Accelerating the discovery of high-efficiency donor–acceptor pairs in organic photovoltaics <i>via</i> SolarPCE-Net guided screening
An asymmetric graph neural network framework (SolarPCE-Net) is introduced for organic photovoltaics, achieving improved power conversion efficiency prediction and offering chemically interpretable design insights.
Authors
- Minghua Huang (ORCID: https://orcid.org/0000-0002-8140-2436)
- Y. Wan (ORCID: https://orcid.org/0000-0003-0392-8130)
- Bram Hoex (ORCID: https://orcid.org/0000-0002-2723-5286)
- Peng Liu (ORCID: https://orcid.org/0000-0002-1667-6617)
- Minghui Li (ORCID: https://orcid.org/0000-0003-4643-2303)
- Bo Hu (ORCID: https://orcid.org/0009-0006-2385-027X)
- Xingyu Liu (ORCID: https://orcid.org/0000-0002-6353-4304)
- Tian Xie
Institutions
- Nanjing Agricultural University (CN)
- City University of Hong Kong (HK)
- UNSW Sydney (AU)
- Guangzhou University (CN)
- Yanshan University (CN)
- Ocean University of China (CN)
- University of Hong Kong (HK)
Publication Details
- Journal
- Journal of Materials Chemistry A
- Published
- 2025-10-08
- DOI
- https://doi.org/10.1039/d5ta04854k
- Citations
- 1
- Primary Topic
- Chalcogenide Semiconductor Thin Films
- Type
- article
- Field-Weighted Citation Impact
- 0.73