Molecular Dynamics Study of Silicon Carbide Using an Ab Initio-Based Neural Network Potential: Effect of Composition and Temperature on Crystallization Behavior-Reference-Cited by-同舟云学术

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Molecular Dynamics Study of Silicon Carbide Using an Ab Initio-Based Neural Network Potential: Effect of Composition and Temperature on Crystallization Behavior

Published:2023-11-14 Issue:46 Volume:127 Page:22692-22703
ISSN:1932-7447
Container-title:The Journal of Physical Chemistry C
language:en
Short-container-title:J. Phys. Chem. C

Author:

Lim Jinyoung¹,Shim Youngseon¹^ORCID,Park Jaehong¹,Yoon Hongkee¹,Shim Munbo¹,Kim Young-Gu¹,Kim Dae Sin¹

Affiliation:

1. Computational Science and Engineering Team, Innovation Center, Samsung Electronics Co., Ltd., Hwaseong-si, Gyeonggi-do 18448, Korea

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.3c04224

Reference89 articles.

1. High-temperature strength of a thermally conductive silicon carbide ceramic sintered with yttria and scandia

2. Anomalous oxidation behaviour of pressureless liquid-phase-sintered SiC

3. Sliding-wear resistance of liquid-phase-sintered SiC containing graphite nanodispersoids

4. Sliding-wear resistance of ultrafine-grained SiC densified by spark plasma sintering with 3Y2O3+5Al2O3 or Y3Al5O12 additives

5. Handbook of SiC properties for fuel performance modeling

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