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Related papers: Machine-Learning-based Prediction of Lattice Therm…

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An analysis of thermal transients from non-equilibrium ab initio molecular-dynamics simulations can be used to calculate the thermal conductivity of materials with a short phonon mean-free path. We adapt the approach-to-equilibrium…

Materials Science · Physics 2020-06-01 Felix C. Mocanu , Konstantinos Konstantinou , Stephen R. Elliott

We investigate electronic structures and thermoelectric properties of recent synthetic half-Heusler $\mathrm{ZrNiPb}$ by using generalized gradient approximation (GGA) and GGA plus spin-orbit coupling (GGA+SOC). Calculated results show that…

Materials Science · Physics 2016-03-29 San-Dong Guo

Finding amorphous polymers with higher thermal conductivity is important, as they are ubiquitous in heat transfer applications. With recent progress in material informatics, machine learning approaches have been increasingly adopted for…

Materials Science · Physics 2021-09-08 Ruimin Ma , Hanfeng Zhang , Jiaxin Xu , Yoshihiro Hayashi , Ryo Yoshida , Junichiro Shiomi , Tengfei Luo

Advances in machine learning have led to the development of foundation models for atomistic materials chemistry, enabling quantum-accurate descriptions of interatomic forces across chemically diverse compounds at reduced computational cost.…

Materials Science · Physics 2025-07-11 Balázs Póta , Paramvir Ahlawat , Gábor Csányi , Michele Simoncelli

Topological semimetal may have substantial applications in electronics, spintronics and quantum computation. Recently, ZrTe is predicted as a new type of topological semimetal due to coexistence of Weyl fermion and massless triply…

Materials Science · Physics 2018-01-17 San-Dong Guo , Yue-Hua Wang , Wan-Li Lu

We demonstrate that a high-dimensional neural network potential (HDNNP) can predict the lattice thermal conductivity of semiconducting materials with an accuracy comparable to that of density functional theory (DFT) calculation. After a…

Materials Science · Physics 2019-08-16 Emi Minamitani , Masayoshi Ogura , Satoshi Watanabe

Nanostructuring has spurred a revival in the field of direct thermoelectric energy conversion. Nanograined materials can now be synthesized with higher figures of merit (ZT) than the bulk counterparts. This leads to increased conversion…

Materials Science · Physics 2024-01-25 Jesús Carrete , Natalio Mingo , Shidong Wang , Stefano Curtarolo

Ternary intermetallic half-Heusler (HH) compounds (XYZ) with 18 valence electron count viz. ZrCoSb, ZrNiSn, and ZrPdSn, have revealed promising thermoelectric properties. Exemplarily, it has been experimentally observed that a slight change…

Materials Science · Physics 2021-11-02 Parul R. Raghuvanshi , Dipanwita Bhattacharjee , Amrita Bhattacharya

The efficient and economical exploitation of polymers with high thermal conductivity is essential to solve the issue of heat dissipation in organic devices. Currently, the experimental preparation of functional thermal conductivity polymers…

Materials Science · Physics 2024-02-16 Xiang Huang , Shengluo Ma , C. Y. Zhao , Hong Wang , Shenghong Ju

We propose a ferromagnetic Heusler alloy that can switch between a metal and a half-metal. Thiseffect can provide tunable spintronics properties. Using the density functional theory (DFT) withreliable implementations of the electron…

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…

In this paper, a multiple-relaxation-time lattice Boltzmann model with an off-diagonal collision matrix was adopted to predict the effective thermal conductivities of the anisotropic heterogeneous materials whose components are also…

Computational Physics · Physics 2015-03-31 Wen-Zhen Fang , Jian-Jun Gou , Hu Zhang , Li Chen , Wen-Quan Tao

Ternary half-Heusler compounds with widely tunable electronic structures, present a new platform to discover topological insulators. Due to time-consuming computations and synthesis procedures, the identification of new topological…

Materials Science · Physics 2020-04-28 Jianghui Liu , Guohua Cao , Zizhen Zhou , Huijun Liu

Thermoelectric materials can be used to construct devices which recycle waste heat into electricity. However, the best known thermoelectrics are based on rare, expensive or even toxic elements, which limits their widespread adoption. To…

Materials Science · Physics 2022-12-14 Luis M. Antunes , Keith T. Butler , Ricardo Grau-Crespo

Calculations of heat transport in crystalline materials have recently become mainstream, thanks to machine-learned interatomic potentials that allow for significant computational cost reductions while maintaining the accuracy of…

Materials Science · Physics 2024-03-04 Nikita Rybin , Alexander Shapeev

This paper proposes a new methodological framework within which the heat conductance in 1D lattices can be studied. The total process of heat conductance is separated into two parts where the first one is the equilibrium process at equal…

Chaotic Dynamics · Physics 2010-06-10 T. Yu. Astakhova , V. N. Likhachev , G. A. Vinogradov

The application of first-principles calculations for predicting lattice thermal conductivity (LTC) in crystalline materials, in conjunction with the linearized phonon Boltzmann equation, has gained increasing popularity. In this…

Materials Science · Physics 2024-05-14 Atsushi Togo , Atsuto Seko

Medium and high entropy ceramics, with their distinctive disordered structures, exhibit ultra-low thermal conductivity and high temperature stability. These properties make them strong contenders for next generation thermal barrier coating…

Materials Science · Physics 2024-05-27 Yuxuan Wang , Guoqiang Lan , Jun Song

High performance thermoelectric devices requires materials with low lattice thermal conductivities. Many strategies, such as phonon engineering, have been made to reduce lattice thermal conductivity without simultaneously decrease of the…

Materials Science · Physics 2020-01-07 Xiaoxia Yu , Hezhu Shao , Xueyun Wang , Yingcai Zhu , Daining Fang , Jiawang Hong

First-principles prediction of lattice thermal conductivity $\kappa_L$ of strongly anharmonic crystals is a long-standing challenge in solid state physics. Making use of recent advances in information science, we propose a systematic and…

Materials Science · Physics 2015-11-17 Fei Zhou , Weston Nielson , Yi Xia , Vidvuds Ozolins