Published on 01 January 2025
QM9VASP, QM9Psi4 and Benchmark Datasets
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QM9VASP, QM9Psi4 and Benchmark dataset including TEA codes.<br>@article{ramakrishnan2014quantum,<br> title={Quantum chemistry structures and properties of 134 kilo molecules},<br> author={Ramakrishnan, Raghunathan and Dral, Pavlo O and Rupp, Matthias and Von Lilienfeld, O Anatole},<br> journal={Scientific data},<br> volume={1},<br> number={1},<br> pages={1--7},<br> year={2014},<br> publisher={Nature Publishing Group}<br>}<br><br>@article{shiota2025lowering,<br> title={Lowering the exponential wall: accelerating high-entropy alloy catalysts screening using local surface energy descriptors from neural network potentials},<br> author={Shiota, Tomoya and Ishihara, Kenji and Mizukami, Wataru},<br> journal={Digital Discovery},<br> volume={4},<br> number={3},<br> pages={738--751},<br> year={2025},<br> publisher={Royal Society of Chemistry}<br>}<br>@misc{shiota2024tamingmultidomainfidelitydata, <br>title={Taming Multi-Domain, -Fidelity Data: Towards Foundation Models for Atomistic Scale Simulations},<br>author={Tomoya Shiota and Kenji Ishihara and Tuan Minh Do and Toshio Mori and Wataru Mizukami}, <br>year={2024}, <br>eprint={2412.13088}, <br>archivePrefix={arXiv}, <br>primaryClass={physics.chem-ph}, <br>url={https://arxiv.org/abs/2412.13088}, <br>}<br>
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Publication Details
Subfield
Computer Networks and Communications
Field
Computer Science
Domain
Physical Sciences
Confidence Score
40%
Source
Open Alex