D.D. Awschalom, J.-M. Halbout
Journal of Magnetism and Magnetic Materials
Polymers are candidate materials for a wide range of sustainability applications such as carbon capture and energy storage. However, computational polymer discovery lacks automated analysis of reaction pathways and stability assessment through retro-synthesis. Here, we report an extension of transformer-based language models to polymerization for both reaction and retrosynthesis tasks. To that end, we have curated a polymerization dataset for vinyl polymers covering reactions and retrosynthesis for representative homo-polymers and co-polymers. Overall, we obtain a forward model Top-4 accuracy of 80% and a backward model Top-4 accuracy of 60%. We further analyze the model performance with representative polymerization examples and evaluate its prediction quality from a materials science perspective. To enable validation and reuse, we have made our models and data available in public repositories.
D.D. Awschalom, J.-M. Halbout
Journal of Magnetism and Magnetic Materials
P.C. Pattnaik, D.M. Newns
Physical Review B
P. Martensson, R.M. Feenstra
Journal of Vacuum Science and Technology A: Vacuum, Surfaces and Films
Michael Ray, Yves C. Martin
Proceedings of SPIE - The International Society for Optical Engineering