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Analogical discovery of disordered perovskite oxides by crystal structure information hidden in unsupervised material fingerprints

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 Added by Achintha Ihalage
 Publication date 2021
  fields Physics
and research's language is English




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Compositional disorder induces myriad captivating phenomena in perovskites. Target-driven discovery of perovskite solid solutions has been a great challenge due to the analytical complexity introduced by disorder. Here, we demonstrate that an unsupervised deep learning strategy can find fingerprints of disordered materials that embed perovskite formability and underlying crystal structure information by learning only from the chemical composition, manifested in (A1-xAx)BO3 and A(B1-xBx)O3 formulae. This phenomenon can be capitalized to predict the crystal symmetry of experimental compositions, outperforming several supervised machine learning (ML) algorithms. The educated nature of material fingerprints has led to the conception of analogical materials discovery that facilitates inverse exploration of promising perovskites based on similarity investigation with known materials. The search space of unstudied perovskites is screened from ~600,000 feasible compounds using experimental data powered ML models and automated web mining tools at a 94% success rate. This concept further provides insights on possible phase transitions and computational modelling of complex compositions. The proposed quantitative analysis of materials analogies is expected to bridge the gap between the existing materials literature and the undiscovered terrain.



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ABO3 oxides with the perovskite-related structures are attracting significant interest due to their promising physical and chemical properties for many applications requiring tunable chemistry, including fuel cells, catalysis, and electrochemical water splitting. Here we report on the crystal structure of the entire family of perovskite oxides with ABO3 stoichiometry, where A and B are Ba, Sr, Mn, Ce. Given the vast size of this chemically complex material system, exploration for stable perovskite-related structures with respect to its constituent elements and annealing temperature is performed by combinatorial pulsed laser deposition and spatially-resolved characterization of composition and structure. As a result of this high-throughput experimental study, we identify hexagonal perovskite-related polytypic transformation as a function of composition in the Ba1-xSrxMnO3 oxides after annealing at different temperatures. Furthermore, a hexagonal perovskite-related polytype is observed in a narrow composition-temperature range of the BaCexMn1-xO3 oxides. In contrast, a tetragonally-distorted perovskite is observed across a wider range of compositions and annealing temperatures in the Sr1-xCexMnO3 oxides. This structure stability is further enhanced along the BaCexMn1-xO3 - Sr1-xCexMnO3 pseudo-binary tie-line at x=0.25 by increasing Ba-incorporation and annealing temperature. These results indicate that the BaCexMn1-xO3 - Sr1-xCexMnO3 pseudo-binary oxide alloys (solid solutions) with tetragonal perovskite structure and broad composition-temperature range of stability are promising candidates for thermochemical water splitting applications.
We show that the magnetism of double perovskite AFe_{1/2}M_{1/2}O_3 systems may be described by the Heisenberg model on the simple cubic lattice, where only half of sites are occupied by localized magnetic moments. The nearest-neighbor interaction J_1 is more than 20 times the next-nearest neighbor interaction J_2, the third-nearest interaction along the space diagonal of the cube being negligible. We argue that the variety of magnetic properties observed in different systems is connected with the variety of chemical ordering in them. We analyze six possible types of the chemical ordering in 2x2x2 supercell, and argue that the probability to find them in a real compound does not correspond to a random occupation of lattice sites by magnetic ions. The exchange J_2 rather than J_1 define the magnetic energy scale of most double perovskite compounds that means the enhanced probability of 1:1 short range ordering. Two multiferroic compounds PbFe_{1/2}M_{1/2}O_3 (M=Nb, Ta) are exceptions. We show that the relatively high temperature of antiferromagnetic transition is compatible with a layered short-range chemical order, which was recently shown to be most stable for these two compounds [I. P. Raevski, {em et al.}, Phys. Rev. B textbf{85}, 224412 (2012)]. We show also that one of the types of ordering has ferrimagnetic ground state. The clusters with short-range order of this type may be responsible for a room-temperature superparamagnetism, and may form the cluster glass at low temperatures.
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Crystal structures play a vital role in determining materials properties. In Li-ion cathodes, the crystal structure defines the dimensionality and connectivity of interstitial sites, thus determining Li-ion diffusion kinetics. While a perfect crystal has infinite structural coherence, a class of recently discovered high-capacity cathodes, Li-excess cation-disordered rocksalts, falls on the other end of the spectrum: Their cation sublattices are assumed to be randomly populated by Li and transition metal ions with zero configurational coherence based on conventional X-ray diffraction, such that the Li transport is purely determined by statistical effects. In contrast to this prevailing view, we reveal that cation short-range order, hidden in diffraction, is ubiquitous in these long-range disordered materials and controls the local and macroscopic environments for Li-ion transport. Our work not only discovers a crucial property that has previously been overlooked, but also provides new guidelines for designing and engineering disordered rocksalts cathode materials.

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