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Single phase, polycrystalline perovskite oxide SrVO3, with its intrinsic low effective work function and facile synthesis process, is a promising thermionic electron emitter cathode candidate, in which previous works have shown evidence of an effective work function as low as 2.3 eV. In this work, we study the vacuum activation process of SrVO3 and find that it has promising emission stability over 15 days of continuous high temperature operation. We find that SrVO3 shows surface Sr and O segregation during its operation, which we hypothesize is needed to create a positive surface dipole, leading to a low effective work function. Emission repeatability from cyclic heating and cooling suggests the promising stability of the low effective work function surface, and additional observations of drift-free emission during 1 h of continuous emission testing at high temperature further demonstrate its excellent performance stability. This assessment of the emission stability over time and the interplay of evolving surface chemistry with emission behavior are necessary for understanding how best to prepare, process, and operate SrVO3 cathodes. [ABSTRACT FROM AUTHOR]

Discovering new materials that efficiently catalyze the oxygen reduction and evolution reactions is critical for facilitating the widespread adoption of solid oxide fuel cell and electrolyzer (SOFC/SOEC) technologies. Here, machine learning (ML) models are developed to predict perovskite catalytic properties critical for SOFC/SOEC applications, including oxygen surface exchange, oxygen diffusivity, and area specific resistance (ASR). The models are based on trivial‐to‐calculate elemental features and are more accurate and dramatically faster than the best models based on ab initio‐derived features, potentially eliminating the need for ab initio calculations in descriptor‐based screening. The model of ASR enables temperature‐dependent predictions, has well calibrated uncertainty estimates and online accessibility. Use of temporal cross‐validation reveals the model to be effective at discovering new promising materials prior to their initial discovery, demonstrating the model can make meaningful predictions. Using the SHapley Additive ExPlanations (SHAP) approach, detailed discussion of different approaches of model featurization is provided for ML property prediction. Finally, the model is used to screen more than 19 million perovskites to develop a list of promising cheap, earth‐abundant, stable, and high performing materials, and find some top materials contain mixtures of less‐explored elements (e.g., K, Bi, Y, Ni, Cu) worth exploring in more detail. [ABSTRACT FROM AUTHOR]

Oxygen vacancy formation energy is an important quantity for enabling fast oxygen diffusion and oxygen catalysis in technologies like solid oxide fuel cells. Both previous literature in various systems and our calculations in LaMnO 3 , La 0.75 Sr 0.25 MnO 3 , LaFeO 3 , and La 0.75 Sr 0.25 FeO 3 , show mixed results for the direction and magnitude of the change in vacancy formation energy with strain. This paper develops a model to make sense of the different trend shapes in vacancy formation energy versus strain. We model strain effects using a set of consistent ab initio calculations, and demonstrate that our calculated results may be simply explained in terms of vacancy formation volume and changes in elastic constants between the bulk and defected states. A positive vacancy formation volume contributes to decreased vacancy formation energy under tensile strain, and an increase in elastic constants contributes to increases in vacancy formation energy with compressive and tensile strains, and vice versa. The vacancy formation volume dominates the linear portion of the vacancy formation energy strain response, while its curvature is governed by the vacancy-induced change in elastic constants. We show results sensitive to B-site cation, A-site doping, tilt system, and vacancy placement, which contributions may be averaged under thermally averaged conditions. In general, vacancy formation energies for most systems calculated here decreased with tensile strain, with about a 30–100 meV/% strain decrease with biaxial strain for those systems which showed a decrease in vacancy formation energy. Experimental verification is necessary to confirm the model outside of calculation. [ABSTRACT FROM AUTHOR]

Perovskites with fast oxygen ion conduction can enable technologies like solid oxide fuel cells. One component of fast oxygen ion conduction is low oxygen migration barrier. Here we apply ab initio methods on over 40 perovskites to produce a database of oxygen migration barriers ranging from 0.2 to 1.6 eV. Mining the database revealed that systems with low barriers also have low metal-oxygen bond strength, as measured by oxygen vacancy formation energy and oxygen p-band center energy. These correlations provide a powerful descriptor for the development of new oxygen ion conductors and may explain the poor stability of some of the best oxygen conducting perovskites under reducing conditions. Other commonly-cited measures of space, volume, or structure ideality showed only weak correlation with migration barrier. The lowest migration barriers (< 0.5 eV) belong to perovskites with non-transition-metal B-site cations, and may require vacancy-creation strategies that involve no dopants or low-association dopants for optimal performance. [ABSTRACT FROM AUTHOR]

