Screening interface passivation materials intelligently through machine learning for highly efficient perovskite solar cells-Reference-Cited by-同舟云学术

Screening interface passivation materials intelligently through machine learning for highly efficient perovskite solar cells

Published:2022 Issue:34 Volume:10 Page:17782-17789
ISSN:2050-7488
Container-title:Journal of Materials Chemistry A
language:en
Short-container-title:J. Mater. Chem. A

Author:

Liu Wu¹²,Lu Yao¹²,Wei Dong³^ORCID,Huo Xiaomin¹²,Huang Xiaofeng¹²,Li Yaoyao¹²,Meng Juan¹²^ORCID,Zhao Suling¹²^ORCID,Qiao Bo¹²^ORCID,Liang Zhiqin¹²,Xu Zheng¹²,Song Dandan¹²^ORCID

Affiliation:

1. Key Laboratory of Luminescence and Optical Information, Beijing Jiaotong University, Ministry of Education, Beijing 100044, China

2. Institute of Optoelectronics Technology, Beijing Jiaotong University, Beijing 100044, China

3. College of Physics and Energy, Fujian Normal University, Fuzhou, 350117, China

Abstract

Based on previous experimental results, machine learning is employed to intelligently screen interface materials for use in PSCs at the atomic level. The results of the high-throughput predictions were validated via DFT calculations and experiments.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Fujian Province

Publisher

Royal Society of Chemistry (RSC)

Subject

General Materials Science,Renewable Energy, Sustainability and the Environment,General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2022/TA/D2TA04788H

Reference43 articles.

1. Development and Challenges of Metal Halide Perovskite Solar Modules

2. Prospects for metal halide perovskite-based tandem solar cells