Thermochemistry of Alane Complexes for Hydrogen Storage: A Theoretical and Experimental Investigation.

Knowledge of the relative stabilities of alane (AlH(3)) complexes with electron donors is essential for identifying hydrogen storage materials for vehicular applications that can be regenerated by off-board methods; however, almost no thermodynamic data are available to make this assessment. To fill this gap, we employed the G4(MP2) method to determine heats of formation, entropies, and Gibbs free energies of formation for 38 alane complexes with NH(3-n)R(n) (R = Me, Et; n = 0-3), pyridine, pyrazine, triethylenediamine (TEDA), quinuclidine, OH(2-n)R(n) (R = Me, Et; n = 0-2), dioxane, and tetrahydrofuran (THF). Monomer, bis, and selected dimer complex geometries were considered. Using these data, we computed the thermodynamics of the key formation and dehydrogenation reactions that would occur during hydrogen delivery and alane regeneration, from which trends in complex stability were identified. These predictions were tested by synthesizing six amine-alane complexes involving trimethylamine, triethylamine, dimethylethylamine, TEDA, quinuclidine, and hexamine and obtaining upper limits of ΔG° for their formation from metallic aluminum. Combining these computational and experimental results, we establish a criterion for complex stability relevant to hydrogen storage that can be used to assess potential ligands prior to attempting synthesis of the alane complex. On the basis of this, we conclude that only a subset of the tertiary amine complexes considered and none of the ether complexes can be successfully formed by direct reaction with aluminum and regenerated in an alane-based hydrogen storage system

BAC-G2 Predictions of Thermochemistry for Gas-Phase Aluminum Compounds

A self-consistent set of thermochemical data for 55 molecules in the Al-H-C-O-F-Cl system are obtained from ab initio quantum-chemistry calculations using the BAC-G2 method. Calculations were performed for both stable and radical species. Good agreement is found between the calculations and experimental heats of formation in most cases where data are available for comparison. Electronic energies, molecular geometries, moments of inertia, and vibrational frequencies are provided in the Supporting Information, as are polynomial fits of the thermodynamic data (heat of formation, entropy, and heat capacity) over the 300--3000 K temperature range

Probing the unusual anion mobility of LiBH_4 confined in highly ordered nanoporous carbon frameworks via solid state NMR and quasielastic neutron scattering

Particle size and particle–framework interactions have profound effects on the kinetics, reaction pathways, and even thermodynamics of complex hydrides incorporated in frameworks possessing nanoscale features. Tuning these properties may hold the key to the utilization of complex hydrides in practical applications for hydrogen storage. Using carefully synthesized, highly-ordered, nanoporous carbons (NPCs), we have previously shown quantitative differences in the kinetics and reaction pathways of LiBH_4 when incorporated into the frameworks. In this paper, we probe the anion mobility of LiBH_4 confined in NPC frameworks by a combination of solid state NMR and quasielastic neutron scattering (QENS) and present some new insights into the nanoconfinement effect. NMR and QENS spectra of LiBH_4 confined in a 4 nm pore NPC suggest that the BH_4− anions nearer the LiBH_4–carbon pore interface exhibit much more rapid translational and reorientational motions compared to those in the LiBH_4 interior. Moreover, an overly broadened BH_4− torsional vibration band reveals a disorder-induced array of BH_4− rotational potentials. XRD results are consistent with a lack of LiBH_4 long-range order in the pores. Consistent with differential scanning calorimetry measurements, neither NMR nor QENS detects a clear solid–solid phase transition as observed in the bulk, indicating that borohydride–framework interactions and/or nanosize effects have large roles in confined LiBH_4

Design principles for the ultimate gas deliverable capacity material: nonporous to porous deformations without volume change

