Decoding Perovskite Interfaces: Machine Learning Uncovers Geometry-Matched Dual-Site Hydrogen Bonding.

Authors

Can Cheng, Xinyu Gu, Kai Sun, Renjie Wang, Zefeng Yang, Yuehao Xu, Pihuang Yang, Zhen Wang, Jionghua Wu, Hao Chen, Ling Wu

Published in

Angewandte Chemie (International ed. in English). Pages e9718249. Oct 20, 2026. Epub Oct 20, 2026.

Abstract

Molecular passivation is central to efficient and stable perovskite photovoltaics, yet interfacial molecules are still largely selected through chemical intuition and iterative experimentation. Here, an interpretable machine-learning framework is developed that extracts chemically meaningful structure-performance relationships from literature data and uses them to guide molecular screening. Using approximately 100 data points, the model quantitatively relates six molecular and material features to photovoltaic performance, while SHapley Additive exPlanations (SHAP) analysis ranks their relative contributions and identifies hydrogen-bonding capacity and adsorption strength as the two most influential factors. Guided by these data-derived relationships, nine previously unexplored molecules were screened, with 2-amino-thiazole-4-carboxamide (ATC) and 1-(2-aminoethyl)-1H-pyrrole-2,5-dione (MPD) emerging as leading candidates. Theoretical and experimental investigations show that MPD exhibits stronger Pb^{2 +} coordination, whereas ATC forms stronger geometry-matched multisite N─H···I interactions, increasing the calculated iodide-migration barrier from 0.39 to 0.67 eV and suppressing interfacial iodide redistribution. ATC-modified cells achieve a PCE of 27.13% and a certified stabilized efficiency of 26.59%, while retaining 90% of their initial efficiency after 1460 h of unencapsulated operation. The strategy further delivers efficiencies of 24.01% and 21.14% in 20.98 cm² rigid and 21.0 cm² flexible modules, respectively, providing a data-to-mechanism route for rational and scalable perovskite interface engineering.

PMID:
42902473
Bibliographic data and abstract were imported from PubMed on 21 Oct 2026.

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