Journal of the Chinese Ceramic Society, Volume. 51, Issue 2, 499(2023)

Applications of Machine Learning in Thermoelectric Materials

SHENG Ye1... NING Jinyan1, and YANG Jiong12 |Show fewer author(s)
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • show less

    Thermoelectric materials are environmental-friendly energy conversion materials. Their performance optimization is a complex issue of multi-parameter coordination, which becomes a challenge. Although the computational simulation and experimental methods for thermoelectric materials have developed rapidly, the efficiency of searching thermoelectric materials still needs to be further improved. Machine learning has some advantages of low computational cost and high prediction speed, which can shorten the search process and accelerate the corresponding studies on the structure and performance optimization of thermoelectric materials. This review introduced the research progress on machine learning for small sample numerical data (data volume is about 102), large sample numerical data (data volume >104) and image data in thermoelectric materials from the perspective of data types. Moreover, different machine learning algorithm models used for the structure and performance of thermoelectric materials in different data types were discussed. In addition, the future development and application direction were also prospected.

    Tools

    Get Citation

    Copy Citation Text

    SHENG Ye, NING Jinyan, YANG Jiong. Applications of Machine Learning in Thermoelectric Materials[J]. Journal of the Chinese Ceramic Society, 2023, 51(2): 499

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Special Issue:

    Received: Oct. 12, 2022

    Accepted: --

    Published Online: Mar. 11, 2023

    The Author Email:

    DOI:10.14062/j.issn.0454-5648.20220863

    Topics