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BETE-NET Superconductor Research Dataset
This dataset contains the paperAccelerating superconductor discovery through tempered deep learning of the electron-phonon spectral function"The data used to train and test the model and the code used to implement and train the model are included in the paper, which has been included in the journal Nature.
Citation
@misc{gibson2024acceleratingsuperconductordiscoverytempered,
title={Accelerating superconductor discovery through tempered deep learning of the electron-phonon spectral function},
author={Jason B. Gibson and Ajinkya C. Hire and Philip M. Dee and Oscar Barrera and Benjamin Geisler and Peter J. Hirschfeld and Richard G. Hennig},
year={2024},
eprint={2401.16611},
archivePrefix={arXiv},
primaryClass={cond-mat.supr-con},
url={https://arxiv.org/abs/2401.16611},
}
BETE-NET.torrent
Seeding 1Downloading 0Completed 158Total Downloads 275
This dataset is contributed by community users and is intended for educational and informational purposes only. If any content involves copyright infringement, please contact us at support@hyper.ai for prompt review and removal.
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