Revealing Carbon Vacancy Distribution on α-MoC<sub>1–<i>x</i></sub>Surfaces by Machine-Learning Force-Field-Aided Cluster Expansion Approach-Reference-Cited by-同舟云学术

Revealing Carbon Vacancy Distribution on α-MoC_1–xSurfaces by Machine-Learning Force-Field-Aided Cluster Expansion Approach

Published:2023-06-30 Issue:27 Volume:127 Page:13228-13237
ISSN:1932-7447
Container-title:The Journal of Physical Chemistry C
language:en
Short-container-title:J. Phys. Chem. C

Author:

Xie Jun-Zhong¹,Jiang Hong¹^ORCID

Affiliation:

1. Beijing National Laboratory for Molecular Sciences, State Key Laboratory of Rare Earth Material Chemistry and Application, Institute of Theoretical and Computational Chemistry, College of Chemistry and Molecular Engineering, Peking University, 100871 Beijing, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Subject

Surfaces, Coatings and Films,Physical and Theoretical Chemistry,General Energy,Electronic, Optical and Magnetic Materials

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpcc.3c01941

Reference72 articles.

1. Platinum-Like Behavior of Tungsten Carbide in Surface Catalysis

2. Carbide and Nitride Overlayers on Early Transition Metal Surfaces: Preparation, Characterization, and Reactivities