Releases: TRI-AMDD/PolyGen
PolyGen: A Generative Model Framework for Polymer Design
This repository contains the code and data used for training generative models in the conditional and unconditional design of polymer structures. PolyGen provides tools for:
Training generative machine learning models,
Example LAMMPS input files to assess polymer structures using molecular dynamics (MD),
Evaluating the generated polymer electrolytes in terms if 6 defined metrics.
The framework has been developed as part of research into accelerating polymer electrolyte discovery and used in the following research papers:
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Yang, Zhenze, et al. "De novo design of polymer electrolytes with high conductivity using gpt-based and diffusion-based generative models." arXiv preprint arXiv:2312.06470 (2023).
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Khajeh, Arash, et al. "A self-improvable polymer discovery framework based on conditional generative model." arXiv preprint arXiv:2312.04013 (2023).