Issue 30, 2024

Giant thermal conductivity and strain thermal response of nitrogen substituted diamane: a machine-learning-based prediction

Abstract

With the ongoing trend of seeking miniaturization and enhanced performance for electronic devices, effective thermal management has emerged as a critical concern. The discovery and investigation of high thermal conductivity (κ) materials have proved to be pivotal in addressing this challenge. This study aims to explore the distinctive properties and potential applications of nitrogen substituted diamane (NCCN), a two-dimensional material with a diamond-like structure composed of carbon and nitrogen atoms. This work systematically delves into NCCN's thermal, mechanical, and electrical properties. It is predicted that NCCN exhibits an exceptional κ, ∼2288 W m−1 K−1, at room temperature (300 K) by combining the machine-learning interatomic potential method and the phonon Boltzmann transport equation, surpassing that of H-diamane and rivaling that of diamond, and an impressive electronic band gap of ∼4.47 eV (PBE). For mechanical properties, the stress–strain relationship reveals that NCCN exhibits isotropic elastic properties and anisotropic tensile strengths. Additionally, the variations in NCCN's κ and electronic energy band structure under different strains underscore its substantial potential in the field of thermoelectric applications.

Graphical abstract: Giant thermal conductivity and strain thermal response of nitrogen substituted diamane: a machine-learning-based prediction

Supplementary files

Article information

Article type
Paper
Submitted
28 Apr 2024
Accepted
30 Jun 2024
First published
04 Jul 2024

Nanoscale, 2024,16, 14387-14401

Giant thermal conductivity and strain thermal response of nitrogen substituted diamane: a machine-learning-based prediction

B. Wang, Z. Huang, X. Xu, S. Fan, K. Zhao and J. Zhu, Nanoscale, 2024, 16, 14387 DOI: 10.1039/D4NR01834F

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