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RESEARCH PAPER · Chemical Society Reviews · 2016

Computational materials design of crystalline solids

Keith T. Butler, Jarvist Moore Frost, Jonathan Michael Skelton, Katrine Louise Svane, Aron Walsh

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Computational materials design of crystalline solidsOriginalOrganised chaos: entropy in hybrid inorganic–organic systems and other materials69Computational Screening of All Stoichiometric Inorganic Materials177Chemical principles for electroactive metal–organic frameworks49ChemInform Abstract: Computational Materials Design of Crystalline Solids0Defect Engineering in Multinary Earth‐Abundant Chalcogenide Photovoltaic Materials357Electroactive Nanoporous Metal Oxides and Chalcogenides by Chemical Design11Perspective: Theory and simulation of hybrid halide perovskites140Perspective: Theory and simulation of hybrid halide perovskites86Developing a Descriptor-Based Approach for CO and NO Adsorption Strength to Transition Metal Sites in Zeolites48Quantum Mechanical/Molecular Mechanical ( QM / MM ) Approaches14Selection Metric for Photovoltaic Materials Screening Based on Detailed-Balance Analysis81Diffusion in energy materials: Governing dynamics from atomistic modelling34Instilling defect tolerance in new compounds298Comparison of approximations in density functional theory calculations: Energetics and structure of binary oxides140Full space device optimization for solar cells58High-Throughput Computational Assessment of Previously Synthesized Semiconductors for Photovoltaic and Photoelectrochemical Devices66In silico design of chiral dimers to direct the synthesis of a chiral zeolite13Efficient First-Principles Calculation of Phonon-Assisted Photocurrent in Large-Scale Solar-Cell Devices74Computational Design of Photovoltaic Materials4The Optical Diode Ideality Factor Enables Fast Screening of Semiconductors for Solar Cells39Effects of composition, crystal structure, and surface orientation on band alignment of divalent metal oxides: A first-principles study36Material design of indium-based compounds: Possible candidates for charge, valence, and bond disproportionation and superconductivity17Materials‐Informatics‐Assisted High‐Yield Synthesis of 2D Nanomaterials through Exfoliation32Advances in modelling and simulation of halide perovskites for solar cell applications93From DFT to machine learning: recent approaches to materials science–a review848Heteroanionic Materials by Design: Progress Toward Targeted Properties236Shining Light on Sulfide Perovskites: LaYS3 Material Properties and Solar Cells43Theoretical prediction of thermal and electronic properties of metal-organic frameworks14Recent advances and applications of machine learning in solid-state materials science2604The Inorganic Crystal Structure Database ( ICSD ): A Tool for Materials Sciences17Experiment‐Oriented Materials Informatics for Efficient Exploration of Design Strategy and New Compounds for High‐Performance Organic Anode25Recent developments in the Inorganic Crystal Structure Database: theoretical crystal structure data and related features740Linking synthesis and structure descriptors from a large collection of synthetic records of zeolite materials123A high throughput molecular screening for organic electronics via machine learning: present status and perspective72MATGANIP: Learning to Discover the Structure-Property Relationship in Perovskites with Generative Adversarial Networks5Charge-enhanced thiourea catalysts as hydrogen bond donors for Friedel‒Crafts Alkylations8Rapid Characterization and Parameter Space Exploration of Perovskites Using an Automated Routine12Machine Learning for Catalysis Informatics: Recent Applications and Prospects611Machine-enabled inverse design of inorganic solid materials: promises and challenges190Machine-learning-assisted search for functional materials over extended chemical space25The uncertainty pyramid for electronic-structure methods9The micromechanical model to computationally investigate cooperative and correlated phenomena in metal–organic frameworks16Descriptors for dielectric constants of perovskite-type oxides by materials informatics with first-principles density functional theory27Lattice dynamics of Pnma Sn(S1–xSex) solid solutions: energetics, phonon spectra and thermal transport7Computational functionality‐driven design of semiconductors for optoelectronic applications58The adsorption and migration behavior of divalent metals (Mg, Ca, and Zn) on pristine and defective graphene57Support work function as a descriptor and predictor for the charge and morphology of deposited Au nanoparticles8Estimating DFT calculated voltage using machine learning regression models4Accuracy of Hybrid Functionals with Non-Self-Consistent Kohn–Sham Orbitals for Predicting the Properties of Semiconductors36Metastability at Defective Metal Oxide Interfaces and Nanoconfined Structures45On the Largest Possible Mobility of Molecular Semiconductors and How to Achieve It75Evaluation-oriented exploration of photo energy conversion systems: from fundamental optoelectronics and material screening to the combination with data science84An overview of the mathematical modelling of perovskite solar cells towards achieving highly efficient perovskite devices36Critical review of machine learning applications in perovskite solar research139Perovskite-inspired materials for photovoltaics and beyond—from design to devices206Computational and data driven molecular material design assisted by low scaling quantum mechanics calculations and machine learning57Energetics of Electron Pairs in Electrophilic Aromatic