Acknowledgements

This work is so-supported by the following funding resource:

Department of Energy/ Advanced Research Projects Agency - Energy (ARPA-E) with Funding Opportunity No. DE-FOA-0002337, ULTIMATE. Award No.: DE-AR0001435

Department of Energy/ EERE Office of Energy Efficiency and Renewable Energy. Award No.: DE-EE0008456

Department of Energy, Office of Fossil Energy, National Energy Technology Laboratory, Innovative Technology Development to Enhance Fossil Power System Efficiency, Funding Opportunity Number: DE-FOA-0001686. Award number: DE-FE0031553

Department of Energy: Office of Nuclear Energy, Funding Opportunity: DE-FOA-0001772, Award No.: DE-NE0008757

Department of Energy, Basic Energy Sciences; DATA SCIENCE FOR DISCOVERY IN Chemical and Materials Sciences, Award number: DE-SC0020147

Department of Energy, Basic Energy Sciences, Award Number: DE-SC0020145.

DOE-NEUP, Funding Opportunity Announcement DE-FOA-0002128. MS-FC-1: Understanding, Predicting, and Optimizing the Physical Properties, Structure, and Dynamics of Molten Salt, Award number: DE-NE0008945

National Science Foundation (NSF) through Grant No. CMMI-1825538.

Office of Naval Research (ONR) project, Contract no. N00014-17-1-2567

Pennsylvania State University’s Institute for CyberScience through the ICS Seed Grant Program

The 2020 Institute for Computational and Data Sciences (ICDS) Seed Grant at the Pennsylvania State University.

First-principles calculations were performed partially on the Roar supercomputer at the Pennsylvania State University’s Institute for Computational and Data Sciences (ICDS), partially on the resources of the National Energy Research Scientific Computing Center (NERSC) supported by the U.S. Department of Energy Office of Science User Facility operated under Contract No. DE-AC02-05CH11231, and partially on the resources of the Extreme Science and Engineering Discovery Environment (XSEDE) supported by National Science Foundation with Grant No. ACI-1548562.