Deciphering the Atomistic Mechanism of Si(111)-7 × 7 Surface Reconstruction Using a Machine-Learning Force Field-Reference-Cited by-同舟云学术

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Deciphering the Atomistic Mechanism of Si(111)-7 × 7 Surface Reconstruction Using a Machine-Learning Force Field

Published:2023-09-07 Issue:37 Volume:145 Page:20511-20520
ISSN:0002-7863
Container-title:Journal of the American Chemical Society
language:en
Short-container-title:J. Am. Chem. Soc.

Author:

Shen Yidi¹,Morozov Sergey I.²^ORCID,Luo Kun¹,An Qi¹^ORCID,Goddard III William A.³

Affiliation:

1. Department of Materials Science and Engineering, Iowa State University, Ames, Iowa 50011, United States

2. Department of Physics of Nanoscale Systems, South Ural State University, Chelyabinsk 454080, Russia

3. Materials and Process Simulation Center (MSC), California Institute of Technology, Pasadena, California 91125, United States

Funder

Hong Kong Government

Division of Civil, Mechanical and Manufacturing Innovation

Publisher

American Chemical Society (ACS)

Subject

Colloid and Surface Chemistry,Biochemistry,General Chemistry,Catalysis

Link

https://pubs.acs.org/doi/pdf/10.1021/jacs.3c06540

Reference48 articles.

1. Effects of surface crack on the mechanical properties of Silica: A molecular dynamics simulation study

2. Mechanical Properties of Vapor−Liquid−Solid Synthesized Silicon Nanowires

3. Physical properties and chemical reactivity of the buckled dimer on Si(100)

4. Surface-State Electrical Conductivity at a Metal-Insulator Transition On Silicon

5. Chain model of Si(111)2×1 surface: Optical properties and surface-state excitons

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