Publication Date:
2014-05-22
Description:
Author(s): K. T. Schütt, H. Glawe, F. Brockherde, A. Sanna, K. R. Müller, and E. K. U. Gross High-throughput density functional calculations of solids are highly time-consuming. As an alternative, we propose a machine learning approach for the fast prediction of solid-state properties. To achieve this, local spin-density approximation calculations are used as a training set. We focus on pre... [Phys. Rev. B 89, 205118] Published Wed May 21, 2014
Keywords:
Electronic structure and strongly correlated systems
Print ISSN:
1098-0121
Electronic ISSN:
1095-3795
Topics:
Physics
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