothing
Nothing For Many Things
Much For Many Things
High Throughput Measurement
Reality of HTE Choice of High Throughput Measurement
Clever Characterisation for Smarter Formulation
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Time
Information /
No of Sam
ples
Real HTE
Non-HTE
Reality of HTE High Throughput Information Delivery
NO
NO
YES / NO
YES
Imagined HTE
Clever Characterisation for Smarter Formulation
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Reality of HTE Smart HTE
HTE does not replace good experimental design HTE needs modelling HTE needs statistical design of experiments HTE clever characterisation – measurement / screening HTE needs validation at every step – sample preparation, screens, …. HTE shouldn’t just be about doing more, but doing it more repeatable Select areas of composition space to work in – based on: • Physical chemistry • Understanding of raw materials • Requirements of applications Plan campaigns to map these areas
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Develop HTE Capabilities
Screen Target Compositions
Develop Database/Modeling Tools
Initiate Application Specific Research
Rules-of-thumb AnalyticalApplication
Data Data models
Test conditions Data
AnalyticalApplication
VALUE
Reality of HTE Overview of Development Programme
Clever Characterisation for Smarter Formulation
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TheDatabase
Design ofExperiments
SamplePrepartion Data Analysis
SampleScreening /
Measurement
Recipe
Recipe
Recipe
Actuals
Results
Dataand
Recipes
Results
Direction
NewProduct
Developmnet
Reality of HTE Informatics
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Reality of HTE Screening
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1st tier • Rapid measurements • Accept relative data • Accept semi-quantitative • Ensure no false negatives • If necessary allow some false positives • Pass / fail ok • Sediment volume / rate, transmission, foam height, relative viscosity, ……. 2nd tier • Absolute data • Quantitative results • Statistically significant • Modulus, complex viscosity, infra-red spectra, adhesion, ……..
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1536 384 96
Reality of HTE The Right Size For Processing and Measurement
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96 Deep wellwe1 - 2 ml 1-50 ml
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Reality of HTE Different Samples – NIST Gradient Approach
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layer thickness gradient
gradient in temperature, composition, UV exposure, etc.
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Micro Capsule Formulation Background
Micro capsules are formed from multiple ingredients Standard process adapted for HTE production Ultimate application requires both efficient storage and rapid release of active Size of capsule used a proxy for active storage measurement Release in application occurs on shear Sedimentation of capsules was used as a first tier screen to rapidly assess a wide formulation space HTE effective as wide range of new actives continually become available
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Micro Capsule Formulation HTE Process
• Dispense ingredients – powders / liquids • Mix – violent shaking • “Cook” • Load active • Process – shear • Sample – avoid if possible • Condition • Application • Measure • Store Data
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Micro Capsule Formulation Challenge Transmission Profile
Tran
smis
sion
Height
LED Photodiode
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Micro Capsule Formulation Transmission Profile
132.9m 199.8m
0.0m 66.5m
266.3m
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1.2
1.4
1.6
1.8
0 5 10 15 20 25 30 35 40 45 50 Tr
ansm
issi
on
Height (mm)
Transmission of Light through Settling Capsules
Time Time
Tran
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sion
Height
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Height
Tran
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Height
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Micro Capsule Formulation Sedimentation “Heat Map”
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Clever Characterisation for Smarter Formulation
Micro Capsule Formulation Shear
gauze
capsule dispersion
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200g of 5% capsules sonicated using probe
Time 3s 8s 13s 23s Swell 20 22 27 22 vol. (ml/g)
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1
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2
2.1
0 5 10 15 20 25 30 35 40 45 50
Tran
smiss
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Height (mm)
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1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
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0 5 10 15 20 25 30 35 40 45 50
Tran
smiss
ion
Height (mm)
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1.2
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Tran
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Height (mm)
Increasing Ultrasonics
Effect of Shear
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Polymer Solubility Formulation Background
Simple process • Mixed solvent of controlled formulation produced • Polymer dissolved under pre-defined conditions Rapidly changing regulations: • Acceptable solvents for different uses • Volatile organic compound limits Increasing use of bio-derived materials: • Solvents from bio sources • Polymers from bio sources
HTE effective as on-going requirement
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Polymer Solubility Formulation Seeking Design Rules from models and data Thermodynamic Model
DOE
Normalised composition
(H2O, IPA, Eth, Pent, EGDME)
3 Phase Flash25C, P = Atm
3 Phase FlashBubble T, P = Atm
V L1 L2 V L1 L2
Normalised composition
(H2O, IPA, Eth, Pent, EGDME)
3 Phase Flash25C, P = Atm
3 Phase FlashBubble T, P = Atm
V L1 L2 V L1 L2
Normalised composition
(H2O, IPA, Eth, Pent, EGDME)
3 Phase Flash25C, P = Atm
3 Phase FlashBubble T, P = Atm
V L1 L2 V L1 L2
HTE Generated Sample
Polymer Soluble?
