Competition between phonon-vacancy and four-phonon scattering in cubic boron arsenide by machine learning interatomic potential-Reference-Cited by-同舟云学术

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Competition between phonon-vacancy and four-phonon scattering in cubic boron arsenide by machine learning interatomic potential

Published:2023-04-10 Issue:4 Volume:7 Page:
ISSN:2475-9953
Container-title:Physical Review Materials
language:en
Short-container-title:Phys. Rev. Materials

Author:

Tang Jialin,Li Guotai,Wang Qi,Zheng Jiongzhi,Cheng Lin,Guo Ruiqiang^ORCID

Funder

Natural Science Foundation of Shandong Province

Excellent Young Scientists Fund

Initiative Research Fund of Shandong Institute of Advanced Technology

Shandong Institute of Advanced Technology

Publisher

American Physical Society (APS)

Subject

Physics and Astronomy (miscellaneous),General Materials Science

Link

http://harvest.aps.org/v2/journals/articles/10.1103/PhysRevMaterials.7.044601/fulltext

Reference65 articles.

1. First-principles calculations for point defects in solids

2. Charged point defects in semiconductors

3. New Insights into Intrinsic Point Defects in V 2 VI 3 Thermoelectric Materials

4. Metal-Doped Lead Halide Perovskites: Synthesis, Properties, and Optoelectronic Applications

5. Quantitative Analysis of Plasmonic Metal Oxide Nanocrystal Ensembles Reveals the Influence of Dopant Selection on Intrinsic Optoelectronic Properties

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1. Significant phonon localization and suppressed transport in silicon-doped gallium oxide: A study using a unified neural network interatomic potential;Journal of Materiomics;2024-07

2. In-plane thermal conductivity of hexagonal boron nitride from 2D to 3D;Journal of Applied Physics;2024-05-23

3. Robust Thermal Transport across the Surface-Active Bonding SiC-on-SiC;ACS Applied Materials & Interfaces;2024-04-10

4. The origin of anomalous mass-dependence of thermal conductivity in Janus XBAlY (X = Se, S, Te; Y = S, Se, O; X ≠ Y) monolayers;Journal of Applied Physics;2024-03-25

5. Vacancy-induced phonon localization in boron arsenide using a unified neural network interatomic potential;Cell Reports Physical Science;2024-01

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