热导率
格子(音乐)
声子
材料科学
凝聚态物理
k-最近邻算法
相变
散射
热的
声子散射
热力学
物理
计算机科学
光学
复合材料
声学
人工智能
作者
Samuel Kielar,Chen Li,Han Huang,Renjiu Hu,Carla Slebodnick,Ahmet Alatas,Zhiting Tian
标识
DOI:10.1038/s41467-024-51377-8
摘要
Understanding thermal transport mechanisms in phase change materials is critical to elucidating the microscopic picture of phase transitions and advancing thermal energy conversion and storage. Experiments consistently show that cubic phase germanium telluride (GeTe) has an unexpected increase in lattice thermal conductivity with rising temperature. Despite its ubiquity, resolving its origin has remained elusive. In this work, we carry out temperature-dependent lattice thermal conductivity calculations for cubic GeTe through efficient, high-order machine-learned models and additional corrections for coherence effects. We corroborate the calculated phonon properties with our inelastic X-ray scattering measurements. Our calculated lattice thermal conductivity values agree well with experiments and show a similar increasing trend. Through additional bonding strength calculations, we propose that a major contributor to the increasing lattice thermal conductivity is the strengthening of second-nearest neighbor interactions. The findings herein serve to deepen our understanding of thermal transport in phase-change materials. Anomalous lattice thermal conductivity increase with temperature in cubic GeTe is correlated with strengthening of second-nearest neighbor bonds at temperatures near that of the phase transition, enhancing our understanding of thermal transport in phase-change materials.
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