Dataset Restricted Access
Ellis, J. A.; Cangi, A.; Modine, N. A.; Stephens, J. A.; Thompson, A. P.; Rajamanickam, S.
{ "@id": "https://doi.org/10.14278/rodare.646", "description": "<p>Output from electronic structure code (Quantum Espresso) that serves as training data for the machine-learning workflow of the related scientific publication (https://arxiv.org/abs/2010.04905).</p>", "@context": "https://schema.org/", "datePublished": "2020-12-11", "@type": "Dataset", "identifier": "https://doi.org/10.14278/rodare.646", "url": "https://rodare.hzdr.de/record/646", "keywords": [ "machine learning", "neural networks", "materials science", "density functional theory" ], "creator": [ { "@type": "Person", "name": "Ellis, J. A.", "affiliation": "Sandia National Laboratories" }, { "@type": "Person", "name": "Cangi, A.", "affiliation": "Helmholtz-Zentrum Dresden-Rossendorf" }, { "@type": "Person", "name": "Modine, N. A.", "affiliation": "Sandia National Laboratories" }, { "@type": "Person", "name": "Stephens, J. A.", "affiliation": "Sandia National Laboratories" }, { "@type": "Person", "name": "Thompson, A. P.", "affiliation": "Sandia National Laboratories" }, { "@type": "Person", "name": "Rajamanickam, S.", "affiliation": "Sandia National Laboratories" } ], "name": "Accelerating Finite-temperature Kohn-Sham Density Functional Theory with Deep Neural Networks", "sameAs": [ "https://www.hzdr.de/publications/Publ-31857" ] }
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