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基于万尼尔函数方法的材料张量光学与输运性质数据集。

Dataset of tensorial optical and transport properties of materials from the Wannier function method.

作者信息

Fang Zhenyao, Hsu Ting-Wei, Yan Qimin

机构信息

Department of Physics, Northeastern University, Boston, Massachusetts, 02115, US.

出版信息

Sci Data. 2025 Jul 1;12(1):1092. doi: 10.1038/s41597-025-05396-9.

Abstract

The discovery of functional materials for energy harvesting and electronic applications require accurate predictions of their optical and transport properties. While several existing datasets contain the optical and transport properties calculated from first-principles calculations, the amount of material entries is often limited and those properties are often reported in scalar form. Comprehensive datasets for the tensorial properties, particularly optical properties, still remain inadequate, which prevents from capturing the anisotropy effect in materials. Therefore, in this work we present the largest-to-date dataset of tensorial optical properties (optical conductivity, shift current) and the dataset of tensorial transport properties (electrical conductivity, thermal conductivity, Seebeck coefficient, thermoelectric figure of merit zT) for 7301 materials, calculated from the Wannier function method. The quality of the Wannier functions were validated by the maximal spread of the Wannier functions and by the comparison with the band structures from first-principles calculations. These results contribute to the systematic study the functional properties for diverse materials and can benefit future data-driven discovery of candidate materials for optoelectronic and thermoelectric applications.

摘要

用于能量收集和电子应用的功能材料的发现需要对其光学和输运性质进行准确预测。虽然现有的几个数据集包含从第一性原理计算得出的光学和输运性质,但材料条目的数量往往有限,而且这些性质通常以标量形式报告。张量性质的综合数据集,特别是光学性质的数据集,仍然不足,这妨碍了捕捉材料中的各向异性效应。因此,在这项工作中,我们展示了迄今为止最大的张量光学性质(光导率、位移电流)数据集以及7301种材料的张量输运性质(电导率、热导率、塞贝克系数、热电优值zT)数据集,这些数据是通过万尼尔函数方法计算得出的。通过万尼尔函数的最大展宽以及与第一性原理计算得到的能带结构进行比较,验证了万尼尔函数的质量。这些结果有助于对各种材料的功能性质进行系统研究,并可为未来基于数据驱动的光电子和热电应用候选材料的发现提供帮助。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b65/12219770/3e4ae7da94fc/41597_2025_5396_Fig1_HTML.jpg

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