Lattice thermal conductivity and Young's modulus of XN<sub>4</sub> (X = Be, Mg and Pt) 2D materials using machine learning interatomic potentials-Reference-Cited by-同舟云学术

Lattice thermal conductivity and Young's modulus of XN₄ (X = Be, Mg and Pt) 2D materials using machine learning interatomic potentials

Author:

Ghorbani Khashayar¹,Mirchi Pedram¹²^ORCID,Arabha Saeed¹³,Rajabpour Ali¹⁴^ORCID,Volz Sebastian⁵⁶^ORCID

Affiliation:

1. Advanced Simulation and Computing Laboratory (ASCL), Imam Khomeini International University, Qazvin, Iran

2. Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran

3. Department of Mechanical Engineering, Lassonde School of Engineering, York University, Toronto M3J 1P3, Canada

4. School of Nano Science, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran

5. Institute of Industrial Science, The University of Tokyo, Tokyo 153-8505, Japan

6. LIMMS, CNRS-IIS IRL 2820, The University of Tokyo, Tokyo 153-8505, Japan

Abstract

DFT and Machine-learning interatomic potential combination for thermal and mechanical properties prediction of nitrogen-rich 2D materials.

Funder

Iran National Science Foundation

Publisher

Royal Society of Chemistry (RSC)

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy

Link

Reference60 articles.

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