Predictions of photophysical properties of phosphorescent platinum(II) complexes based on ensemble machine learning approach.

Wang, Shuai; Yam, ChiYung; Chen, Shuguang; Hu, LiHong; Li, Liping; Hung, Faan-Fung; Fan, Jiaqi; Che, Chi-Ming; Chen, GuanHua

Wang, Shuai; Yam, ChiYung; Chen, Shuguang; Hu, LiHong; Li, Liping; Hung, Faan-Fung; Fan, Jiaqi; Che, Chi-Ming; Chen, GuanHua.

Afiliação

Wang S; Department of Chemistry, The University of Hong Kong, Hong Kong, China.
Yam C; Hong Kong Quantum AI Lab Limited, Hong Kong, China.
Chen S; Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Shenzhen, China.
Hu L; Department of Chemistry, The University of Hong Kong, Hong Kong, China.
Li L; Hong Kong Quantum AI Lab Limited, Hong Kong, China.
Hung FF; School of Information Science and Technology, Northeast Normal University, Changchun, China.
Fan J; Hong Kong Quantum AI Lab Limited, Hong Kong, China.
Che CM; Department of Chemistry, The University of Hong Kong, Hong Kong, China.
Chen G; Hong Kong Quantum AI Lab Limited, Hong Kong, China.

J Comput Chem ; 45(6): 321-330, 2024 Mar 05.

Article em En | MEDLINE | ID: mdl-37861354

Palavras-chave

DFT; OLED; machine learning; phosphorescent emitters; photophysical properties

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: J Comput Chem Assunto da revista: QUIMICA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China

Texto completo

Imprimir

XML

PubMed Links

Buscar no Google