Design of polyimides with targeted glass transition temperature using a graph neural network-Reference-Cited by-同舟云学术

Design of polyimides with targeted glass transition temperature using a graph neural network

Published:2023 Issue:8 Volume:11 Page:2930-2940
ISSN:2050-7526
Container-title:Journal of Materials Chemistry C
language:en
Short-container-title:J. Mater. Chem. C

Author:

Qiu Haoke¹²^ORCID,Qiu Xuepeng²³^ORCID,Dai Xuemin³,Sun Zhao-Yan¹²^ORCID

Affiliation:

1. State Key Laboratory of Polymer Physics and Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, China

2. School of Applied Chemistry and Engineering, University of Science and Technology of China, Hefei 230026, China

3. CAS Key Laboratory of High-Performance Syntheic Rubber and its Composite Materials, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, China

Abstract

Models were obtained to predict the Tg of polyimides and compared with the experimental results. 110 polyimides are screened through high-throughput calculations and chemical knowledge. Novel molecular design guidelines are provided.

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

Royal Society of Chemistry (RSC)

Subject

Materials Chemistry,General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2023/TC/D2TC05174E

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