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Thermal management materials are of critical importance for engineering miniaturized electronic devices, where theoretical design of such materials demands the evaluation of thermal conductivities which are numerically expensive. In this…

Materials Science · Physics 2020-12-15 Yixuan Zhang , Chen Shen , Teng Long , Hongbin Zhang

The highly anisotropic thermal conductivity in layered materials is crucial for a broad range of applications such as thermal management of electronic devices, thermal insulation, and thermoelectrics. Understanding of anisotropic thermal…

Materials Science · Physics 2022-08-23 Jialin Tang , Qi Wang , Jiongzhi Zheng , Lin Cheng , Ruiqiang Guo

Penta-NiN2, a novel pentagonal 2D sheet with potential nanoelectronic applications, is investigated in terms of its lattice thermal conductivity, stability, and mechanical behavior. A deep learning interatomic potential (DLP) is firstly…

Materials Science · Physics 2024-03-07 Pedram Mirchi , Christophe Adessi , Samy Merabia , Ali Rajabpour

Thermal and mechanical properties of two-dimensional nanomaterials are commonly studied by calculating force constants using the density functional theory (DFT) and classical molecular dynamics (MD) simulations. Although DFT simulations…

Materials Science · Physics 2021-07-30 Saeed Arabha , Ali Rajabpour

Beryllium polynitrides, BeN4 is a novel layered material, which has been most recently fabricated under high pressure (Phys. Rev. Lett. 126(2021), 175501). As a new class of 2D materials, in this work we conduct first-principles…

Materials Science · Physics 2021-05-27 Bohayra Mortazavi , Fazel Shojaei , Xiaoying Zhuang

We present a combined computational and experimental investigation of the thermal properties of uranium nitride (UN), focusing on the development of a machine learning interatomic potential (MLIP) using the moment tensor potential (MTP)…

Though offering unprecedented pathways to molecular dynamics (MD) simulations of technologically-relevant materials and conditions, machine-learning interatomic potentials (MLIPs) are typically trained for ``simple'' materials and…

Materials Science · Physics 2025-07-09 Nikola Koutná , Shuyao Lin , Lars Hultman , Davide G. Sangiovanni , Paul H. Mayrhofer

Accurate evaluation of the thermal conductivity of a material can be a challenging task from both experimental and theoretical points of view. In particular for the nanostructured materials, the experimental measurement of thermal…

Ternary pnictides semiconductors with II-IV-V2 stoichiometry hold potential as cost effective thermoelectric materials with suitable electronic transport properties, but their lattice thermal conductivities ($\kappa$) are typically too…

Very recently, a novel two-dimension (2D) MXene, MoSi$_2$N$_4$, was successfully synthesized with excellent ambient stability, high carrier mobility, and moderate band gap (Science 369, 670, 2020). In this work, the intrinsic lattice…

Materials Science · Physics 2021-03-25 Jihai Yu , Jian Zhou , Xiangang Wan , Qingfang Li

We present a machine-learning interatomic potential (MLIP) framework, which substantially accelerates the prediction of lattice thermal conductivity for both particle-like and wave-like thermal transport, including three-phonon and…

Materials Science · Physics 2024-11-19 Hao-Jen You , Yi-Ting Chiang , Arun Bansil , Hsin Lin

One of the ultimate goals of computational modeling in condensed matter is to be able to accurately compute materials properties with minimal empirical information. First-principles approaches such as the density functional theory (DFT)…

Machine Learning Interatomic Potentials (MLIPs) are a modern computational method that allows achieving near-quantum mechanical accuracy (DFT) while still describing large-scale systems in molecular dynamics (MD) simulations. In this work,…

Materials Science · Physics 2026-02-13 Le Huu Nghia , Pham Thi Bich Thao , Truong Do Anh Kha , Vo Khuong Dien , Nguyen Thanh Tien

Examination of thermal expansion of two-dimensional (2D) nanomaterials is a challenging theoretical task with either ab-initio or classical molecular dynamics simulations. In this regard, while ab-initio molecular dynamics (AIMD)…

Materials Science · Physics 2021-10-22 Bohayra Mortazavi , Ali Rajabpour , Xiaoying Zhuang , Timon Rabczuk , Alexander V. Shapeev

Graphitic carbon nitride nanosheets are among 2D attractive materials due to presenting unusual physicochemical properties.Nevertheless, no adequate information exists about their mechanical and thermal properties. Therefore, we used…

Materials Science · Physics 2017-04-17 B Mortazavi , G Cuniberti , T Rabczuk

Chemical vapor deposition has been most recently employed to fabricate centimeter-scale high-quality single-layer MoSi2N4 (Science; 2020;369; 670). Motivated by this exciting experimental advance, herein we conduct extensive…

We have developed a machine learning-based interatomic potential (MLIP) for the quaternary MoNbTaW (R4) and quinary MoNbTaTiW (R5) high entropy alloys (HEAs). MLIPs enabled accurate high throughput calculations of elastic and mechanical…

Materials Science · Physics 2022-01-25 Anup Pandey , Jonathan Gigax , Reeju Pokharel

Thermal properties of molybdenum disulfide (MoS$_2$) have recently attracted attention related to fundamentals of heat propagation in strongly anisotropic materials, and in the context of potential applications to optoelectronics and…

Through first-principles calculation based on the density functional theory (DFT) within the pseudo potential-plane wave (PP-PW) approach, we studied the structural, mechanical and thermal properties of Cu$_2$CdSnSe$_4$ and Cu$_2$HgSnSe$_4$…

Materials Science · Physics 2017-02-13 S. Bensalem , M. Chegaar , A. Bouhemadou

We analyze the occurrence of in-plane anisotropy in the electronic, magnetic, elastic and transport properties of more than one thousand 2D materials from the C2DB database. We identify hundreds of anisotropic materials and classify them…

Materials Science · Physics 2020-09-09 Luca Vannucci , Urko Petralanda , Asbjørn Rasmussen , Thomas Olsen , Kristian S. Thygesen
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