Easy and fast prediction of green solvents for small molecule donor-based organic solar cells through machine learning-Reference-Cited by-同舟云学术

Easy and fast prediction of green solvents for small molecule donor-based organic solar cells through machine learning

Published:2023 Issue:15 Volume:25 Page:10417-10426
ISSN:1463-9076
Container-title:Physical Chemistry Chemical Physics
language:en
Short-container-title:Phys. Chem. Chem. Phys.

Author:

Mahmood Asif¹^ORCID,Sandali Yahya²,Wang Jin-Liang¹^ORCID

Affiliation:

1. Key Laboratory of Cluster Science of Ministry of Education, Beijing Key Laboratory of Photoelectronic/Electrophotonic Conversion Materials, School of Chemistry and Chemical Engineering, Beijing Institute of Technology, Beijing 100081, China

2. Physics Department, College of Science, University of Jeddah, Jeddah 23890, Saudi Arabia

Abstract

A fast machine learning based framework is introduced for the prediction of solubility parameters and selection of green solvents for small molecular donor-based organic solar cells.

Funder

National Natural Science Foundation of China

Thousand Young Talents Program of China

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/D3CP00177F

Reference65 articles.

1. A Bayesian Approach to Predict Solubility Parameters

2. Graphical Gaussian process regression model for aqueous solvation free energy prediction of organic molecules in redox flow batteries