Rational ensemble design of alloy catalysts for selective ammonia oxidation based on machine learning-Reference-Cited by-同舟云学术

Rational ensemble design of alloy catalysts for selective ammonia oxidation based on machine learning

Published:2022 Issue:47 Volume:10 Page:25238-25248
ISSN:2050-7488
Container-title:Journal of Materials Chemistry A
language:en
Short-container-title:J. Mater. Chem. A

Author:

Yang Jiaqiang¹,Wang Zhaojie¹,Liu Zhang¹,Wang Qingbo²^ORCID,Wen Yanwei¹^ORCID,Zhang Aimin³,Chen Rong⁴^ORCID,Shan Bin¹^ORCID

Affiliation:

1. State Key Laboratory of Material Processing and Die and Mould Technology, School of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China

2. School of Mathematics and Physics, China University of Geosciences (Wuhan), Wuhan 430074, PR China

3. State Key Laboratory of Advanced Technologies for Comprehensive Utilization of Platinum Metals, Kunming Institute of Precious Metals, Kunming 650106, China

4. State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China

Abstract

High-throughput computation and machine learning studies are conducted for the rational design of ensembles of alloy catalysts for selective catalytic oxidation of NH3 (NH3-SCO).

Funder

National Natural Science Foundation of China

Major Science and Technology Projects in Yunnan Province

Natural Science Foundation of Hubei Province

Huazhong University of Science and Technology

National Key Research and Development Program of China

Publisher

Royal Society of Chemistry (RSC)

Subject

General Materials Science,Renewable Energy, Sustainability and the Environment,General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2022/TA/D2TA07216E