THE MICROSCALE POLYMER PROCESSING PROJECT Status Report:2007

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1 THE MICROSCALE POLYMER PROCESSING PROJECT Status Report:2007 Peter Hine Polymer and Complex Fluids Group, School of Physics and Astronomy University of Leeds, Leeds, UK

2 Microscale Polymer Processing Consortium TuE BASF, Innovene, Mitsubishi, Dow, Du Pont, DSM, ICI, Lucite

3 Microscale Polymer Processing Consortium TuE BASF, Innovene, Mitsubishi, Dow, Du Pont, DSM, ICI, Lucite Flagship IRC Project!

4 Microscale Polymer Processing Consortium Follow the processing path of well characterised polymers from synthesis through processing and property evaluation combined with the parallel development of a mathematical and computational protocol. Solid state Modelling Flow computation Molecular Theory Synthesis Materials testing Model Processing Flow Rig Advanced Rheological Characterisation Polymer characterisation Scale up Frequency G 0 1 δ dσ 1 ( ) trσ T trσ = σ IG κσ σκ σ β ( σ IG0) dt τ d τ R 3G E E E E E+07 Molecular weight

5 Microscale Polymer Processing Consortium THEORY MODEL MATERIALS INDUSTRIAL RESINS E E+05 log G'(ω), G''(ω) 4 2 G'(ω), G''(ω) ω 1.00E E E E E E E E E E log ω 1.0 DOW680E k b e fo re k a f te r Model distribution for CM RI (relative intensity) Frequency Retention time (minutes) MW

6 The Tube Model The tube is a mean field picture of the other polymers. tube chain 0 τ e τ R τ d Segmental Fluctuation Retraction CLF Reptation τ e, the entanglement time. τ R the Rouse time. τ d the reptation time. Each chain is constrained by its neighbours into a tube. Each chain can freely diffuse along the tube (reptation) but it is highly constrained in a perpendicular direction.

7 The Tube Model G Mono-dispersed PS 250k 170 C Loss modulus G vs frequency τ d τ R /τ e Two distinct relaxation processes and therefore two important relaxation times Frequency (1/τ). γ τ > 1 τ e /τ R τ d

8 MUPP1 Key Aspects 3G 0 1 δ dσ 1 ( ) trσ T trσ = σ IG κσ σκ σ β ( σ IG0 ) dt τ d τ R 3G0 Derivation of new theoretical models for monodispersed polymers (PS,PE). Rolie-Poly, POM-POM Synthesis of model polymers (monodispersed and branched) for validation of models and flowsolve. Development of a FE programme (flowsolve) for solving 2D flow geometries with embedded new theoretical models. Development of novel processing rigs for small amounts of material. Development of visualisation techniques for comparison with flowsolve.

9 MUPP2 Key Targets 3G 0 1 δ dσ 1 ( ) trσ T trσ = σ IG κσ σκ σ β ( σ IG0 ) dt τ d τ R 3G0 Derivation of new theoretical models for Derivation monodispersed of new theoretical polymers (PS,PE). models for polydispersed polymers and blends Rolie-Poly, POM-POM Synthesis of model polymers Extend tools (monodispersed Synthesis and of branched) heavily for developed in MUPP1 validation branched of polymers models and for to industrial development flowsolve. theoretical materials and models. Development of a processes. FE programme Development of novel (flowsolve) for processing rigs for solving 2D flow 3D flows small amounts of geometries with material. embedded new Crystalline Polymers Development of theoretical visualisation models. 2Phase techniques Materials for Development of FE Development of comparison with programme for visualisation (flowsolve3d) solving Knowledge flowsolve. Transfer techniques for 3D flow geometries with comparison with embedded new flowsolve3d. theoretical models.

10 Microscale Polymer Processing Consortium A Matrix approach to Industrial demand and technical opportunity Platform V: Solid State Properties Platform IV: Flow Visualisation Platform III: Experimental Probes Platform II: Theoretical Molecular Modelling Platform I: Synthesis and Characterisation Stm1: CRYSTAL Stm2: TOOLBOX Stm3: 2-PHASE

11 MUPP2 Highlights - New Theoretical Models Bimodal blends A step towards understanding polydispersed or branched melts 14k PI with 10% 94k PI Thin tube is the tube representing entanglements with ALL other chains Fat tube is the tube representing entanglements with LONG CHAINS ONLY A reasonable fit (Rolie-Poly) with the experiments is obtained when τ R is used as an adjustable parameter... so we think we need to formulate the problem more exactly TOOLBOX K. Jagannathan, D. Auhl, D.J. Read, A.E. Likhtman, C. Fernyhough and T.C.B. McLeish

12 MUPP2 Highlights - New Theoretical Models Bimodal blends A step towards understanding polydispersed or branched melts Transition from fat-tube to thintube reptation Increasing terminal time, up towards thin tube reptation time Increasing terminal modulus TOOLBOX springs picture Quite a lot of subtleties in bimodal blend physics!

