Ensemble-machine-learning-based correlation analysis of internal and band characteristics of thermoelectric materials

Lihao Chen; Ben Xu; Jia Chen; Ke Bi; Changjiao Li; Shengyu Lu; Guosheng Hu; Yuanhua Lin

doi:10.1039/D0TC02855J

Ensemble-machine-learning-based correlation analysis of internal and band characteristics of thermoelectric materials

Lihao Chen,

*^a Ben Xu,*^b Jia Chen,^a Ke Bi,

^a Changjiao Li,

^c Shengyu Lu,

^d Guosheng Hu^d and Yuanhua Lin^b

Author affiliations

* Corresponding authors

^a Information Functional Materials and Devices Laboratory, Beijing University of Posts and Telecommunications, Beijing 100876, P. R. China
E-mail: chenlihao@bupt.edu.cn

^b State Key Laboratory of New Ceramics and Fine Processing School of Materials Science and Engineering, Tsinghua University, Beijing 100084, P. R. China
E-mail: xuben@mail.tsinghua.edu.cn

^c State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Center for Smart Materials and Device Integration, International School of Materials Science and Engineering, Wuhan University of Technology, Wuhan 430070, P. R. China

^d Software School, Xiamen University, Xiamen 361005, P. R. China

Abstract

Machine learning can significantly help to predict the thermoelectric properties of materials, such as the Seebeck coefficient and electrical conductivity. However, the mechanism underlying the excellent performance of such models is not known. In this study, a new dual-route machine learning system (DMLS) is developed to extract the relationship between the features from materials and the ones from band structure. These findings can help us to set up a bridge between the feature significance and the thermal electric properties, such as Seebeck coefficient, which can provide theoretical guidance regarding the designing of a material with excellent thermoelectric properties.

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DOI: https://doi.org/10.1039/D0TC02855J
Article type: Paper
Submitted: 16 Jun 2020
Accepted: 01 Sep 2020
First published: 02 Sep 2020

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J. Mater. Chem. C, 2020,8, 13079-13089

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Ensemble-machine-learning-based correlation analysis of internal and band characteristics of thermoelectric materials

L. Chen, B. Xu, J. Chen, K. Bi, C. Li, S. Lu, G. Hu and Y. Lin, J. Mater. Chem. C, 2020, 8, 13079 DOI: 10.1039/D0TC02855J

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Journal of Materials Chemistry C

Ensemble-machine-learning-based correlation analysis of internal and band characteristics of thermoelectric materials

Abstract

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Ensemble-machine-learning-based correlation analysis of internal and band characteristics of thermoelectric materials

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