Perovskite oxides containing transition metals are promising materials in a wide range of electronic and electrochemical applications. However, neither their work function values nor an understanding of their work function physics have been established. Here, the work function trends of a series of perovskite (ABO3 formula) materials using density functional theory are predicted, and show that the work functions of (001)-terminated AO- and BO2-oriented surfaces can be described using concepts of electronic band filling, bond hybridization, and surface dipoles. The calculated range of AO (BO2) work functions are 1.60-3.57 eV (2.99-6.87 eV). An approximately linear correlation ( R2 between 0.77 and 0.86 is found, depending on surface termination) between work function and position of the oxygen 2 p band center, which correlation enables both understanding and rapid prediction of work function trends. Furthermore, SrVO3 is identified as a stable, low work function, highly conductive material. Undoped (Ba-doped) SrVO3 has an intrinsically low AO-terminated work function of 1.86 eV (1.07 eV). These properties make SrVO3 a promising candidate material for a new electron emission cathode for application in high power microwave devices, and as a potential electron emissive material for thermionic energy conversion technologies. [ABSTRACT FROM AUTHOR]

In this paper, we perform a comparative study based on ab initio modeling for perovskite ABO3 (001) surfaces and surface defect energetics in order to understand the influence of polarity and redox active Mn in the LaMnO3 system. We consider LaMnO3,LaAlO3,SrTiO3, and briefly LaFeO3 systems for comparison, which illustrate the interplay between properties of polar surfaces and the varying d-electron shell of transition metals. We are motivated by the need to understand the surfaces of mixed electronic and ionic conductors typically used in solid oxide fuel cell cathodes and other ion conducting technologies, which are represented here by the LaMnO3 system. We focus on the influence of the metal character and surface polarity on the surface and surface defect chemistry in these selected systems. We demonstrate that the facile redox of the TM (3d4) in LaMnO3 with partial eg orbital occupation (or specifically eg occupancy close to 1) allows the polar surfaces to be compensated by changes in charge density over relatively short length scales (3 to 4 unit cells or ∼1.5 nm) near the surface as compared to LaAlO3. In contrast to LaAlO3, this low-energy and short-range screening mechanism leads to low surface energies without any additional reconstruction, rapidly converging surface properties with film thickness (by ∼8 unit cells), bulklike defect chemistry more than ∼1.5 nm from the surface, and surface defect energetics that are primarily governed by the local charge doping or the created electric field near the polar surfaces. We show that LaMnO3 exhibits very different surface properties from LaAlO3 and SrTiO3, thereby demonstrating that these properties are due to the presence of the redox active transition metal with partial eg orbital occupation and a polar surface, respectively. These understandings can help guide qualitative analysis, computational study, and design of surfaces of mixed electronic and ionic conductors. [ABSTRACT FROM AUTHOR]

The high-pressure behavior of magnetite has been widely debated in the literature. Experimental measurements have found conflicting high-pressure transitions: a charge reordering in magnetite from inverse-spinel to normal-spinel [ Pasternak et al. J. Phys. Chem. Solids 65 1531 (2004); Rozenberg et al. Phys. Rev. B 75 020102 (2007)], iron high-spin to intermediate-spin transition in magnetite [ Ding et al. Phys. Rev. Lett. 100 045508 (2008)], electron delocalization in magnetite [ Baudelet et al. Phys. Rev. B 82 140412 (2010); Glazyrin et al. Am. Mineral. 97 128 (2012)], and a structural phase transition from magnetite to h-Fe3O4 [ Dubrovinsky et al. J. Phys.: Condens. Matter 15 7697 (2003); Fei et al. Am. Mineral. 84 203 (1999); Haavik et al. Am. Mineral. 85 514 (2000)]. We present ab initio calculations of iron's spin state in magnetite and h-Fe3O4, which help resolve the high-pressure debate. The results of the calculations find that iron remains high spin in both magnetite and h-Fe3O4; intermediate-spin iron is not stable. In addition, magnetite remains inverse-spinel but undergoes a phase transition to h-Fe3O4 near 10 GPa. Magnetite has a complex magnetic ordering, multiple valence states (Fe2+ and Fe3+), charge ordering, and different local Fe site environments, all of which were accounted for in the calculations. The lack of intermediate-spin iron in magnetite helps resolve the spin state of iron in perovskite, the major mineral in the lower mantle. In both magnetite and perovskite, x-ray emission spectroscopy (XES) measurements in the literature show a drop in satellite peak intensity by approximately half, which is interpreted as intermediate-spin iron. In both minerals, calculations give no indication of intermediate-spin iron and predict high-spin iron to be stable for defect-free crystals. The results question the interpretation of a nonzero drop in XES satellite peak intensities as intermediate-spin iron. [ABSTRACT FROM AUTHOR]

