ArticleProceedings of the National Academy of Sciences of the United States of America2020
Predicting optical spectra for optoelectronic polymers using coarse-grained models and recurrent neural networks.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed, 50 citations in OpenAlex.
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- Models connecting microstructure and charge transport in disordered semiconducting polymers: from theories to digital design.Materials horizons · 2025Review
- Genetic algorithm-accelerated computational discovery of liquid crystal polymers with enhanced optical properties.RSC advances · 2025Article
- Multi-Cover Persistence (MCP)-based machine learning for polymer property prediction.Briefings in bioinformatics · 2024Article
- Applications of Long Short-Term Memory (LSTM) Networks in Polymeric Sciences: A Review.Polymers · 2024Review
- Accessing the electronic structure of liquid crystalline semiconductors with bottom-up electronic coarse-graining.Chemical science · 2024Article
- PolyNC: a natural and chemical language model for the prediction of unified polymer properties.Chemical science · 2024Article
- Conformational Heterogeneity and Interchain Percolation Revealed in an Amorphous Conjugated Polymer.ACS nano · 2022Article
- Identifying structure-absorption relationships and predicting absorption strength of non-fullerene acceptors for organic photovoltaics.Energy & environmental science · 2022Article
- UV-adVISor: Attention-Based Recurrent Neural Networks to Predict UV-Vis Spectra.Analytical chemistry · 2021Article
- The Martini Model in Materials Science.Advanced materials (Deerfield Beach, Fla.) · 2021Article
- Integration of Machine Learning and Coarse-Grained Molecular Simulations for Polymer Materials: Physical Understandings and Molecular Design.Frontiers in chemistry · 2021Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
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Abstract
Coarse-grained modeling of conjugated polymers has become an increasingly popular route to investigate the physics of organic optoelectronic materials. While ultraviolet (UV)-vis spectroscopy remains one of the key experimental methods for the interrogation of these materials, a rigorous bridge between simulated coarse-grained structures and spectroscopy has not been established. Here, we address this challenge by developing a method that can predict spectra of conjugated polymers directly from coarse-grained representations while avoiding repetitive procedures such as
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