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RESEARCH PAPER · Physical Review Letters · 2016

Sampling Polymorphs of Ionic Solids using Random Superlattices

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Sampling Polymorphs of Ionic Solids using Random SuperlatticesOriginalSynthesis of a mixed-valent tin nitride and considerations of its possible crystal structures41The thermodynamic scale of inorganic crystalline metastability959A computational framework for automation of point defect calculations210Phase stability and electronic behavior of MgS, MgSe and MgTe compounds35Design of Metastable Tin Titanium Nitride Semiconductor Alloys35Computationally guided discovery of thermoelectric materials277Polymorphism in elemental silicon: Probabilistic interpretation of the realizability of metastable structures25Thermodynamic Stability of Molybdenum Oxycarbides Formed from Orthorhombic Mo2C in Oxygen-Rich Environments51Crystal structure prediction: reflections on present status and challenges86Critical role of electronic correlations in determining crystal structure of transition metal compounds9Predicting kinetics of polymorphic transformations from structure mapping and coordination analysis19Traversing Energy Landscapes Away from Equilibrium: Strategies for Accessing and Utilizing Metastable Phase Space94Correlated materials design: prospects and challenges46Quest for New Thermoelectric Materials2Connection between Mott physics and crystal structure in a series of transition metal binary compounds25Structure prediction drives materials discovery717Using symmetry to elucidate the importance of stoichiometry in colloidal crystal assembly16Predicting the phase diagram of titanium dioxide with random search and pattern recognition36Screening for Planar Carbon Allotropes Using Structure Space Sampling10The glassy solid as a statistical ensemble of crystalline microstates33Metastability at Defective Metal Oxide Interfaces and Nanoconfined Structures45Predicting the phase diagram of titanium dioxide with random search and pattern recognition.9Identification of synthesisable crystalline phases of water – a prototype for the challenges of computational materials design1The role of disorder in the synthesis of metastable ternary nitrides2Selective Synthesis of α-, β-, and γ-Ag2WO4 Polymorphs: Promising Platforms for Photocatalytic and Antibacterial Materials66Promises and perils of computational materials databases43Biased screening for multi-component materials with Structures of Alloy Generation And Recognition (SAGAR)39First-principles design of halide-reduced electrides: Magnetism and topological phases6Ternary Nitride Materials: Fundamentals and Emerging Device Applications96Study of disorder in pulsed laser deposited double perovskite oxides by first-principle structure prediction10Metastable materials discovery in the age of large-scale computation53Large-scale structure prediction of near-stoichiometric magnesium oxide based on a machine-learned interatomic potential: Crystalline phases and oxygen-vacancy ordering11Predicting energy and stability of known and hypothetical crystals using graph neural network43Free energy predictions for crystal stability and synthesisability47Experimental Synthesis of Theoretically Predicted Multivalent Ternary Nitride Materials73Role of disorder in the synthesis of metastable zinc zirconium nitrides37Guiding epitaxial crystallization of amorphous solids at the nanoscale: Interfaces, stress, and precrystalline order11Structure and stability of van der Waals layered group-IV monochalcogenides3Organic crystal structure prediction and its application to materials design69Phase diagrams—Why they matter and how to predict them63Predicting and accessing metastable phases9Polymorphism of group-IV carbides: Structures, (meta)stability, electronic, and transport properties11Simulating high-entropy alloys at finite temperatures: An uncertainty-based approach11Resolving local ordering and structure in Mn x Ge 1− x Te alloys through thermodynamic ensembles of pair distribution functions1Synthesizability of materials stoichiometry using semi-supervised learning21From Design to Device: Challenges and Opportunities in Computational Discovery of p -Type Transparent Conductors18All “Roads” Lead to Rocksalt Structure15Synthesis pathways to thin films of stable layered nitrides18Automated high-throughput organic crystal structure prediction via population-based sampling8Predicting emergence of crystals from amorphous precursors with deep learning potentials12Basin-Size Mapping: Prediction of Metastable Polymorph Synthesizability Across TaC–TaN Alloys3Modeling glasses from first principles using random structure sampling6Discovering Stable Amorphous Ceramics: From Computational Prediction to Thin‐Film Synthesis4High throughput and machine learning approaches for thermoelectric materials4Structural stability, elemental ordering, and transport properties of layered ScTaN 20Effective bands and band-like electron transport in amorphous solids6First-principles study of the phase competition, and mechanical and piezoelectric properties of pseudo-binary (SiC) 1− x (AlN) x alloy0An Investigation into the Kinetic Persistence of TiO2 Polymorphs Using Machine-Learning-Driven Pathfinding in Crystal Configuration Space0

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