Quantum-corrected thickness-dependent thermal conductivity in amorphous silicon predicted by machine learning molecular dynamics simulations

Amorphous silicon (a-Si) is an important thermal-management material and also serves as an ideal playground for studying heat transport in strongly disordered materials. Theoretical prediction of the thermal conductivity of a-Si in a wide range of temperatures and sample sizes is still a challenge....

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Bibliographic Details
Main Authors: Yanzhou Wang, Zheyong Fan, Ping Qian, Miguel A Caro, Tapio Ala-Nissila
Format: Default Article
Published: 2023
Subjects:
Mathematical sciences
Other mathematical sciences
Other mathematical sciences not elsewhere classified
Machine learning
Molecular dynamics
Thermal conductivity
Online Access:https://hdl.handle.net/2134/22035311.v1
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