Bayesian automated weighting of aggregated DFT, MD, and experimental data for candidate thermodynamic models of aluminum with uncertainty quantification-Reference-Cited by-同舟云学术

Bayesian automated weighting of aggregated DFT, MD, and experimental data for candidate thermodynamic models of aluminum with uncertainty quantification

Published:2021-12 Issue: Volume:20 Page:101216
ISSN:2589-1529
Container-title:Materialia
language:en
Short-container-title:Materialia

Author:

Gabriel Joshua J.^ORCID,Paulson Noah H.^ORCID,Duong Thien C.,Becker Chandler A.,Tavazza Francesca,Kattner Ursula R.,Stan Marius

Funder

Argonne National Laboratory

National Institute of Standards and Technology

Laboratory Directed Research and Development

U.S. Department of Commerce

Center for Hierarchical Materials Design

Northwestern Argonne Institute of Science and Engineering, Northwestern University

U.S. Department of Energy

Laboratory Computing Resource Center

Office of Science

Publisher

Elsevier BV

Subject

General Materials Science

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