3 papers
cond-mat.mtrl-sci2026
Ab initio-based Deep-Learning Prediction of Carrier Mobility in Strongly Anharmonic Materials
Juan Zhang, Boheng Zhao, Yang Li +4
Predicting charge transport in strongly anharmonic materials, particularly ultralow thermal conductors, remains a major challenge for first-principles methods. In such systems, per…
cond-mat.mtrl-sci2026
NanoBTE: Fast Iterative Solution of the Phonon Boltzmann Transport Equation for Nanoscale Heat Transport
Hongjiang Chen, Hai-Xuan Lin, Xiaole Tian +7
Nanoscale heat dissipation has become a critical challenge in advanced semiconductor devices, where phonon transport can strongly deviate from the classical Fourier description due…
cond-mat.mtrl-sci2025
Cooperative Suppression Strategy for Dual Thermal Transport Channels in Crystalline Materials
Yu Wu, Ying Chen, Shuming Zeng +4
We propose a novel design principle for achieving ultralow thermal conductivity in crystalline materials via a "heavy-light and soft-stiff" structural motif. By combining heavy and…