Accelerating superconductor discovery through tempered deep learning of the electron-phonon spectral function
Abstract Integrating deep learning with the search for new electron-phonon superconductors represents a burgeoning field of research, where the primary challenge lies in the computational intensity of calculating the electron-phonon spectral function, α 2 F(ω), the essential ingredient of Midgal-Eli...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-01-01
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| Series: | npj Computational Materials |
| Online Access: | https://doi.org/10.1038/s41524-024-01475-4 |
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