Dr Simon R Gibbon AkzoNobel Research, Development & … Gibbon... · 2017. 12. 21. · Akzo formed following the merger of Dutch companies AKU and KZO . Akzo Nobel acquired ICI and

Clever Characterisation a Different Approach HTE Dr Simon R Gibbon AkzoNobel Research, Development & Innovation [email protected]

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

More than 350 years of history and cutting-edge innovation

3

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

The world of AkzoNobel*

4

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

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


Our commitment to doing more with less

Sustainability

Human Cities Making cities more human

Colo

r

Herit

age

Tran

spor

t

Educ

atio

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Spor

t and

leis

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Sust

aina

bilit

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AkzoNobel and 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

Reality of HTE Why HTE? Sample Space


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

20,000 Years + 1 Ice–Age 100 Years + 500 Years of Neglect = World Heritage Site


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


Time

Information /

No of Sam

ples

Real HTE

Non-HTE

Reality of HTE High Throughput Information Delivery

NO

NO

YES / NO

YES

Imagined HTE


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


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


TheDatabase

Design ofExperiments

SamplePrepartion Data Analysis

SampleScreening /

Measurement

Recipe

Recipe

Recipe

Actuals

Results

Dataand

Recipes

Results

Direction

NewProduct

Developmnet

Reality of HTE Informatics


Reality of HTE Screening


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, ……..

1536 384 96

Reality of HTE The Right Size For Processing and Measurement

Clever Characterisation for Smarter Formulation 17

96 Deep wellwe1 - 2 ml 1-50 ml

Reality of HTE Different Samples – NIST Gradient Approach


layer thickness gradient

gradient in temperature, composition, UV exposure, etc.

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


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


Micro Capsule Formulation Challenge Transmission Profile

Tran

smis

sion

Height

LED Photodiode

Micro Capsule Formulation Transmission Profile

132.9m 199.8m

0.0m 66.5m

266.3m

1

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

smis

sion

Height

Tran

smis

sion

Height

Tran

smis

sion

Height


Micro Capsule Formulation Sedimentation “Heat Map”



Micro Capsule Formulation Shear

gauze

capsule dispersion

200g of 5% capsules sonicated using probe

Time 3s 8s 13s 23s Swell 20 22 27 22 vol. (ml/g)


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

ion

Height (mm)

1

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2

0 5 10 15 20 25 30 35 40 45 50

Tran

smiss

ion

Height (mm)

1

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

0 5 10 15 20 25 30 35 40 45 50

Tran

smiss

ion

Height (mm)

Increasing Ultrasonics

Effect of Shear

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


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





V L1 L2 V L1 L2





V L1 L2 V L1 L2

HTE Generated Sample

Polymer Soluble?

>1 Phase?

Pass?

Phase Volumes

Design Rules

Select Polymer and ingredients


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


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

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

30

Add images of ICIA


31

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

0

10

20

30

40

50

60

70

80

90

Height (0.0462mm)

Tran

smis

sion

%


Business Unit | Title

32

0 200 400 600 800 1000

0

20

40

60

80

100

Height (0.0462mm)

Tran

smis

sion

%

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


33

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

0

20

40

60

80

100

120

0

50

100

150

200

250

300

Height (mm)

Tran

smis

sion

%

2008072263


0 5 10 15 20 25 30 35 40 45

0

20

40

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120

140

160

0

50

100

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250

300

Height (mm)

Tran

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sion

%

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.


Sealant Elasticity Formulation Background

35

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


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

1 2 3 4 Clever Characterisation for Smarter Formulation

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


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

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


Sealant Elasticity Formulation Force vs. Deformation


Sealant Elasticity Formulation Inverse Analysis

Stress relaxation in compression & inverse predictions

Sealants

Wood Adhesive

0

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


Characterisation and HTE


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

Acknowledgements


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

Documents

Dr Simon R Gibbon AkzoNobel Research, Development & … Gibbon... · 2017. 12. 21. · Akzo formed following the merger of Dutch companies AKU and KZO . Akzo Nobel acquired ICI and