Bulletin of the American Physical Society
APS March Meeting 2022
Volume 67, Number 3
Monday–Friday, March 14–18, 2022; Chicago
Session W16: Machine Learning and Data in Polymer Physics II
3:00 PM–6:00 PM,
Thursday, March 17, 2022
Room: McCormick Place W-184A
Sponsoring Units: DPOLY DBIO DCOMP GDS
Chair: Debra Audus, NIST
Abstract: W16.00010 : Machine Learning-based Study of Mechanical Properties of Dynamically Crosslinked Polymer Networks*
5:12 PM–5:24 PM
Mehdi B Zanjani
In this study, we utilize Molecular Dynamics (MD) simulations to investigate the relationship between polymer network configuration and the resulting mechanical properties of crosslinked polymer composites. MD simulations are employed to generate stress-strain curves for a variety of crosslinker and backbone polymer configurations. The results of the MD simulations are gathered as the reference data set to be utilized within a Machine Learning (ML) framework. We establish “3D images” of the polymer network configurations obtained from MD simulations and build Convolutional Neural Networks (CNNs) in order to investigate the relationship between the architecture of the network and the mechanical behavior of the material. We discuss the efficiency and accuracy of the CNN in evaluating the mechanical properties of each system and study the impact of the configurational details of each network under set initial conditions. The results of this work provide new insight into the complex architecture of crosslinked polymer networks and help identify material structures that can deliver desired mechanical properties.
*We acknowledge funding from American Chemical Society-PRF (Award #61290).
The American Physical Society (APS) is a non-profit membership organization working to advance the knowledge of physics.
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