Reactivity of molecular catalysts can be controlled by organic ligands that regulate the steric and electronic properties of catalyst sites. This level of control has generally been unavailable for heterogeneous catalysts. We show that self-assembled monolayers (SAMs) on titania with tunable electronic properties provided fine control over surface reactivity. Controlling the identity of substituents on benzylphosphonic acid SAMs modulated the near-surface electrostatics, enabling regulation of the dehydration activity of 1-propanol and 1-butanol over a wide range, with activities and selectivities of the optimal catalyst far exceeding those of uncoated TiO2. The dipole moment of the adsorbed phosphonate was strongly correlated to the dehydration activity; kinetic measurements and computational modeling indicated that the interfacial electric field altered the transition-state structure and energy. Coating catalysts with SAMs having controllable charge distributions may provide a general approach to heterogeneous catalyst design analogous to the variation of ligands in molecular catalysts.

Ferrite spinels are metal oxides used in a wide variety of applications, many of which are controlled by the diffusion of metal cations through the metal oxide lattice. In this work, we used density functional theory (DFT) to examine the diffusion of Fe, Co, and Ni cations through the Fe3O4, CoFe2O4, and NiFe2O4 ferrite spinels. We apply DFT and crystal field theory to uncover the principles that govern cation diffusion in ferrite spinels. We found that a migrating cation hops from its initial octahedral site to a neighboring octahedral vacancy via a tetrahedral metastable intermediate separated from octahedral sites by a trigonal planar transition state (TS). The cations hop with relative activation energies of Co ≈< Fe < Ni; the ordering of the diffusion barriers is controlled by the crystal field splitting of the diffusing cation. Specifically, the barriers depend on the orbital splitting and number of electrons which must be promoted into the higher energy t2g orbitals of the tetrahedral metastable intermediate as the cations move along the minimum energy pathway of hopping. Additionally, for each diffusing cation, the barriers are inversely proportional to the spinel lattice parameter, leading to relative barriers for cation diffusion of Fe3O4 < CoFe2O4 < NiFe2O4. This results from the shorter cation-O bonds at the TS for spinels with smaller lattices, which inherently possess shorter bond lengths, and consequently higher system energies at their more constricted TS geometries.

Metastable inorganic materials with unique properties are important in many practical applications, but their synthesis is often challenging. In physics, epitaxial stabilization, also known as pseudomorphic growth, is used to synthesize metastable polymorphs, but usually only as very thin films and on expensive single-crystal substrates. In chemistry, the templated growth of inorganic solid-state materials on selfassembled monolayers of organic molecules is reported. Bridging these two fields, here, we show that the synthesis of metastable polymorphs is possible up to large film thickness on amorphous substrates covered with thin inorganic seed layers that serve as templates. The stabilization of a 500-nm-thick metastable wurtzite (WZ) MnTe film by a 5-nm-thick ZnTe seed layer sputtered on amorphous glass substrates is experimentally demonstrated. Theoretical calculations explain this experimental observation by the small WZ polymorph energy relative to that of the ground-state nickeline (NC) structure of MnTe and a large lattice constant difference of the two. The resulting metastable WZ-MnTe polymorph exhibits a wide band gap of 2.7 eV and a low hole density of 10 12 cm −3 , which is relevant to optoelectronic applications. These properties are in sharp contrast to those of the narrow-band-gap highly doped NC-MnTe with 1.3 eV band gap and 10 19 cm −3 hole density. The difference in hole density is due to the calculated difference in the formation energy of manganese vacancy acceptor defects. Overall, these results suggest that templated growth on amorphous substrates with seed layers can be used to synthesize metastable polymorphs of other materials, without the need for expensive single-crystal substrates.

