Machine Learning for Atomic Simulation and Activity Prediction in Heterogeneous Catalysis: Current Status and Future-Reference-Cited by-同舟云学术

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Machine Learning for Atomic Simulation and Activity Prediction in Heterogeneous Catalysis: Current Status and Future

Published:2020-10-30 Issue:22 Volume:10 Page:13213-13226
ISSN:2155-5435
Container-title:ACS Catalysis
language:en
Short-container-title:ACS Catal.

Author:

Ma Sicong¹^ORCID,Liu Zhi-Pan¹^ORCID

Affiliation:

1. Collaborative Innovation Center of Chemistry for Energy Material, Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, Key Laboratory of Computational Physical Science, Department of Chemistry, Fudan University, Shanghai 200433, China

Funder

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

China Postdoctoral Science Foundation

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Subject

Catalysis,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acscatal.0c03472

Reference117 articles.

1. Ertl, G.; Knözinger, H.; Weitkamp, J. Handbook of heterogeneous catalysis; Wiley-VCH: Weinheim, 1997; p 65.

2. Catalytic Role of Gold in Gold-Based Catalysts: A Density Functional Theory Study on the CO Oxidation on Gold

3. General Rules for Predicting Where a Catalytic Reaction Should Occur on Metal Surfaces: A Density Functional Theory Study of C−H and C−O Bond Breaking/Making on Flat, Stepped, and Kinked Metal Surfaces

4. How a century of ammonia synthesis changed the world

5. Predicting Catalysis: Understanding Ammonia Synthesis from First-Principles Calculations

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