five

High Thermal Conductivity of Wurtzite Boron Arsenide Predicted by Including Four-Phonon Scattering with Machine Learning Potential

收藏
Figshare2021-08-20 更新2026-04-28 收录
下载链接:
https://figshare.com/articles/dataset/High_Thermal_Conductivity_of_Wurtzite_Boron_Arsenide_Predicted_by_Including_Four-Phonon_Scattering_with_Machine_Learning_Potential/15832036
下载链接
链接失效反馈
官方服务:
资源简介:
Materials with high thermal conductivity are of great importance to the thermal management of modern electronic devices. Recently, it was found that cubic boron arsenide (c-BAs) is a high thermal conductivity (κ) material with a value of ∼1300 W/(m·K) at room temperature (RT), where four-phonon scattering plays a crucial role in limiting the κ. In this work, with four-phonon scattering included, we find that the κ of wurtzite BAs (w-BAs) reaches as high as 1036 W/(m·K) along the a–b plane at RT, decreasing by 43% compared to the calculation without considering four-phonon scattering. The similar phonon transport properties between c-BAs and w-BAs can be understood in terms of similar projected density of states and scattering rates, which have the origin in crystal structural resemblance. To accelerate the calculation, the moment tensor potential derived from machine learning is adopted and proven to be a reliable and efficient method to obtain high-order interatomic force constants.
创建时间:
2021-08-20
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作