13 MUPP2 Highlights flowsolve 3D / 3D Visualisation TOOLBOX P.Jimack, R.Tenshev, M.Walkley, O.Harlen, T.Gough

14 MUPP2 Highlights Flow prediction for industrial materials We=409 T.Gough, D.Hassell, H.Klein Multi mode POM- POM fit for flowsolve TOOLBOX Lightly branched metallocene industrial polymer melt

15 MUPP2 Highlights Crystalline Polymers Both threadlike and globular crystalline regions can be seen optically, forming in the flow-field. Isotactic PP processed visually in the Cambridge Multipass Rheometer. Experiments in Sheffield and Eindhoven using other geometries are now being compared to rheological molecular models of crystal growth rate in oriented melts. CRYSTAL P.Olmsted, T Ryan, S.Mykhaylvk, P Fairclough, M.Mackley

16 MUPP2 Highlights 2Phase Most Industrial Materials are blends of polymers and additives in order to tailor functionality. Even with clever synthesis it is not always possible to get the portfolio of properties required with a single polymer.? 3G 0 1 δ dσ 1 ( ) trσ T trσ = σ IG κσ σκ σ β ( σ IG0) dt τ d τ R 3G Frequency E E E E E+07 Molecular weight 2PHASE

17 MUPP2 Highlights 2Phase Linear shear Frequency E E E E E+07 η η o Molecular weight = 1 φ φmax α γ eff &t γ = 1 φ 170 C α = 2 φ = 0.68 max Kreiger-Docherty 2PHASE

18 MUPP2 Highlights 2Phase γ = 1 s 1 Non-linear shear η η o = 1 φ φ max α γ eff &t γ = 1 φ 2PHASE J.Embery, M.Tassieri, T.Lord, O.Harlen, A.Malidi

19 MUPP2 Highlights 2Phase γ = 1 s 1 Cavitation 170 C 2PHASE J.Embery, M.Tassieri, P.J.Hine

20 MUPP2 Highlights 2Phase Die Swell τ R Die Swell τ d 7 mm 1 5 mm 25 mm 2.5 mm Die γ& Wall shear rate s -1 PURE PS Swell +20% glass 1 Wall shear rate s -1 2PHASE M.Tassieri γ&

21 MUPP2 Highlights 2Phase - chaining P.J.Hine, T.Gough, M.Tassieri, T.Lord 2PHASE

22 MUPP2 Highlights 2Phase - chaining MesoFlowsolve Continuous shearing generates particle chaining in a shear-thinning fluid (CMC solution) But not in a constant viscosity Boger fluid A.Malidi, O.Harlen 2PHASE

23 MUPP2 KNOWLEDGE TRANSFER To deliver a set of molecular design tools that will enable a predictive approach to polymer processing, linking molecular engineering at the level of polymer architecture to engineering at the level of process flow conditions to optimise the performance of products. An important new direction for the MUPP project. Funded directly from subscriptions of the industrial project members. Joint portfolio of applications driven projects to take MUPP science into industrial project streams. Call on research personnel across the MUPP sites as necessary. Careful management of IP required. Feedback to pure science. Suneel Kunamaneni and Michael Kapnistos

24 KT - Film Casting using Pom-Pom model The molecular physics of the pompom model has been integrated with the engineering analysis of Doi and Ito in order to predict necking in film casting. Doi-Ito model Deepk Ahirwal, Suneel Kunamaneni, Tom McLeish and Jaap DenDoelder

25 KT - From Polymer Microstructure to Rheology Method Input detailed information on polymer architecture. Predict linear rheology without any freely adjustable parameters. Polymer ensemble priority and seniority are directly calculated in time. Calculate the non-linear rheological response of the polymer sample. Polymer Architecture Branch- On-Branch Model calculation Linear Rheology Multimode Pom-pom calculation Non-Linear Rheology Applications Predict rheological properties of hypothetical materials. Blending tool of different polymer architectures. Mapping architecture with q-spectrum. Generate constitutive equations for polymer processing simulations. M. Kapnistos, C. Das, D.J. Read, T.C.B. McLeish

26 Acknowledgments All MUPP2 colleagues. EPSRC.