Two critical limitations of organic–inorganic lead halide perovskite materials for solar cells are their poor stability in humid environments and inclusion of toxic lead. In this study, high‐throughput density functional theory (DFT) methods are used to computationally model and screen 1845 halide perovskites in search of new materials without these limitations that are promising for solar cell applications. This study focuses on finding materials that are comprised of nontoxic elements, stable in a humid operating environment, and have an optimal bandgap for one of single junction, tandem Si‐perovskite, or quantum dot–based solar cells. Single junction materials are also screened on predicted single junction photovoltaic (PV) efficiencies exceeding 22.7%, which is the current highest reported PV efficiency for halide perovskites. Generally, these methods qualitatively reproduce the properties of known promising nontoxic halide perovskites that are either experimentally evaluated or predicted from theory. From a set of 1845 materials, 15 materials pass all screening criteria for single junction cell applications, 13 of which are not previously investigated, such as (CH3NH3)0.75Cs0.25SnI3, ((NH2)2CH)Ag0.5Sb0.5Br3, CsMn0.875Fe0.125I3, ((CH3)2NH2)Ag0.5Bi0.5I3, and ((NH2)2CH)0.5Rb0.5SnI3. These materials, together with others predicted in this study, may be promising candidate materials for stable, highly efficient, and nontoxic perovskite‐based solar cells. [ABSTRACT FROM AUTHOR]

Perovskite materials have become ubiquitous in many technologically relevant applications, ranging from catalysts in solid oxide fuel cells to light absorbing layers in solar photovoltaics. The thermodynamic phase stability is a key parameter that broadly governs whether the material is expected to be synthesizable, and whether it may degrade under certain operating conditions. Phase stability can be calculated using Density Functional Theory (DFT), but the significant computational cost makes such calculation potentially prohibitive when screening large numbers of possible compounds. In this work, we developed machine learning models to predict the thermodynamic phase stability of perovskite oxides using a dataset of more than 1900 DFT-calculated perovskite oxide energies. The phase stability was determined using convex hull analysis, with the energy above the convex hull (E hull ) providing a direct measure of the stability. We generated a set of 791 features based on elemental property data to correlate with the E hull value of each perovskite compound, and found through feature selection that the top 70 features were sufficient to produce the most accurate models without significant overfitting. For classification, the extra trees algorithm achieved the best prediction accuracy of 0.93 (±0.02), with an F 1 score of 0.88 (±0.03). For regression, leave-out 20% cross-validation tests with kernel ridge regression achieved the minimal root mean square error (RMSE) of 28.5 (±7.5) meV/atom between cross-validation predicted E hull values and DFT calculations, with the mean absolute error (MAE) in cross-validation energies of 16.7 (±2.3) meV/atom. This error is within the range of errors in DFT formation energies relative to elemental reference states when compared to experiments and therefore may be considered sufficiently accurate to use in place of full DFT calculations. We further validated our model by predicting the stability of compounds not present in the training set and demonstrated our machine learning models are a fast and effective means of obtaining qualitatively useful guidance for a wide-range of perovskite oxide stability, potentially impacting materials design choices in a variety of technological applications. [ABSTRACT FROM AUTHOR]

