4 papers
Predicting Interface Structure using the Minima Hopping Method with a Machine Learning Interatomic Potential
Chang-Ti Chou, Menghang Wang, Chao Yang +4
Predicting atomic-scale interfacial structures remains a central challenge in materials science due to their structural complexity and the difficulty of direct comparison between c…
Lattice-to-Total Thermal Conductivity Ratio: A Phonon-Glass Electron-Crystal Descriptor for Data-Driven Thermoelectric Design
Yifan Sun, Zhi Li, Tetsuya Imamura +3
Thermoelectrics (TEs) are promising candidates for energy harvesting with performance quantified by figure of merit, . To accelerate the discovery of high- materials, effor…
Origin of Glass-like Thermal Conductivity in Crystalline TlAgTe
Shantanu Semwal, Yi Xia, Chris Wolverton +1
Ordered crystalline compounds exhibiting ultralow and glass-like thermal conductivity are both fundamentally and technologically important, where phonon quasi-particles dominate th…
High-throughput computational framework for lattice dynamics and thermal transport including high-order anharmonicity: an application to cubic and tetragonal inorganic compounds
Zhi Li, Huiju Lee, Chris Wolverton +1
Accurately predicting lattice thermal conductivity (kL) from first principles remains a challenge in identifying materials with extreme thermal behavior. While modern lattice dynam…