Work

Machine Learning‐Driven Molecule Additives for High‐Performance Perovskite Solar Cells with Bandgap Universality and Scalability

Year: 2026

Type: article

Source: Advanced Functional Materials

DOI: 10.1002/adfm.74914

Authors: Han Wang, Bingqian Zhang, Chenyang Zhang, Waqas Akram, Javed Iqbal, Yu Lei, Caidong Cheng, Ruida Xu, Yuteng Jia, Panyu Wang, Qiangqiang Zhao, Kaiyu Wang, Kaiyu Wang, Jingyuan Qiao, Shuping Pang, Kai Wang, Kai Wang, Mingjia Xiao

Institutions: Xi'an Polytechnic University, Chinese Academy of Sciences, Qingdao Institute of Bioenergy and Bioprocess Technology, Northwestern Polytechnical University, University of Agriculture Faisalabad, University of Bahrain, Wenzhou Medical University

Language: English

Topic: Perovskite Materials and Applications

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Affordable and clean energy

Open Access status: closed

Funders: National Natural Science Foundation of China, Natural Science Foundation of Shandong Province

Awards: G136945885, G5269855332

OpenAlex ID: W7135381190

FWCI: 1.673

Cites: 34

Cited by: 1

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