Work

A hierarchical HGBT-based machine learning framework for predicting the power conversion efficiency of perovskite solar cells

Year: 2025

Type: article

Source: Materials Today Communications

DOI: 10.1016/j.mtcomm.2025.112747

Authors: Jiayi Ping, Pei Wang, Bowen Liu, Hairui Zhou, Yuanhua Li, Jia Lin

Institution: Shanghai University of Electric Power

Language: English

Topic: Machine Learning in Materials Science

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: closed

Funders: National Natural Science Foundation of China, Shanghai Municipal Education Commission, Shanghai Shuguang Program

Awards: G2758674866, G4204973843, G6337012273

OpenAlex ID: W4410199152

FWCI: 0.601

Cites: 34

Cited by: 3

Related to: 10