A Nonequilibrium Model for Particle Networking/Jamming and Time-Dependent Dynamic Rheology of Filled Polymers
We describe an approach for modeling the filler network formation kinetics of particle-reinforced rubbery polymers—commonly called filler flocculation—that was developed by employing parallels between deformation effects in jammed particle systems and the influence of temperature...
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doaj-4aa1fe64812741868e3dee5338c7fe122020-11-25T03:35:38ZengMDPI AGPolymers2073-43602020-01-0112119010.3390/polym12010190polym12010190A Nonequilibrium Model for Particle Networking/Jamming and Time-Dependent Dynamic Rheology of Filled PolymersChristopher G. Robertson0Sankar Raman Vaikuntam1Gert Heinrich2Endurica LLC, Findlay, OH 45840, USALeibniz-Institut für Polymerforschung Dresden e.V., 01069 Dresden, GermanyLeibniz-Institut für Polymerforschung Dresden e.V., 01069 Dresden, GermanyWe describe an approach for modeling the filler network formation kinetics of particle-reinforced rubbery polymers—commonly called filler flocculation—that was developed by employing parallels between deformation effects in jammed particle systems and the influence of temperature on glass-forming materials. Experimental dynamic viscosity results were obtained concerning the strain-induced particle network breakdown and subsequent time-dependent reformation behavior for uncross-linked elastomers reinforced with carbon black and silica nanoparticles. Using a relaxation time function that depends on both actual dynamic strain amplitude and fictive (structural) strain, the model effectively represented the experimental data for three different levels of dynamic strain down-jump with a single set of parameters. This fictive strain model for filler networking is analogous to the established Tool−Narayanaswamy−Moynihan model for structural relaxation (physical aging) of nonequilibrium glasses. Compared to carbon black, precipitated silica particles without silane surface modification exhibited a greater overall extent of filler networking and showed more self-limiting behavior in terms of network formation kinetics in filled ethylene-propylene-diene rubber (EPDM). The EPDM compounds with silica or carbon black filler were stable during the dynamic shearing and recovery experiments at 160 °C, whereas irreversible dynamic modulus increases were noted when the polymer matrix was styrene-butadiene rubber (SBR), presumably due to branching/cross-linking of SBR in the rheometer. Care must be taken when measuring and interpreting the time-dependent filler networking in unsaturated elastomers at high temperatures.https://www.mdpi.com/2073-4360/12/1/190polymer nanocompositesfilled rubberparticle networkfiller flocculationfictive strainstructural relaxationtool–narayanaswamy–moynihan modeljamming |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Christopher G. Robertson Sankar Raman Vaikuntam Gert Heinrich |
spellingShingle |
Christopher G. Robertson Sankar Raman Vaikuntam Gert Heinrich A Nonequilibrium Model for Particle Networking/Jamming and Time-Dependent Dynamic Rheology of Filled Polymers Polymers polymer nanocomposites filled rubber particle network filler flocculation fictive strain structural relaxation tool–narayanaswamy–moynihan model jamming |
author_facet |
Christopher G. Robertson Sankar Raman Vaikuntam Gert Heinrich |
author_sort |
Christopher G. Robertson |
title |
A Nonequilibrium Model for Particle Networking/Jamming and Time-Dependent Dynamic Rheology of Filled Polymers |
title_short |
A Nonequilibrium Model for Particle Networking/Jamming and Time-Dependent Dynamic Rheology of Filled Polymers |
title_full |
A Nonequilibrium Model for Particle Networking/Jamming and Time-Dependent Dynamic Rheology of Filled Polymers |
title_fullStr |
A Nonequilibrium Model for Particle Networking/Jamming and Time-Dependent Dynamic Rheology of Filled Polymers |
title_full_unstemmed |
A Nonequilibrium Model for Particle Networking/Jamming and Time-Dependent Dynamic Rheology of Filled Polymers |
title_sort |
nonequilibrium model for particle networking/jamming and time-dependent dynamic rheology of filled polymers |
publisher |
MDPI AG |
series |
Polymers |
issn |
2073-4360 |
publishDate |
2020-01-01 |
description |
We describe an approach for modeling the filler network formation kinetics of particle-reinforced rubbery polymers—commonly called filler flocculation—that was developed by employing parallels between deformation effects in jammed particle systems and the influence of temperature on glass-forming materials. Experimental dynamic viscosity results were obtained concerning the strain-induced particle network breakdown and subsequent time-dependent reformation behavior for uncross-linked elastomers reinforced with carbon black and silica nanoparticles. Using a relaxation time function that depends on both actual dynamic strain amplitude and fictive (structural) strain, the model effectively represented the experimental data for three different levels of dynamic strain down-jump with a single set of parameters. This fictive strain model for filler networking is analogous to the established Tool−Narayanaswamy−Moynihan model for structural relaxation (physical aging) of nonequilibrium glasses. Compared to carbon black, precipitated silica particles without silane surface modification exhibited a greater overall extent of filler networking and showed more self-limiting behavior in terms of network formation kinetics in filled ethylene-propylene-diene rubber (EPDM). The EPDM compounds with silica or carbon black filler were stable during the dynamic shearing and recovery experiments at 160 °C, whereas irreversible dynamic modulus increases were noted when the polymer matrix was styrene-butadiene rubber (SBR), presumably due to branching/cross-linking of SBR in the rheometer. Care must be taken when measuring and interpreting the time-dependent filler networking in unsaturated elastomers at high temperatures. |
topic |
polymer nanocomposites filled rubber particle network filler flocculation fictive strain structural relaxation tool–narayanaswamy–moynihan model jamming |
url |
https://www.mdpi.com/2073-4360/12/1/190 |
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