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Methodology for determining the electronic thermal conductivity of metals via direct nonequilibrium ab initio molecular dynamics

机译:通过直接的非平衡从头算分子动力学确定金属的电子热导率的方法

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摘要

Many physical properties of metals can be understood in terms of the free electron model, as proven by the Wiedemann-Franz law. According to this model, electronic thermal conductivity can be inferred from the Boltzmann transport equation (BTE). However, the BTE does not perform well for some complex metals, such as Cu. Moreover, the BTE cannot clearly describe the origin of the thermal energy carried by electrons or how this energy is transported in metals. The charge distribution of conduction electrons in metals is known to reflect the electrostatic potential of the ion cores. Based on this premise, we develop a methodology for evaluating electronic thermal conductivity of metals by combining the free electron model and nonequilibrium ab initio molecular dynamics simulations. We confirm that the kinetic energy of thermally excited electrons originates from the energy of the spatial electrostatic potential oscillation, which is induced by the thermal motion of ion cores. This method directly predicts the electronic thermal conductivity of pure metals with a high degree of accuracy, without explicitly addressing any complicated scattering processes of free electrons. Our methodology offers a route to understand the physics of heat transfer by electrons at the atomistic level. The methodology can be further extended to the study of similar electron-involved problems in materials, such as electron-phonon coupling, which is underway currently.
机译:Wiedemann-Franz定律证明了金属的许多物理性质可以通过自由电子模型来理解。根据此模型,可以从玻耳兹曼输运方程(BTE)推导电子热导率。但是,BTE在某些复杂的金属(例如铜)上的性能不佳。而且,BTE无法清楚地描述电子所携带的热能的来源,也无法清楚地描述该能量如何在金属中传输。已知金属中导电电子的电荷分布会反映离子核的静电势。在此前提下,我们开发了一种通过结合自由电子模型和非平衡从头算分子动力学模拟来评估金属的电子热导率的方法。我们确认,热激发电子的动能来源于离子核的热运动引起的空间静电势振荡的能量。该方法可以高精度地直接预测纯金属的电子热导率,而无需明确解决自由电子的任何复杂散射过程。我们的方法提供了一条途径,以了解原子级电子的热传递物理学。该方法可以进一步扩展到研究材料中类似的涉及电子的问题,例如目前正在进行的电子-声子耦合。

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  • 来源
    《Physical review》 |2016年第7期|075149.1-075149.7|共7页
  • 作者单位

    Aachen Institute for Advanced Study in Computational Engineering Science (AICES), RWTH Aachen University, 52062 Aachen, Germany;

    Institute of Mineral Engineering, Division of Materials Science and Engineering, Faculty of Georesources and Materials Engineering, RWTH Aachen University, 52064 Aachen, Germany;

    School of Earth and Environment, University of Leeds, Leeds LS2 9JT, United Kingdom;

    Institute of Mineral Engineering, Division of Materials Science and Engineering, Faculty of Georesources and Materials Engineering, RWTH Aachen University, 52064 Aachen, Germany;

    Aachen Institute for Advanced Study in Computational Engineering Science (AICES), RWTH Aachen University, 52062 Aachen, Germany,Juelich Supercomputing Centre, Forschungszentrum Juelich and JARA-HPC, 52425 Juelich, Germany;

    Aachen Institute for Advanced Study in Computational Engineering Science (AICES), RWTH Aachen University, 52062 Aachen, Germany,Institute of Mineral Engineering, Division of Materials Science and Engineering, Faculty of Georesources and Materials Engineering, RWTH Aachen University, 52064 Aachen, Germany;

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