Towards Pareto optimal high entropy hydrides <i>via</i> data-driven materials discovery-Reference-Cited by-同舟云学术

Towards Pareto optimal high entropy hydrides via data-driven materials discovery

Published:2023 Issue:29 Volume:11 Page:15878-15888
ISSN:2050-7488
Container-title:Journal of Materials Chemistry A
language:en
Short-container-title:J. Mater. Chem. A

Author:

Witman Matthew D.¹^ORCID,Ling Sanliang²^ORCID,Wadge Matthew²^ORCID,Bouzidi Anis³,Pineda-Romero Nayely³,Clulow Rebecca⁴^ORCID,Ek Gustav⁴^ORCID,Chames Jeffery M.¹^ORCID,Allendorf Emily J.¹,Agarwal Sapan¹,Allendorf Mark D.¹^ORCID,Walker Gavin S.²,Grant David M.²,Sahlberg Martin⁴,Zlotea Claudia³,Stavila Vitalie¹^ORCID

Affiliation:

1. Sandia National Laboratories, Livermore, California 94551, USA

2. Advanced Materials Research Group, Faculty of Engineering, University of Nottingham, University Park, Nottingham, NG7 2RD, UK

3. Univ. Paris Est Créteil, CNRS, ICMPE, UMR 7182, 2 rue Henri Dunant, Thiais, 94320, France

4. Department of Chemistry – Ångström Laboratory, Uppsala University, Box 523, Uppsala, SE-75120, Sweden

Abstract

Data-driven predictions of metal hydride thermodynamic properties elucidate the Pareto optimal front of high entropy alloy candidates for hydrogen storage.

Funder

Hydrogen and Fuel Cell Technologies Office

U.S. Department of Energy

Engineering and Physical Sciences Research Council

Sandia National Laboratories

NordForsk

Publisher

Royal Society of Chemistry (RSC)

Subject

General Materials Science,Renewable Energy, Sustainability and the Environment,General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2023/TA/D3TA02323K