非对称输运分布函数:偏态是提高热电性能的关键

IF 11 1区 综合性期刊 Q1 Multidisciplinary
Research Pub Date : 2022-07-15 DOI:10.34133/2022/9867639
Jin-Cheng Zheng
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引用次数: 2

摘要

如何实现高热电系数仍然是一个科学难题。通过求解玻尔兹曼输运方程,热电性质可以写成一个函数的积分,即输运分布函数(TDF)。本文系统地研究了各种典型函数形式下输运分布函数的形状对材料热电性能的影响。发现TDF的不对称性,即偏态,可以用来普遍描述其热电性能的变化趋势。通过定义对称和非对称TDF函数,然后为热电应用构建了一种新的偏度。通过与从头算和实验的比较表明,所提出的热电偏度不仅能很好地反映常规偏度的主要特征,而且能准确地预测热电功率。这一比较证实了我们提出的热电偏度的独特特征,以及它在TDF统计和材料热电性能之间的特殊连接作用。增加TDF的不对称性可以提高热电性能。最后,有趣的是发现基于典型量子统计(费米-狄拉克分布)的热电输运性质可以用经典统计的典型形状参数(偏度)很好地描述。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Asymmetrical Transport Distribution Function: Skewness as a Key to Enhance Thermoelectric Performance
How to achieve high thermoelectric figure of merit is still a scientific challenge. By solving the Boltzmann transport equation, thermoelectric properties can be written as integrals of a single function, the transport distribution function (TDF). In this work, the shape effects of transport distribution function in various typical functional forms on thermoelectric properties of materials are systematically investigated. It is found that the asymmetry of TDF, characterized by skewness, can be used to describe universally the trend of thermoelectric properties. By defining symmetric and asymmetric TDF functions, a novel skewness is then constructed for thermoelectric applications. It is demonstrated, by comparison with ab initio calculations and experiments, that the proposed thermoelectric skewness not only perfectly captures the main feature of conventional skewness but also is able to predict the thermoelectric power accurately. This comparison confirms the unique feature of our proposed thermoelectric skewness, as well as its special role of connection between the statistics of TDF and thermoelectric properties of materials. It is also found that the thermoelectric performance can be enhanced by increasing the asymmetry of TDF. Finally, it is also interesting to find that the thermoelectric transport properties based on typical quantum statistics (Fermi-Dirac distributions) can be well described by typical shape parameter (skewness) for classical statistics.
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来源期刊
Research
Research Multidisciplinary-Multidisciplinary
CiteScore
13.40
自引率
3.60%
发文量
0
审稿时长
14 weeks
期刊介绍: Research serves as a global platform for academic exchange, collaboration, and technological advancements. This journal welcomes high-quality research contributions from any domain, with open arms to authors from around the globe. Comprising fundamental research in the life and physical sciences, Research also highlights significant findings and issues in engineering and applied science. The journal proudly features original research articles, reviews, perspectives, and editorials, fostering a diverse and dynamic scholarly environment.
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