Generative deep learning for predicting ultrahigh lattice thermal conductivity materials
Abstract Developing materials with ultrahigh thermal conductivity is crucial for thermal management and energy conversion. The recent development of generative models and machine learning (ML) holds great promise for predicting new functional materials. However, these data-driven methods are not tai...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
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| Series: | npj Computational Materials |
| Online Access: | https://doi.org/10.1038/s41524-025-01592-8 |
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