Decoupling Intrinsic Molecular Efficacy From Platform Effects: An Interpretable Machine Learning Framework for Unbiased Perovskite Passivator Discovery
<-1.7 eV), net electron donation, and optimized interfacial energetics. Crucially, our closed-loop "data-interpretation-screening-verification" pipeline establishes a transferable paradigm for rational materials design, extendable to other optoelectronic interfaces beyond perovskites.
Authors
- Z L Li (ORCID: https://orcid.org/0000-0002-2096-6414)
- Junhua Zhang (ORCID: https://orcid.org/0000-0002-8936-3822)
- Yi-Xiang Wang (ORCID: https://orcid.org/0000-0002-4021-4228)
- Shan Gao
- Xiangmei Duan
- Zhen Zhu
Institutions
- Ningbo University of Technology (CN)
Publication Details
- Journal
- Advanced Science
- Published
- 2026-04-30
- DOI
- https://doi.org/10.1002/advs.75486
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China