PolyRL: reinforcement learning-guided polymer generation for multi-objective polymer discovery
PolyRL integrates property prediction, polymer generation, reinforcement learning, and molecular dynamics validation into a closed-loop framework for polymer discovery.
Authors
- Y. H. Li
- Zhi Wang (ORCID: https://orcid.org/0000-0003-1389-0068)
- Xiaonan Wang (ORCID: https://orcid.org/0000-0001-9775-2417)
- Wentao Li (ORCID: https://orcid.org/0000-0002-5367-3482)
- Lei Qi (ORCID: https://orcid.org/0000-0001-7091-0702)
Institutions
- State Key Laboratory of Chemical Engineering (CN)
- Beijing University of Chemical Technology (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- Digital Discovery
- Published
- 2025-11-25
- DOI
- https://doi.org/10.1039/d5dd00272a
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Tsinghua University