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Modeling Thermoset Polymers at the Atomic Scale

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Modeling Thermoset Polymers at the Atomic Scale: Prediction of Network Topology, Glass Transition Temperature and Mechanical Properties


Historically thermoset matrix materials for fiber reinforced composites have been developed through an empirical approach rather than taking advantage of a relation between the macroscopic design related mechanical performance metrics and the constituent material intrinsic atomic or molecular structure.  Using computational techniques in a “virtual laboratory” sense would facilitate a more rapid development cycle and allow for increased interrogation of candidate materials. Molecular simulation represents an avenue to explore the chemical structure-function relationship of these polymers by leveraging advances in the speed and accuracy of molecular dynamics (MD) simulations provided by high performance computing (CPU/GPU), efficient algorithms and modern force fields. An iterative MD-based chemical crosslinking routine allows the generation of realistic chemical network models. We have developed a cross linking algorithm that allows for any chemistry to be defined by the severing of reactant (monomer)bonds and formation of product bonds (polymer). This feature greatly increases the applicability in forming polymers with different crosslinking chemistries. System properties can be monitored during a crosslinking simulation within a single interface, allowing the user to estimate properties like theoretical gel points and reactive group concentrations as curing occurs. After curing glass transition temperatures can predicted using long MD cooling simulations in excess of 1 microsecond through the GPU-enabled Desmond simulation engine. Mechanical elastic and ultimate performance properties can also be predicted. In this talk, several different types of crosslinking chemistries will be explored, including epoxies, benzoxazines and polyurethanes


Authors: Jeffrey M. Sanders, H. Shaun Kwak, Stephen Christensen, Thomas J.L. Mustard, and Mathew D. Halls


Conference: SAMPE Seattle 2017


SKU/Code: SE17--0651

Pages: 9

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