期刊
NANO LETTERS
卷 19, 期 6, 页码 3387-3395出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.nanolett.8b05196
关键词
Materials informatics; machine learning; material discovery; thermal conductivity; thermoelectric properties; interfacial thermal conductance
类别
资金
- National Natural Science Foundation of China [51576076, 51606072, 51711540031]
- Natural Science Foundation of Hubei Province [2017CFA046]
- Fundamental Research Funds for the Central Universities [2019kfyRCPY045]
There has been increasing demand for materials with functional thermal properties, but traditional experiments and simulations are high-cost and time-consuming. The emerging discipline, materials informatics, is an effective approach that can accelerate materials development by combining material science and big data techniques. Recently, materials informatics has been successfully applied to designing thermal materials, such as thermal interface materials for heat-dissipation, thermoelectric materials for power generation, and so forth. This Mini Review summarizes the research progress associated with studies regarding the prediction and discovery of materials with desirable thermal transport properties by using materials informatics. On the basis of the review of past research, perspectives are discussed and future directions for studying functional thermal materials by materials informatics are given.
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