Machine-learning-derived thermal conductivity of two-dimensional TiS2/MoS2 van der Waals heterostructures
Predicting the thermal conductivity of two-dimensional (2D) heterostructures is challenging and cannot be adequately resolved using conventional computational approaches. To address this challenge, we propose a new and efficient approach that combines first-principles density functional theory (DFT)...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
AIP Publishing LLC
2024-09-01
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| Series: | APL Machine Learning |
| Online Access: | http://dx.doi.org/10.1063/5.0205702 |