Machine learning and density functional theory simulation of the electronic structural properties for novel quaternary semiconductors-Reference-Cited by-同舟云学术

Machine learning and density functional theory simulation of the electronic structural properties for novel quaternary semiconductors

Published:2023 Issue:13 Volume:25 Page:9123-9130
ISSN:1463-9076
Container-title:Physical Chemistry Chemical Physics
language:en
Short-container-title:Phys. Chem. Chem. Phys.

Author:

Gao Mengwei¹^ORCID,Cai Bo¹²^ORCID,Liu Gaoyu¹,Xu Lili¹,Zhang Shengli¹^ORCID,Zeng Haibo¹^ORCID

Affiliation:

1. MIIT Key Laboratory of Advanced Display Materials and Devices, School of Materials Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China

2. State Key Laboratory of Organic Electronics and Information Displays & Institute of Advanced Materials (IAM), Nanjing University of Posts & Telecommunications, 9 Wenyuan Road, Nanjing 210023, China

Abstract

Four quaternary semiconductors with excellent properties as candidate luminescent materials are selected by combining machine learning and first-principles calculations.

Funder

Natural Science Foundation of Jiangsu Province

China Postdoctoral Science Foundation

Fundamental Research Funds for the Central Universities

Publisher

Royal Society of Chemistry (RSC)

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy

Link

http://pubs.rsc.org/en/content/articlepdf/2023/CP/D2CP04244D

Reference52 articles.

1. A fluorene-terminated hole-transporting material for highly efficient and stable perovskite solar cells