Leveraging Machine Learning Potentials for In-Situ Searching of Active sites in Heterogeneous Catalysis-Reference-Cited by-同舟云学术

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Leveraging Machine Learning Potentials for In-Situ Searching of Active sites in Heterogeneous Catalysis

Published:2024-09-11 Issue: Volume: Page:
ISSN:2771-9316
Container-title:Precision Chemistry
language:en
Short-container-title:Precision Chemistry

Author:

Cheng Xiran¹,Wu Chenyu¹²,Xu Jiayan³^ORCID,Han Yulan¹³,Xie Wenbo¹,Hu P.¹³^ORCID

Affiliation:

1. School of Physical Science and Technology, ShanghaiTech University, Shanghai 201210, China

2. Key Laboratory of Mesoscopic Chemistry of MOE, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, China

3. School of Chemistry and Chemical Engineering, The Queen’s University of Belfast, Belfast BT9 5AG, U.K.

Funder

National Key Research and Development Program of China

NSFC

ShanghaiTech University

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/prechem.4c00051

Reference153 articles.

1. The role of dynamics in heterogeneous catalysis: Surface diffusivity and N ₂ decomposition on Fe(111)

2. Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery

3. The concept of active site in heterogeneous catalysis

4. Coordination environment of active sites and their effect on catalytic performance of heterogeneous catalysts

5. Introduction to Density Functional Theory: Calculations by Hand on the Helium Atom

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