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DOE OSTI · 3013315

Efficiently predicting pressure-composition-temperature diagrams to discover low-stability metal hydrides

Way, Lauren [Sandia National Laboratories (SNL-CA), Livermore, CA (United States)] (ORCID:0009000948561433)·Charbonnier, Veronique [National Inst. of Advanced Industrial Science and Technology (AIST), Tsukuba (Japan)]·Fadonougbo, Julien O. [Uppsala Univ. (Sweden)]·Clulow, Rebecca [Uppsala Univ. (Sweden)] (ORCID:0000000200964366)·Lei, Lei [Univ. of Nottingham (United Kingdom)]·Ling, Sanliang [Univ. of Nottingham (United Kingdom)] (ORCID:0000000315747476)·Grant, David [Univ. of Nottingham (United Kingdom)] (ORCID:0000000267867720)·Dornheim, Martin [Univ. of Nottingham (United Kingdom)] (ORCID:000000018491435X)·Banerjee, Tanumoy [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)]·Breunig, Hanna [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)] (ORCID:000000024727424X)·Zlotea, Claudia [Univ. Paris Est Creteil, Thiais (France); Centre National de la Recherche Scientifique (CNRS) (France). Institut de Chimie et des Matériaux Paris-Est (ICMPE)]·Rowberg, Andrew J. E. [Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)] (ORCID:0000000229286917)·Guan, Pin-Wen [Sandia National Laboratories (SNL-CA), Livermore, CA (United States)] (ORCID:0000000244843216)·Stavila, Vitalie [Sandia National Laboratories (SNL-CA), Livermore, CA (United States)] (ORCID:0000000309810432)·Allendorf, Mark D. [Sandia National Laboratories (SNL-CA), Livermore, CA (United States)] (ORCID:0000000156458246)·Sahlberg, Martin [Univ. of Nottingham (United Kingdom)]·Sakaki, Kouji [National Inst. of Advanced Industrial Science and Technology (AIST), Tsukuba (Japan)] (ORCID:0000000347811073)·Bartelt, Norman Charles [Sandia National Laboratories (SNL-CA), Livermore, CA (United States)] (ORCID:0000000344443500)·Witman, Matthew David [Sandia National Laboratories (SNL-CA), Livermore, CA (United States)] (ORCID:0000000162635114)
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Abstract

Quantitatively accurate computational predictions of metal hydride thermodynamics are challenging but critical for alloy performance optimization across a multitude of technological domains, including hydrogen storage, compression, purification, and getters. Recent machine learning approaches have demonstrated great success in this area, but can potentially suffer from several shortcomings since they rely on imbalanced experimental training data and can have poor out-of-distribution (ood) test performance. Here, in this study, we circumvent such pitfalls by developing a computationally efficient, first principles-based workflow for direct prediction of metal hydride phase equilibrium, i.e., the pressure-composition-temperature (PCT) diagram. We then demonstrate its utility on predicting low stability hydrides derived from compositionally complex C14 Laves phase AB2 alloys. Specifically, we computationally predict and then experimentally validate an AB 2 alloy series (z < 0.6 for Ti 2−z Zr z CrMnFeNi) with ideal hydriding thermodynamics for a two-stage metal hydride-based compressor for pressurizing boil off from liquefied hydrogen. Importantly, this study lays the groundwork for accurate and efficient discovery/optimization of ood, low-stability hydrides for which purely data-driven approaches lack sufficient accuracy.

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08 HYDROGEN25 ENERGY STORAGE36 MATERIALS SCIENCEChemistryEnergy - HydrogenEnergy - StorageMaterials science

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Way, Lauren [Sandia National Laboratories (SNL-CA), Livermore, CA (United States)] (ORCID:0009000948561433), Charbonnier, Veronique [National Inst. of Advanced Industrial Science and Technology (AIST), Tsukuba (Japan)], Fadonougbo, Julien O. [Uppsala Univ. (Sweden)], Clulow, Rebecca [Uppsala Univ. (Sweden)] (ORCID:0000000200964366), Lei, Lei [Univ. of Nottingham (United Kingdom)], Ling, Sanliang [Univ. of Nottingham (United Kingdom)] (ORCID:0000000315747476), Grant, David [Univ. of Nottingham (United Kingdom)] (ORCID:0000000267867720), Dornheim, Martin [Univ. of Nottingham (United Kingdom)] (ORCID:000000018491435X), Banerjee, Tanumoy [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)], Breunig, Hanna [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)] (ORCID:000000024727424X), Zlotea, Claudia [Univ. Paris Est Creteil, Thiais (France); Centre National de la Recherche Scientifique (CNRS) (France). Institut de Chimie et des Matériaux Paris-Est (ICMPE)], Rowberg, Andrew J. E. [Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)] (ORCID:0000000229286917), Guan, Pin-Wen [Sandia National Laboratories (SNL-CA), Livermore, CA (United States)] (ORCID:0000000244843216), Stavila, Vitalie [Sandia National Laboratories (SNL-CA), Livermore, CA (United States)] (ORCID:0000000309810432), Allendorf, Mark D. [Sandia National Laboratories (SNL-CA), Livermore, CA (United States)] (ORCID:0000000156458246), Sahlberg, Martin [Univ. of Nottingham (United Kingdom)], Sakaki, Kouji [National Inst. of Advanced Industrial Science and Technology (AIST), Tsukuba (Japan)] (ORCID:0000000347811073), Bartelt, Norman Charles [Sandia National Laboratories (SNL-CA), Livermore, CA (United States)] (ORCID:0000000344443500), Witman, Matthew David [Sandia National Laboratories (SNL-CA), Livermore, CA (United States)] (ORCID:0000000162635114). 2025-12-08. Efficiently predicting pressure-composition-temperature diagrams to discover low-stability metal hydrides. https://doi.org/10.1039/d5ta06645j

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