We have studied the ferrous (Fe 2+ ) and ferric (Fe 3+ ) iron concentrations in Al-free Fe containing Mg-silicate perovskite (Mg-Pv) at pressure ( P ), temperature ( T ), and oxygen fugacity ( f O 2 ) conditions related to the lower mantle using a thermodynamic model based on ab initio calculations. We consider the oxidation reaction and the charge disproportionation reaction, both of which can produce Fe 3+ in Mg-Pv. The model shows qualitatively good agreement with available experimental data on Fe 3+ / Σ Fe ( Σ Fe = total Fe in system), spin transitions, and equations of state. We predict that under lower-mantle conditions Fe 3+ / Σ Fe determined by the charge disproportionation is estimated to be 0.01–0.07 in Al-free Mg-Pv, suggesting that low Al Mg-Pv in the uppermost pyrolitic mantle (where majoritic garnet contains most of the Al) and in the harzburgitic heterogeneities throughout the lower mantle contains very little Fe 3+ . We find that the volume reduction by the spin transition of the B-site Fe 3+ leads to a minimum Fe 3+ / Σ Fe in Mg-Pv at mid-mantle pressures. The model shows that configurational entropy is a key driving force to create Fe 3+ and therefore Fe 3+ content is highly temperature sensitive. The temperature sensitivity may lead to a maximum Fe 3+ / Σ Fe in Mg-Pv in warm regions at the core–mantle boundary region, such as Large Low Shear Velocity Provinces (LLSVPs), potentially altering the physical (e.g., bulk modulus) and transport (e.g., thermal and electrical conductivities) properties of the heterogeneities. [ABSTRACT FROM AUTHOR]

Abstract: We present ab initio calculations of the zero-temperature iron high- to low-spin crossover in (Mg1− x Fe x )SiO3 perovskite at pressures relevant to Earth''s lower mantle. Equations of state are fit for a range of compositions and used to predict the Fe spin transition pressure and associated changes in volume and bulk modulus. We predict a dramatic decrease in transition pressure as Fe concentration increases. This trend is contrary to that seen in ferropericlase, and suggests the energetics for spin crossover is highly dependent on the structural environment of Fe. Both Local Density Approximation (LDA) and Generalized Gradient Approximation (GGA) exchange-correlation methods are used, and both methods reproduce the same compositional trends. However, GGA gives a significantly higher transition pressure than LDA. The spin transition is made easier by the decreasing spin-flip energy with pressure but is also driven by the change in volume from high to low spin. Volume trends show that high-spin Fe2+ is larger than Mg2+ even under pressure, but low-spin Fe2+ is smaller at ambient conditions and approximately the same size as Mg2+ under high pressure, indicating that low-spin Fe2+ is less compressible than high-spin Fe2+. We find large changes between high- and low-spin in the slope of volume with Fe concentration. Although these changes are small in absolute magnitude for small Fe content, they are still important when measured per Fe and could be relevant for calculating partitioning coefficients in the lower mantle. [Copyright &y& Elsevier]

Knowledge of Fe composition in lower-mantle minerals (primarily perovskite and ferropericlase) is essential to a complete understanding of the Earth's interior. Fe cation diffusion potentially controls many aspects of the distribution of Fe in the Earth's lower mantle, including mixing of chemical heterogeneities, element partitioning, and the extent of core-mantle communications. Fe in ferropericlase has been shown to undergo a spin transition starting at about 40 GPa and exists in a mixture of high-spin and low-spin states over a wide range of pressures. Present experimental data on Fe transport in ferropericlase is limited to pressures below 35 GPa and provides little information on the pressure dependence of the activation volume and none on the impact of the spin transition on diffusion. Therefore, known experimental data on Fe diffusion cannot be reliably extrapolated to predict diffusion throughout the lower mantle. Here, first-principles and statistical modeling are combined to predict diffusion of Fe in ferropericlase over the entire lower mantle, including the effects of the Fe spin transition. A thorough statistical thermodynamic treatment is given to fully incorporate the coexistence of high- and low-spin Fe in the model of overall Fe diffusion in the lower mantle. Pure low-spin Fe diffuses approximately 104 times slower than high-spin Fe in ferropericlase but Fe diffusion of the mixed-spin state is only about 10 times slower than that of high-spin Fe. The predicted Fe diffusivities demonstrate that ferropericlase is unlikely to be rate limiting in transporting Fe in deep earth since much slower Fe diffusion in perovskite is predicted. [ABSTRACT FROM AUTHOR]