Destabilizing high-capacity high entropy hydrides via earth abundant substitutions: from predictions to experimental validation - Agafonov, Andrei; Pineda-Romero, Nayely; Witman, Matthew; Nassif, Vivian; Vaughan, Gavin B.M.; Lei, Lei; Ling, Sanliang; Grant, David M.; Dornheim, Martin; Allendorf, Mark; Stavila, Vitalie; Zlotea, Claudia (Acta Materialia, 2024)
The vast chemical space of high entropy alloys (HEAs) makes trial-and-error experimental approaches for materials discovery intractable and often necessitates data-driven and/or first principles computational insights to successfully target materials with desired properties. In the context of materials discovery for hydrogen storage applications, a theoretical prediction-experimental validation approach can vastly accelerate the search for substitution strategies to destabilize high-capacity hydrides based on benchmark HEAs, e.g. TiVNbCr alloys. Here, machine learning predictions, corroborated by density functional theory calculations, predict substantial hydride destabilization with increasing substitution of earth-abundant Fe content in the (TiVNb)75Cr25-xFex system. The as-prepared alloys crystallize in a single-phase bcc lattice for limited Fe content x < 7, while larger Fe content favors the formation of a secondary C14 Laves phase intermetallic. Short range order for alloys with x < 7 can be well described by a random distribution of atoms within the bcc lattice without lattice distortion. Hydrogen absorption experiments performed on selected alloys validate the predicted thermodynamic destabilization of the corresponding fcc hydrides and demonstrate promising lifecycle performance through reversible absorption/desorption. This demonstrates the potential of computationally expedited hydride discovery and points to further opportunities for optimizing bcc alloy ↔ fcc hydrides for practical hydrogen storage applications.
Keywords: High entropy alloys; Hydrogen storage; Machine learning; Density functional theory; Neutron diffraction; Synchrotron X-ray diffraction; Pair distribution function