Lattice Thermal Conductivity of 2D Nanomaterials: A Simple Semi-Empirical Approach

TL;DR

This paper introduces a simple semi-empirical method to efficiently estimate the lattice thermal conductivity of 2D nanomaterials, avoiding complex simulations while maintaining accuracy.

Contribution

It presents a novel semi-empirical approach based on thermochemical equations and Arrhenius fitting for calculating LTC in 2D nanomaterials, reducing computational costs.

Findings

Accurately estimates LTC of various 2D materials.

Values agree well with existing theoretical and experimental data.

Method is faster and less resource-intensive than traditional protocols.

Abstract

Extracting reliable information on certain physical properties of materials, like thermal behavior, such as thermal transport, which can be very computationally demanding. Aiming to overcome such difficulties in the particular case of lattice thermal conductivity (LTC) of 2D nanomaterials, we propose a simple, fast, and accurate semi-empirical approach for its calculation.The approach is based on parameterized thermochemical equations and Arrhenius-like fitting procedures, thus avoiding molecular dynamics or \textit{ab initio} protocols, which frequently demand computationally expensive simulations. As proof of concept, we obtain the LTC of some prototypical physical systems, such as graphene (and other 2D carbon allotropes), hexagonal boron nitride (hBN), silicene, germanene, binary, and ternary BNC latices and two examples of the fullerene network family. Our values are in good agreement with other theoretical and experimental estimations, nonetheless being derived in a rather straightforward way, at a fraction of the computational cost.