>1 Phase?
Pass?
Phase Volumes
Design Rules
Select Polymer and ingredients
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Polymer Solubility Formulation Design Rules
Thermodynamic Model
> 1 phase
Ideal Polymer Solution Model
Soluble?
Pass - clear
Turbid one phase Turbid two phases
n
n n
y
Clever Characterisation for Smarter Formulation
0.000 0.000
0.0557911
0.247696
0.439601
0.631506
0.631506
0.823411
0.000 0.000
0.3792610.512393
0.645525
0.7786560.911788
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Polymer Solubility Formulation Measurement Workflow
ICIA – Transmission scanner • suitable for glass vials • LED / photodiode pair records transmission profiles • 192 unique sample positions
• Unique number of scans • Unique interval between scans • Unique no of measurements per scan
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Add images of ICIA
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Polymer Solubility Formulation Measurement Technique
Sample placed in holder Whole sample scanned Once / hour Transmission scan produced which is representative of sample
0 200 400 600 800 1000
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Height (0.0462mm)
Tran
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%
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Business Unit | Title
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0 200 400 600 800 1000
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Height (0.0462mm)
Tran
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Polymer Solubility Formulation Time lapse
All data stored in local database Multiple scans can be overlaid Monitor change in phase behaviour as system achieves equilibrium
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Polymer Solubility Formulation Powerful Analysis Technique
Significant fluctuations in transmission along the sample tube This is due to unmixed polymer adhered to side of tube Also, unmixed sample at bottom of tube Sample is OK, but classified as fail.
0 5 10 15 20 25 30 35 40 45
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Height (mm)
Tran
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%
2008072263
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0 5 10 15 20 25 30 35 40 45
0
20
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Height (mm)
Tran
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%
2008072274
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Polymer Solubility Formulation Curious Samples
2 area identified by scans and visual observations Not actually 2 phases, the turbidity is caused by undissolved polymer on glass Sample is OK, but classified as fail.
