A Critical Review of Machine Learning Techniques on Thermoelectric Materials.
J Phys Chem Lett
; 14(7): 1808-1822, 2023 Feb 23.
Article
en En
| MEDLINE
| ID: mdl-36763950
ABSTRACT
Thermoelectric (TE) materials can directly convert heat to electricity and vice versa and have broad application potential for solid-state power generation and refrigeration. Over the past few decades, efforts have been made to develop new TE materials with high performance. However, traditional experiments and simulations are expensive and time-consuming, limiting the development of new materials. Machine learning (ML) has been increasingly applied to study TE materials in recent years. This paper reviews the recent progress in ML-based TE material research. The application of ML in predicting and optimizing the properties of TE materials, including electrical and thermal transport properties and optimization of functional materials with targeted TE properties, is reviewed. Finally, future research directions are discussed.
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Banco de datos:
MEDLINE
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En
Revista:
J Phys Chem Lett
Año:
2023
Tipo del documento:
Article
País de afiliación:
China