CONSPECTUS: Not only is hydrogen critical for current chemical and refining processes, it is also projected to be an important energy carrier for future green energy systems such as fuel cell vehicles. Scientists have examined light metal hydrides for this purpose, which need to have both good thermodynamic properties and fast charging/discharging kinetics. The properties of hydrogen in metals are also important in the development of membranes for hydrogen purification. In this Account, we highlight our recent work aimed at the large scale screening of metal-based systems with either favorable hydrogen capacities and thermodynamics for hydrogen storage in metal hydrides for use in onboard fuel cell vehicles or promising hydrogen permeabilities relative to pure Pd for hydrogen separation from high temperature mixed gas streams using dense metal membranes. Previously, chemists have found that the metal hydrides need to hit a stability sweet spot: if the compound is too stable, it will not release enough hydrogen under low temperatures; if the compound is too unstable, the reaction may not be reversible under practical conditions. Fortunately, we can use DFT-based methods to assess this stability via prediction of thermodynamic properties, equilibrium reaction pathways, and phase diagrams for candidate metal hydride systems with reasonable accuracy using only proposed crystal structures and compositions as inputs. We have efficiently screened millions of mixtures of pure metals, metal hydrides, and alloys to identify promising reaction schemes via the grand canonical linear programming method. Pure Pd and Pd-based membranes have ideal hydrogen selectivities over other gases but suffer shortcomings such as sensitivity to sulfur poisoning and hydrogen embrittlement. Using a combination of detailed DFT, Monte Carlo techniques, and simplified models, we are able to accurately predict hydrogen permeabilities of metal membranes and screen large libraries of candidate alloys, selections of which are described in this Account. To further increase the number of membrane materials that can be studied with DFT, computational costs need to be reduced either through methods development to break bottlenecks in the performance prediction algorithm, particularly related to transition state identification, or through screening techniques that take advantage of correlations to bypass constraints.
Hydrogen
separation using metal membranes offers significant energetic,
technological, and economic advantages over conventional separation
processes, resulting in extensive efforts to develop favorable membrane
materials. Intermetallics are stoichiometric compounds of two or more
metals that form an ordered structure. This work exhibits a systematic
search for intermetallic membrane materials for hydrogen separation
from potential candidates using density functional theory (DFT)-based
methods to quantitatively predict solubility, diffusivity, and permeability.
Geometric correlations were used to significantly decrease the number
of calculations performed without compromising on the accuracy of
the predictions. In this work, 1001 intermetallic structures were
screened, and eight materials, MnTi, MgZn2, PtTl2, FeHf2, HfTa, NiTi, TiV, and Fe2Y, were identified
as potential candidates for hydrogen separation membranes based on
the calculated hydrogen permeability. This work, in addition to identifying
novel membrane materials, highlights the significance of computational
tools for screening large libraries of materials for specific applications.
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