To extend rational materials design and discovery into the space of metastable polymorphs, rapid and reliable assessment of their lifetimes is essential. Motivated by the early work of Buerger (1951), here we investigate the routes to predict kinetics of polymorphic transformations using solely crystallographic arguments. As part of this investigation we developed a general algorithm to map crystal structures onto each other and construct transformation pathways between them. The developed algorithm reproduces reliably known transformation pathways and reveals the critical role that the dissociation of chemical bonds along the pathway plays in choosing the best (low-energy barrier) mapping. By utilizing our structure-mapping algorithm we were able to quantitatively demonstrate the intuitive expectation that the minimal dissociation of chemical bonds along the pathway, or in ionic systems, the condition of coordination of atoms along the pathway not decreasing below the coordination in the end compounds, represents the requirement for fast transformation kinetics. We also demonstrate the effectiveness of the structure-mapping algorithm in combination with the coordination analysis in studying transformations between polymorphs for which a detailed atomic-level picture is presently elusive.

The development of an economically viable solar thermochemical fuel production process relies largely on identifying redox active materials with optimized thermodynamic and kinetic properties. Iron aluminate (FeAl2O4, hercynite) and cobalt-iron aluminate (CoxFe1-xAl2O4) have both been demonstrated as viable redox-active materials for this process. However, doping with cobalt produces a qualitative tradeoff between the thermodynamic and kinetic properties of hercynite by improving the reaction kinetics although, so far, at the expense of some drop in the overall activity per unit weight. In this work, we evaluate four spinel aluminate materials with varying cobalt contents (FeAl2O4, Co0.05Fe0.95Al2O4, Co0.25Fe0.75Al2O4, and Co0.40Fe0.60Al2O4) to better understand the role of cobalt in the redox mediating properties of these materials and to quantify its effect on the thermodynamic and kinetic properties for CO2 reduction. A solid-state Classification: General Business Use kinetic analysis was performed on each sample to model its CO2 reduction kinetics at temperatures ranging from 1200°C to 1350°C. An F1 model representative of first-order reaction kinetics was found to most accurately represent the experimental data for all materials evaluated. The computed rate constants, activation energies, and pre-exponential factors all increase with increasing cobalt content. High temperature in-situ XPS was utilized to characterize the spinel surfaces and indicated the presence of metallic states of the reduced cobalt-iron spinel, which are not present in un-doped hercynite. These species provide a new site for the CO2 reduction reaction and enhance its rate through an increased pre-exponential factor.

The iron aluminate spinel hercynite (FeAl2O4) is a promising redox material for solar thermochemical hydrogen production (STCH). Although it has a high H2 production capacity, the kinetics of its oxidation and reduction may be too slow to be practical for STCH. However, our results suggest that Fe-rich hercynite may have substantially faster redox kinetics, which could make hercynite competitive with other materials for STCH. We used density functional theory to investigate the origin of hercynite’s slow kinetic behavior and show that it arises from the high activation barrier of 2.46 eV for oxygen vacancy (VO) diffusion in normal hercynite. To model the effect of disorder caused by spinel inversion, we examined 11 of the most common cation arrangements and found a near 1:1 correlation between the diffusion barrier and VO formation energy, both of which decrease by 0.6 eV for each additional nearest-neighbor Fe atom. To examine this trend, we used integrated crystal orbital Hamilton population (ICOHP) analysis to estimate the difference in the metal–oxygen bond strengths of cations neighboring VO and the diffusion transition state. The ICOHP predicted bond strengths correlate to both the diffusion barrier and VO formation energy. We also computed the effect of the charge state of the oxygen vacancy and found that positively charged vacancies are stable at low Fermi energies and have a diffusion barrier of only 0.79 eV, 1.67 eV lower than that of the neutral vacancy, demonstrating that stabilizing these charged vacancies may enable faster oxidation and reduction kinetics in hercynite. We show that uncompensated Fe antisite defects, which are present in Fe-rich hercynite, provide redox flexibility that stabilizes the charged VO and thereby increase the rate of VO diffusion. Finally, we predict that at higher VO concentrations the diffusion barrier depends on the relative positions of the vacancies and decreases when they are next-nearest neighbors.

