Advancing Thermal Management with Machine-Learning Potentials on Boron Nitride (BN) and Other Group 13 Nitrides
Author:
Affiliation:
1. Department of Chemistry, Indian Institute of Technology (IIT) Indore, Simrol, Indore 453552, India
2. Terramera Inc., Chemistry & Bioinformatics Department, Vancouver, British Columbia V5Y 1K3, Canada
Funder
Council of Scientific and Industrial Research, India
Science and Engineering Research Board
Ministry of Education, India
Publisher
American Chemical Society (ACS)
Subject
Electrical and Electronic Engineering,Materials Chemistry,Electrochemistry,Energy Engineering and Power Technology,Chemical Engineering (miscellaneous)
Link
https://pubs.acs.org/doi/pdf/10.1021/acsaem.3c01161
Reference55 articles.
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2. Experimental observation of high thermal conductivity in boron arsenide
3. Zhang, H.; Lv, Z.; Tian, L.; Tan, Z.; Liu, L.; Li, Z. Thermal Conductivity Measurements of Ultra-Thin Single Crystal Silicon Films Using Improved Structure. In ICSICT-2006:2006 8th International Conference on Solid-State and Integrated Circuit Technology, Proceedings; 2007.
4. Physical Properties of Copper Based MMC Strengthened with Alumina
5. Thermal Conductivity of Pure and Impure Silicon, Silicon Carbide, and Diamond
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