Combining component screening, machine learning and molecular engineering for the design of high-performance inverted perovskite solar cells-Reference-Cited by-同舟云学术

Combining component screening, machine learning and molecular engineering for the design of high-performance inverted perovskite solar cells

Published:2024 Issue:15 Volume:17 Page:5532-5541
ISSN:1754-5692
Container-title:Energy & Environmental Science
language:en
Short-container-title:Energy Environ. Sci.

Author:

Zhang Boxue¹,Zeng Huaibiao²,Yin Haomiao²,Zheng Daming¹,Wan Zhongquan²^ORCID,Jia Chunyang²^ORCID,Stuyver Thijs³^ORCID,Luo Junsheng²^ORCID,Pauporté Thierry¹^ORCID

Affiliation:

1. Institut de Recherche de Chimie Paris (IRCP) UMR8247, Chimie ParisTech, PSL University CNRS, 11 rue P. et M. Curie, Paris F-75005, France

2. National Key Laboratory of Electronic Films and Integrated Devices, School of Integrated Circuit Science and Engineering, University of Electronic Science and Technology of China, 611731 Chengdu, P. R. China

3. Chimie ParisTech, Université PSL, CNRS, Institute of Chemistry for Life and Health Sciences, 75005 Paris, France

Abstract

To develop efficient and stable inverted perovskite solar cells, we describe an innovative strategy that combines component screening, machine learning and molecular engineering.

Funder

National Natural Science Foundation of China

Agence Nationale de la Recherche

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/EE/D4EE00635F

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