当前位置: X-MOL 学术Nanoscale Microscale Thermophys. Eng. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Materials Informatics for Heat Transfer: Recent Progresses and Perspectives
Nanoscale and Microscale Thermophysical Engineering ( IF 4.1 ) Pub Date : 2019-02-19 , DOI: 10.1080/15567265.2019.1576816
Shenghong Ju 1, 2 , Junichiro Shiomi 1, 2, 3, 4
Affiliation  

ABSTRACT With the advances in materials and integration of electronics and thermoelectrics, the demand for novel crystalline materials with ultimate high/low thermal conductivity is increasing. However, search for optimal thermal materials is a challenge due to the tremendous degrees of freedom in the composition and structure of crystal compounds and nanostructures, and thus empirical search would be exhausting. Materials informatics, which combines the simulation/experiment with machine learning, is now gaining great attention as a tool to accelerate the search of novel thermal materials. In this review, we discuss recent progress in developing materials informatics (MI) for heat transport: the exploration of crystals with high/low-thermal conductivity via high-throughput screening, and nanostructure design for high/low-thermal conductance using the Bayesian optimization and Monte Carlo tree search. The progresses show that the MI methods are useful for designing thermal functional materials. We end by addressing the remaining issues and challenges for further development.

中文翻译:

传热材料信息学:最新进展和前景

摘要随着材料的进步以及电子和热电的集成,对具有极限高/低热导率的新型晶体材料的需求正在增加。然而,由于晶体化合物和纳米结构的组成和结构具有极大的自由度,因此寻找最佳热材料是一项挑战,因此经验搜索将是一项艰巨的任务。将模拟/实验与机器学习相结合的材料信息学现在作为一种加速新型热材料搜索的工具受到了极大的关注。在这篇综述中,我们讨论了开发用于热传输的材料信息学 (MI) 的最新进展:通过高通量筛选探索具有高/低热导率的晶体,使用贝叶斯优化和蒙特卡罗树搜索进行高/低热导率的纳米结构设计。研究进展表明,MI 方法可用于设计热功能材料。我们最后解决了进一步发展的剩余问题和挑战。
更新日期:2019-02-19
down
wechat
bug