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Register a new userIdentifying outstanding transition-metal-alloy heterogeneous catalysts for the oxygen reduction and evolution reactions via subgroup discovery
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In order to estimate the reactivity of a large number of potentially complex heterogeneous catalysts while searching for novel and more efficient materials, physical as well as data-centric models have been developed for a faster evaluation of adsorption energies compared to first-principles calculations. However, global models designed to describe as many materials as possible might overlook the very few compounds that have the appropriate adsorption properties to be suitable for a given catalytic process. Here, the subgroup-discovery (SGD) local artificial-intelligence approach is used to identify the key descriptive parameters and constrains on their values, the so-called SG rules, which particularly describe transition-metal surfaces with outstanding adsorption properties for the oxygen reduction and evolution reactions. We start from a data set of 95 oxygen adsorption energy values evaluated by density-functional-theory calculations for several monometallic surfaces along with 16 atomic, bulk and surface properties as candidate descriptive parameters. From this data set, SGD identifies constraints on the most relevant parameters describing materials and adsorption sites that (i) result in O adsorption energies within the Sabatier-optimal range required for the oxygen reduction reaction and (ii) present the largest deviations from the linear scaling relations between O and OH adsorption energies, which limit the performance in the oxygen evolution reaction. The SG rules not only reflect the local underlying physicochemical phenomena that result in the desired adsorption properties but also guide the challenging design of alloy catalysts.
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Symbolic regression (SR) is an emerging method for building analytical formulas to find models that best fit data sets. Here, SR was used to guide the design of new oxide perovskite catalysts with improved oxygen evolution reaction (OER) activities. An unprecedentedly simple descriptor, {mu}/t, where {mu} and t are the octahedral and tolerance factors, respectively, was identified, which accelerated the discovery of a series of new oxide perovskite catalysts with improved OER activity. We successfully synthesized five new oxide perovskites and characterized their OER activities. Remarkably, four of them, Cs0.4La0.6Mn0.25Co0.75O3, Cs0.3La0.7NiO3, SrNi0.75Co0.25O3, and Sr0.25Ba0.75NiO3, outperform the current state-of-the-art oxide perovskite catalyst, Ba0.5Sr0.5Co0.8Fe0.2O3 (BSCF). Our results demonstrate the potential of SR for accelerating data-driven design and discovery of new materials with improved properties.
Inorganic oxyfluorides have significant importance in the development of new functionalities for energy production and storage, photonics, catalysis, etc. In order to explore a simple preparation route that avoids the use of toxic HF or F2 gas as a reaction reagent, we have employed polytetrafluoroethylene (PTFE). Five oxyfluorides including Nb5O12F, Nb3O7F, Ta3O7F, TaO2F, and Mo4O11.2F0.8 were synthesized by reactions between PTFE and transition metal oxides in sealed quartz ampules. The reaction mechanism was studied by means of gas analysis, which detected SiF4 as a main product gas during the reaction. A possible reaction mechanism between the PTFE and transition metal oxides is discussed.
It is shown that producing PrBaCo2O5 and Ba0.5Sr0.5Co0.8Fe0.2O3 nanoparticle by a scalable synthesis method leads to high mass activities for the oxygen evolution reaction with outstanding improvements by 10 and 50 times, respectively, compared to those prepared via the state of the art synthesis method. Here, detailed comparisons at both laboratory and industrial scales show that Ba0.5Sr0.5Co0.8Fe0.2O3 appears to be the most active and stable perovskite catalyst under alkaline conditions, while PrBaCo2O6 reveals thermodynamic instability described by the density functional theory based Pourbaix diagrams highlighting cation dissolution under oxygen evolution conditions. Operando Xray absorption spectroscopy is used in parallel to monitor electronic and structural changes of the catalysts during oxygen evolution reaction. The exceptional BSCF functional stability can be correlated to its thermodynamic metastability under oxygen evolution conditions as highlighted by Pourbaix diagram analysis. BSCF is able to dynamically self reconstruct its surface, leading to formation of Co based oxyhydroxide layers while retaining its structural stability. Differently, PBCO demonstrates a high initial oxygen evolution reaction activity while it undergoes a degradation process considering its thermodynamic instability under oxygen evolution conditions as anticipated by its Pourbaix diagram. Overall, this work demonstrates a synergetic approach of using both experimental and theoretical studies to understand the behavior of perovskite catalysts.
Chalcogen vacancies are considered to be the most abundant point defects in two-dimensional (2D) transition-metal dichalcogenide (TMD) semiconductors, and predicted to result in deep in-gap states (IGS). As a result, important features in the optical response of 2D-TMDs have typically been attributed to chalcogen vacancies, with indirect support from Transmission Electron Microscopy (TEM) and Scanning Tunneling Microscopy (STM) images. However, TEM imaging measurements do not provide direct access to the electronic structure of individual defects; and while Scanning Tunneling Spectroscopy (STS) is a direct probe of local electronic structure, the interpretation of the chemical nature of atomically-resolved STM images of point defects in 2D-TMDs can be ambiguous. As a result, the assignment of point defects as vacancies or substitutional atoms of different kinds in 2D-TMDs, and their influence on their electronic properties, has been inconsistent and lacks consensus. Here, we combine low-temperature non-contact atomic force microscopy (nc-AFM), STS, and state-of-the-art ab initio density functional theory (DFT) and GW calculations to determine both the structure and electronic properties of the most abundant individual chalcogen-site defects common to 2D-TMDs. Surprisingly, we observe no IGS for any of the chalcogen defects probed. Our results and analysis strongly suggest that the common chalcogen defects in our 2D-TMDs, prepared and measured in standard environments, are substitutional oxygen rather than vacancies.
Metal-insulator transitions (MIT),an intriguing correlated phenomenon induced by the subtle competition of the electrons repulsive Coulomb interaction and kinetic energy, is of great potential use for electronic applications due to the dramatic change in resistivity. Here, we demonstrate a reversible control of MIT in VO2 films via oxygen stoichiometry engineering. By facilely depositing and dissolving a water-soluble yet oxygen-active Sr3Al2O6 capping layer atop the VO2 at room temperature, oxygen ions can reversibly migrate between VO2 and Sr3Al2O6, resulting in a gradual suppression and a complete recovery of MIT in VO2. The migration of the oxygen ions is evidenced in a combination of transport measurement, structural characterization and first-principles calculations. This approach of chemically-induced oxygen migration using a water-dissolvable adjacent layer could be useful for advanced electronic and iontronic devices and studying oxygen stoichiometry effects on the MIT.
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