Understanding the fundamental limits of gas deliverable capacity in porous materials is of critical importance as it informs whether technical targets (e.g., for on-board vehicular storage) are feasible. High-throughput screening studies of rigid materials, for example, have shown they are not able to achieve the original ARPA-E methane storage targets, yet an interesting question remains: what is the upper limit of deliverable capacity in flexible materials? In this work we develop a statistical adsorption model that specifically probes the limit of deliverable capacity in intrinsically flexible materials. The resulting adsorption thermodynamics indicate that a perfectly designed, intrinsically flexible nanoporous material could achieve higher methane deliverable capacity than the best benchmark systems known to date with little to no total volume change. Density functional theory and grand canonical Monte Carlo simulations identify a known metal–organic framework (MOF) that validates key features of the model. Therefore, this work (1) motivates a continued, extensive effort to rationally design a porous material analogous to the adsorption model and (2) calls for continued discovery of additional high deliverable capacity materials that remain hidden from rigid structure screening studies due to nominal non-porosity

Analytical models for high-temperature corrosion of silica refractories in glass-melting furnaces

Corrosion of refractory silica brick used to line the crown of many glass-melting furnaces is a serious problem in furnaces using oxygen-fuel rather than air-fuel mixtures. To better understand and to quantify this process analytical models are utilized to evaluate the importance of four potential rate-limiting processes: a) gas-phase transport of NaOH to the crown surface; b) diffusion of sodium-containing reactants through a liquid product layer that forms on the brick face; c) gas-phase diffusion of NaOH into refractory pores; and d) chemical-kinetic limitations at the silica grain surface. Predictions are compared with reported corrosion rates and product compositions previously determined by post-mortem analysis of refractory samples. It is concluded that corrosion occurs largely by reaction and removal of material from the exposed brick face, rather than by transport of reactants into the porous bricks. The observed presence of corrosion products deep within the brick pores is shown to be consistent with capillary suction of high-viscosity liquid products from the hot face into the interior. The results further suggest that mechanisms (b) and (c) do not substantially limit the rate of corrosion, but that mechanisms (a) and (d) may both be important. Comparison of measurements with equilibrium predictions of corrosion-product composition indicate that the corrosion reactions are likely to be close to equilibrium at the conditions and lifetimes typical of full-scale furnaces, but that significant departures from equilibrium may occur in short-duration tests. Although computed corrosion rates based on mass transport through a gas boundary layer are somewhat greater than those observed, the results are very sensitive to the gas-phase concentration of NaOH and to the refractory temperature, both of which contain significant uncertainties

Computational investigation of noble gas adsorption and separation by nanoporous materials.

Molecular simulations are used to assess the ability of metal-organic framework (MOF) materials to store and separate noble gases. Specifically, grand canonical Monte Carlo simulation techniques are used to predict noble gas adsorption isotherms at room temperature. Experimental trends of noble gas inflation curves of a Zn-based material (IRMOF-1) are matched by the simulation results. The simulations also predict that IRMOF-1 selectively adsorbs Xe atoms in Xe/Kr and Xe/Ar mixtures at total feed gas pressures of 1 bar (14.7 psia) and 10 bar (147 psia). Finally, simulations of a copper-based MOF (Cu-BTC) predict this material's ability to selectively adsorb Xe and Kr atoms when present in trace amounts in atmospheric air samples. These preliminary results suggest that Cu-BTC may be an ideal candidate for the pre-concentration of noble gases from air samples. Additional simulations and experiments are needed to determine the saturation limit of Cu-BTC for xenon, and whether any krypton atoms would remain in the Cu-BTC pores upon saturation

Extracting an Empirical Intermetallic Hydride Design Principle from Limited Data via Interpretable Machine Learning

An open question in the metal hydride community is whether there are simple, physics-based design rules that dictate the thermodynamic properties of these materials across the variety of structures and chemistry they can exhibit. While black box machine learning-based algorithms can predict these properties with some success, they do not directly provide the basis on which these predictions are made, therefore complicating the a priori design of novel materials exhibiting a desired property value. In this work we demonstrate how feature importance, as identified by a gradient boosting tree regressor, uncovers the strong dependence of the metal hydride equilibrium H2 pressure on a volume-based descriptor that can be computed from just the elemental composition of the intermetallic alloy. Elucidation of this simple structure–property relationship is valid across a range of compositions, metal substitutions, and structural classes exhibited by intermetallic hydrides. This permits rational targeting of novel intermetallics for high-pressure hydrogen storage (low-stability hydrides) by their descriptor values, and we predict a known intermetallic to form a low-stability hydride (as confirmed by density functional theory calculations) that has not yet been experimentally investigated

