Accelerating the Discovery of Cu–Sn–S Thermoelectric Compounds via High-Throughput Synthesis, Characterization, and Machine Learning-Assisted Image Analysis-Reference-Cited by-同舟云学术

Accelerating the Discovery of Cu–Sn–S Thermoelectric Compounds via High-Throughput Synthesis, Characterization, and Machine Learning-Assisted Image Analysis

Published:2021-08-25 Issue:17 Volume:33 Page:6918-6924
ISSN:0897-4756
Container-title:Chemistry of Materials
language:en
Short-container-title:Chem. Mater.

Author:

Sheng Ye¹,Deng Tingting²,Qiu Pengfei²^ORCID,Shi Xun²^ORCID,Xi Jinyang¹^ORCID,Han Yuexing³,Yang Jiong¹^ORCID

Affiliation:

1. Materials Genome Institute, Shanghai University, Shanghai 200444, China

2. State Key Laboratory of High Performance Ceramics and Superfine Microstructure, Shanghai Institute of Ceramics, Chinese Academy of Sciences, Shanghai 200050, China

3. School of Computer Engineering and Science & Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai 200444, China

Funder

State Administration of Foreign Experts Affairs

Ministry of Education of the People's Republic of China

Ministry of Science and Technology of the People's Republic of China

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Subject

Materials Chemistry,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.chemmater.1c01856

Reference42 articles.