Herein, we detail an approach to accelerate the computational screening of materials for properties dictated by the kinetics of solid-state diffusion through reliably and rapidly identifying upper and lower bounds to the transition state (TS) energy through our proposed modified single iteration synchronous-transit (MSIST) approach. While this sacrifices providing detailed information of the explicit TS structure, it requires only 30% of the force evaluations of a full nudged elastic band (NEB) TS search and reduces the computational demand to compute estimated diffusion barriers by ∼70% on average. In all 53 cases in which we explicitly compared our results to those of an NEB calculation, the upper and lower bounds identified using this approach bracketed the TS energy calculated with explicit NEB calculations. We use the applications of diffusion of Na+ in potential sodium-ion battery electrodes and oxygen vacancy diffusion in solid-oxide fuel cell electrodes and redox mediators for solar thermochemical hydrogen production to demonstrate the power of MSIST for analyzing the kinetics of bulk diffusion. For Na+ diffusion through 13 proposed electrode materials in which the average diffusion barrier was 0.28 eV, the average difference between the upper and lower bounds was 0.08 eV. An iterative application of this approach to the three materials with the largest difference between their upper and lower bounds further narrowed the average range of the bounded TS energies to 0.04 eV while still requiring fewer force evaluations than an NEB TS calculation. When applied in a high-throughput manner to study 514 diffusion pathways in 97 different materials, the average difference between the upper and lower bounds was 0.33 eV and the average barrier, as calculated by the average of all upper and lower bounds, was ∼1.7 eV. Because the MSIST approach produces explicit errors, i.e., the difference between the upper and lower bounds energies, even predicted barrier ranges with large errors can be reliably modeled with weighted regression techniques. MSIST enables the analysis of the kinetics of solid-state diffusion across larger sets of materials and can thus efficiently provide data to train statistically learned models of diffusion and to develop physical insights into the diffusion process.

To continue to meet global energy demands, efficient methods of utilizing renewable energy must be developed. Converting solar energy into chemical fuels is a promising approach, but efficient and cost effective methods for producing solar fuels have not yet been developed. Solar thermal water splitting is a particularly promising possibility because it has a high theoretical hydrogen production efficiency. However, achieving this efficiency requires finding the proper redox material. Currently, the most promising materials are metal oxides, including spinels and perovskites. These materials split water via a high temperature cycle in which the material is reduced, forming oxygen vacancies, in one step, then oxidized by stripping oxygen from water in the next. An efficient STWS process is extremely demanding on materials and requires that they be thermodynamically capable of being reduced, withstand the high temperatures of solar thermal water splitting, and form oxygen vacancies with enough energy to reduce water. Furthermore, materials must also be kinetically viable, able to complete the water splitting cycle quickly enough to allow for large scale production of hydrogen. The initial reduction step uses concentrated solar energy to heat the material to temperatures exceeding 1350oC and creating oxygen vacancies in the process. This reduced material can subsequently be oxidized by splitting water and forming hydrogen. A variety of materials have been found that can undergo this process, CeO2, FeAl2O4, and SLMA, but they all fall short in some aspect. To discover new STWS materials and optimize these compounds for their STWS abilities, it is important to have a detailed understanding of the electronic structure which governs both the thermodynamics and kinetics of these materials. Using atomistic modeling, we identify the intrinsic material properties that enable high performance for the oxidation and reduction steps of the two-step cycle. This understanding can be used to guide the rational doping of these compounds as well as establish design principles for the design of new high performance materials. While the thermodynamic and kinetics of STWS chemistry can be directly modeled using quantum chemical methods, these calculations are too computationally intensive to examine large numbers of materials to identify promising candidates. This is especially the case for calculations that consider the disordered spin structure and high temperature atomic structure of these materials – which we explicitly account for in our approach. We have developed efficient computational methods to identify STWS materials with desirable thermodynamic and kinetic properties with these critical considerations. We have used high level calculations on a subset of materials to inform a machine learning approach that identifies descriptors for the activation barriers for the rate limiting step for water splitting. These descriptors can be determined from simpler calculations and will allow for rapid calculation and determination of water splitting materials. This work focuses on the use of density functional theory to develop general descriptors of the water splitting reaction and in turn a more fundamental understanding of the reaction mechanism and efficient approach to screening materials for their STWS kinetics.