{"title":"Accurate estimation of interfacial thermal conductance between silicon and diamond enabled by a machine learning interatomic potential","authors":"Ali Rajabpour , Bohayra Mortazavi , Pedram Mirchi , Julien El Hajj , Yangyu Guo , Xiaoying Zhuang , Samy Merabia","doi":"10.1016/j.ijthermalsci.2025.109876","DOIUrl":null,"url":null,"abstract":"<div><div>Thermal management at silicon-diamond interface is critical for advancing high-performance electronic and optoelectronic devices. In this study, we calculate the interfacial thermal conductance between silicon and diamond using a computationally efficient machine learning (ML) interatomic potential trained on density functional theory (DFT) data. Using non-equilibrium molecular dynamics (NEMD) simulations, we compute the interfacial thermal conductance (ITC) for various system sizes. Our results reveal an extremely close agreement with experimental data than those obtained using traditional semi-empirical potentials such as Tersoff and Brenner which overestimate ITC. In addition, we analyze the frequency-dependent heat transfer spectrum, providing insights into the contributions of different phonon modes to the interfacial thermal conductance. The ML potential accurately captures the phonon dispersion relations and lifetimes, in good agreement with DFT calculations and experimental observations. It is shown that the Tersoff potential predicts higher phonon group velocities and phonon lifetimes compared to the DFT results. Furthermore, it predicts higher interfacial bonding strength, which is consistent with higher interfacial thermal conductance as compared to the ML potential. This study highlights the use of ML interatomic potentials to improve the accuracy and computational efficiency of thermal transport simulations of complex material interface systems.</div></div>","PeriodicalId":341,"journal":{"name":"International Journal of Thermal Sciences","volume":"214 ","pages":"Article 109876"},"PeriodicalIF":4.9000,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Thermal Sciences","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1290072925001991","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Thermal management at silicon-diamond interface is critical for advancing high-performance electronic and optoelectronic devices. In this study, we calculate the interfacial thermal conductance between silicon and diamond using a computationally efficient machine learning (ML) interatomic potential trained on density functional theory (DFT) data. Using non-equilibrium molecular dynamics (NEMD) simulations, we compute the interfacial thermal conductance (ITC) for various system sizes. Our results reveal an extremely close agreement with experimental data than those obtained using traditional semi-empirical potentials such as Tersoff and Brenner which overestimate ITC. In addition, we analyze the frequency-dependent heat transfer spectrum, providing insights into the contributions of different phonon modes to the interfacial thermal conductance. The ML potential accurately captures the phonon dispersion relations and lifetimes, in good agreement with DFT calculations and experimental observations. It is shown that the Tersoff potential predicts higher phonon group velocities and phonon lifetimes compared to the DFT results. Furthermore, it predicts higher interfacial bonding strength, which is consistent with higher interfacial thermal conductance as compared to the ML potential. This study highlights the use of ML interatomic potentials to improve the accuracy and computational efficiency of thermal transport simulations of complex material interface systems.
期刊介绍:
The International Journal of Thermal Sciences is a journal devoted to the publication of fundamental studies on the physics of transfer processes in general, with an emphasis on thermal aspects and also applied research on various processes, energy systems and the environment. Articles are published in English and French, and are subject to peer review.
The fundamental subjects considered within the scope of the journal are:
* Heat and relevant mass transfer at all scales (nano, micro and macro) and in all types of material (heterogeneous, composites, biological,...) and fluid flow
* Forced, natural or mixed convection in reactive or non-reactive media
* Single or multi–phase fluid flow with or without phase change
* Near–and far–field radiative heat transfer
* Combined modes of heat transfer in complex systems (for example, plasmas, biological, geological,...)
* Multiscale modelling
The applied research topics include:
* Heat exchangers, heat pipes, cooling processes
* Transport phenomena taking place in industrial processes (chemical, food and agricultural, metallurgical, space and aeronautical, automobile industries)
* Nano–and micro–technology for energy, space, biosystems and devices
* Heat transport analysis in advanced systems
* Impact of energy–related processes on environment, and emerging energy systems
The study of thermophysical properties of materials and fluids, thermal measurement techniques, inverse methods, and the developments of experimental methods are within the scope of the International Journal of Thermal Sciences which also covers the modelling, and numerical methods applied to thermal transfer.