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Sealant Elasticity Formulation Background
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Additive produced for sealant required to produce a set mechanical elasticity Mixing process possible by in-line mixing at small scale so HTE friendly Mini-instron measurement gives full mechanical properties on all samples Direct formulation optimisation
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Sealant Elasticity Formulation Sealant well plate preparation
Sealant set in well plate Piston
pushes out initial part
Top part sealant cut using wire
Remaining part of sealant pushed out to desired l/d ratio
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Sealant Elasticity Formulation Testing procedure with lubricant - underside
Piston rig coated in lubricant before well plate positioned in place before pushing out and cutting to length
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Sealant Elasticity Formulation Testing procedure with lubricant - top side
Sealant cut by wire and pushed out fully
Well plate with samples ready for testing
Separator plate place on well plate to avoid cross contamination
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Sealant Elasticity Formulation Testing procedure with lubricant - top side
Well plate assembly ready for testing
Lubricant soaked sponge
Compression platen (attached to load cell)
Rubber wiper blade to remove test fragments
Cleaning and lubricating stage
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Sealant Elasticity Formulation Force vs. Deformation
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Sealant Elasticity Formulation Inverse Analysis
Stress relaxation in compression & inverse predictions
Sealants
Wood Adhesive
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0.04
0.08
0.12
0.16
0.0 0.5 1.0 1.5 2.0 2.5
Indentation depth (mm)
Inde
ntat
ion
load
(N)
Data (Average)FE-OgdenFE-Mooney-RivlinFE-Neo HookeanFE-Hertzian
Inverse predictions and data
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Characterisation and HTE
42 Clever Characterisation for Smarter Formulation
HTE approach is best suited to: • Products where large samples sets need to be tested • Products where the same test will need to be applied for foreseeable future Development of clever screens / measurements requires good understanding of physical control of application performance: • Clever characterisation of controlled sample set • Supported by modelling based on appropriate science Clever screening can make products HTE suitable: • Screens directly related to application • Screens giving insight into physical properties • Reduce sample set that needs full measurement
Never forget what the formulation tools you already know / use
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Acknowledgements
43 Clever Characterisation for Smarter Formulation
ICI Strategic Technology Group / AkzoNobel Expert Capability Group Stephen Rogers, Pam Shadforth, Katherine Mossop, Alan McNicol, Rob Bailey, Boris Molle, Bill Meredith, Wayne Mah, Roger Kemp, Tahir Malik, John Carroll, Mark Taylor, Lois Hobson, Nabil Zahlan AkzoNobel Decorative Paints – Anthony Woods, Kris Randel, Luc Verhoeven AkzoNobel Speciality Chemicals - Aart Wismeijer, Joke Speelman AkzoNobel Vehicle Refinishes – Elwin de Wolf NIST – National Combinatorial Materials Centre (NCMC) Eric Amis, Kate Beers, Chris Stafford, Mike Fasolka Labman Automation Jamie Marsay, Ian Riley, Peter Cooper, Robert Talintyre, Andrew Whitwell
Clever Characterisation a Different Approach HTEContents�More than 350 years of history �and cutting-edge innovation��The world of AkzoNobel*Paints, coatings and specialty chemicals����SustainabilitySlide Number 7AkzoNobel and FormulationReality of HTE�Why HTE? Sample SpaceSlide Number 10Reality of HTE�Choice of High Throughput Measurement Reality of HTE�High Throughput Information DeliveryReality of HTE�Smart HTEReality of HTE�Overview of Development ProgrammeReality of HTE�InformaticsReality of HTE�ScreeningReality of HTE�The Right Size For Processing and MeasurementReality of HTE�Different Samples – NIST Gradient ApproachMicro Capsule Formulation�BackgroundMicro Capsule Formulation�HTE ProcessMicro Capsule Formulation Challenge �Transmission ProfileMicro Capsule Formulation�Transmission ProfileMicro Capsule Formulation�Sedimentation “Heat Map”Micro Capsule Formulation�ShearSlide Number 25Slide Number 26Polymer Solubility Formulation�BackgroundPolymer Solubility Formulation�Seeking Design Rules from models and data�Thermodynamic Model Polymer Solubility Formulation �Design RulesPolymer Solubility Formulation Measurement WorkflowPolymer Solubility Formulation �Measurement TechniquePolymer Solubility Formulation �Time lapsePolymer Solubility Formulation �Powerful Analysis TechniquePolymer Solubility Formulation�Curious SamplesSealant Elasticity Formulation�BackgroundSealant Elasticity Formulation�Sealant well plate preparationSealant Elasticity Formulation�Testing procedure with lubricant - undersideSealant Elasticity Formulation�Testing procedure with lubricant - top sideSealant Elasticity Formulation�Testing procedure with lubricant - top sideSealant Elasticity Formulation�Force vs. DeformationSealant Elasticity Formulation�Inverse AnalysisCharacterisation and HTEAcknowledgements