Thermochemistry of Alane Complexes for Hydrogen Storage: A Theoretical and Experimental Comparison

Knowledge of the relative stabilities of alane (AlH3) complexes with electron donors is essential for identifying hydrogen storage materials for vehicular applications that can be regenerated by off-board methods; however, almost no thermodynamic data are available to make this assessment. To fill this gap, we employed the G4(MP2) method to determine heats of formation, entropies, and Gibbs free energies of formation for thirty-eight alane complexes with NH3-nRn (R = Me, Et; n = 0-3), pyridine, pyrazine, triethylenediamine (TEDA), quinuclidine, OH2-nRn (R = Me, Et; n = 0-2), dioxane, and tetrahydrofuran (THF). Monomer, bis, and selected dimer complex geometries were considered. Using these data, we computed the thermodynamics of the key formation and dehydrogenation reactions that would occur during hydrogen delivery and alane regeneration, from which trends in complex stability were identified. These predictions were tested by synthesizing six amine-alane complexes involving trimethylamine, triethylamine, dimethylethylamine, TEDA, quinuclidine, and hexamine, and obtaining upper limits of delta G for their formation from metallic aluminum. Combining these computational and experimental results, we establish a criterion for complex stability relevant to hydrogen storage that can be used to assess potential ligands prior to attempting synthesis of the alane complex. Based on this, we conclude that only a subset of the tertiary amine complexes considered and none of the ether complexes can be successfully formed by direct reaction with aluminum and regenerated in an alane-based hydrogen storage system.Comment: Accepted by the Journal of Physical Chemistry

Data-Driven Discovery and Synthesis of High Entropy Alloy Hydrides with Targeted Thermodynamic Stability

Solid-state hydrogen storage materials that are optimized for specific use cases could be a crucial facilitator of the hydrogen economy transition. Yet, the discovery of novel hydriding materials has historically been a manual process driven by chemical intuition or experimental trial and error. Data-driven materials’ discovery paradigms provide an alternative to traditional approaches, whereby machine/statistical learning (ML) models are used to efficiently screen materials for desired properties and significantly narrow the scope of expensive/time-consuming first-principles modeling and experimental validation. Here, we specifically focus on a relatively new class of hydrogen storage materials, high entropy alloy (HEA) hydrides, whose vast combinatorial composition space and local structural disorder necessitate a data-driven approach that does not rely on exact crystal structures to make property predictions. Our ML model quickly screens hydride stability within a large HEA space and permits down selection for laboratory validation based on not only targeted thermodynamic properties but also secondary criteria such as alloy phase stability and density. To experimentally verify our predictions, we performed targeted synthesis and characterization of several novel hydrides that demonstrate significant destabilization (70× increase in equilibrium pressure, 20 kJ/molH2 decrease in desorption enthalpy) relative to the benchmark HEA hydride, TiVZrNbHfHx. Ultimately, by providing a large composition space in which hydride thermodynamics can be continuously tuned over a wide range, this work will enable efficient material selection for various applications, especially in areas such as metal hydride-based hydrogen compressors, actuators, and heat pumps

Tunable intervalence charge transfer in ruthenium Prussian blue analogue enables stable and efficient biocompatible artificial synapses

Emerging concepts for neuromorphic computing, bioelectronics, and brain-computer interfacing inspire new research avenues aimed at understanding the relationship between oxidation state and conductivity in unexplored materials. Here, we present ruthenium Prussian blue analogue (RuPBA), a mixed valence coordination compound with an open framework structure and ability to conduct both ionic and electronic charge, for flexible artificial synapses that reversibly switch conductance by more than four orders of magnitude based on electrochemically tunable oxidation state. Retention of programmed states is improved by nearly two orders of magnitude compared to the extensively studied organic polymers, thus reducing the frequency, complexity and energy costs associated with error correction schemes. We demonstrate dopamine detection using RuPBA synapses and biocompatibility with neuronal cells, evoking prospective application for brain-computer interfacing. By application of electron transfer theory to in-situ spectroscopic probing of intervalence charge transfer, we elucidate a switching mechanism whereby the degree of mixed valency between N-coordinated Ru sites controls the carrier concentration and mobility, as supported by DFT