2 papers
cond-mat.mtrl-sci2026
Fast and Accurate Prediction of Lattice Thermal Conductivity via Machine Learning Surrogates
Zeyu Wang, Shuya Yamazaki, Martin Hoffmann Petersen +11
The appearance of generative models has opened vast chemical spaces in the design of functional materials. Although machine learning interatomic potentials (MLIPs) have substantial…
cond-mat.mtrl-sci2025
Suppression of Thin-Film Thermal Conductivity due to Surface Roughness
Michimasa Morita, Junichiro Shiomi
Understanding thermal transport in silicon nanostructures is crucial for effective thermal management in semiconductor devices. In such nanostructures, boundary scattering can sign…