HH130: A Standardized Database of Machine Learning Interatomic Potentials, Datasets, and Its Applications in the Thermal Transport of Half-Heusler Thermoelectrics

High-throughput screening of thermoelectric materials from databases requires efficient and accurate computational methods. Machine-learning interatomic potentials (MLIPs) provide a promising avenue, facilitating the development of database-driven thermal transport applications through...