Substitutions6Predicting stable crystalline compounds using chemical similarity113Topological representations of crystalline compounds for the machine-learning prediction of materials properties112Optimizing machine learning models for granular NdFeB magnets by very fast simulated annealing24On the Study of Crystal Structures by Simulation and Modeling0Optimization of carrier transport materials for the performance enhancement of the MAGeI3 based perovskite solar cell137Experiment‐Oriented Machine Learning of Polymer:Non‐Fullerene Organic Solar Cells94Enabling Circular Economy: The Overlooked Role of Inorganic Materials Chemistry14Machine Learning Meets with Metal Organic Frameworks for Gas Storage and Separation239Machine Learning in Magnetic Materials48Ab initio random structure searching for battery cathode materials41The Advantage of Nanowire Configuration in Band Structure Determination9Genetic Algorithms and Machine Learning for Predicting Surface Composition, Structure, and Chemistry: A Historical Perspective and Assessment22Panoramic (in beam) studies of materials synthesis1Machine‐Learning‐Assisted Accurate Prediction of Molecular Optical Properties upon Aggregation59Artificial intelligence: machine learning for chemical sciences104Machine Learning-Assisted Development of Organic Solar Cell Materials: Issues, Analyses, and Outlooks98Curie Temperature Prediction of BiFeO3-PbTiO3-BaTiO3 Solid Solution Based on Machine Learning4Data-driven generation of mixed X-anion perovskite properties6Band theoretical approaches to topological physics in strongly-correlated f-electron Kondo systems1Highly accurate machine learning prediction of crystal point groups for ternary materials from chemical formula19Robust Design of High-Performance Optoelectronic Chalcogenide Crystals from High-Throughput Computation60Fusing separated representation into an autoencoder for magnetic materials outlier detection2Unsupervised machine learning to classify crystal structures according to their structural distortion: A case study on Li-argyrodite solid-state electrolytes11Atomic‐Scale Design of Anode Materials for Alkali Metal (Li/Na/K)‐Ion Batteries: Progress and Perspectives149The physical significance of imaginary phonon modes in crystals176Applications of Artificial Intelligence and Machine Learning Algorithms to Crystallization160A Capacity-Prediction Model for Exploration of Organic Anodes: Discovery of 5-Formylsalicylic Acid as a High-Performance Anode Active Material14Investigation of the Pb–Fe–Se Ternary System and the Synthesis of a Ternary Pb1–xFexSe Phase3In silico study on probing atomistic insight into structural stability and tensile properties of Fe-doped hydroxyapatite single crystals0Synthesis, crystal structure, Hirshfeld surface, nonlinear optical properties and computational studies of Schiff based (E)-N'-(2,4-dimethoxybenzylidene) benzohydrazide single crystals for optoelectronic applications10Atomic structure generation from reconstructing structural fingerprints10In silico study on probing atomistic insights into structural stability and tensile properties of Fe-doped hydroxyapatite single crystals15Computational Studies on Na‐Ion Electrode Materials3High-Efficiency Inorganic Perovskite Solar Cell in a Wide Additive-Processing Window7Capacity-prediction models for organic anode-active materials of lithium-ion batteries: advances in predictors using small data10Mechanical properties and peculiarities of molecular crystals391DFT-D3 study of two-dimensional polymerization of C60 crystal under high pressure1The use of generative models to speed up the discovery of materials6Harvesting energy from extreme environmental conditions with cellulosic triboelectric materials93A state-of-the-art review on the utilization of machine learning in nanofluids, solar energy generation, and the prognosis of solar power44On the mechanical, electronic, and optical properties of the boron nitride analog for the recently synthesized biphenylene network: a DFT study20Prediction of Specific Surface Area of Metal-Organic Frameworks by Graph Kernels0Accurate and Efficient Spin–Phonon Coupling and Spin Dynamics Calculations for Molecular Solids38Learning Stability Scores from Computationally Generated Kinetic Data0Gradient boosted and statistical feature selection workflow for materials property predictions27Transverse effective charge, energy band structure and optical properties of nanostructured AlxIn1-xPySbzAs1-y-z alloy for the solar cells system2Towards the high-throughput prediction of finite-temperature properties using the quasi-harmonic approximation4Efficient design and synthesis of an amorphous conjugated polymer network for a metal-free electrocatalyst of hydrogen evolution reaction16Machine learning of stability scores from kinetic data5Machine-learning-assisted prediction of the size of microgels prepared by aqueous precipitation polymerization7Insights into the DHQ-BN: mechanical, electronic, and optical properties8Advances in materials informatics: a review42Accelerating materials discovery: combinatorial synthesis, high-throughput characterization, and computational advances77Prediction of specific surface area of metal–organic frameworks by graph kernels2Application of machine learning in perovskite materials and devices: A review75Predicting structural, elastic, and optoelectronic properties of oxide perovskites HfXO3 (X =Be, Mg) employing the DFT approach20Machine learning: An accelerator for the exploration and application of advanced metal-organic frameworks45Design Principles Guided by DFT Calculations and High-Throughput Frameworks for the Discovery of New Diamond-like Chalcogenide Thermoelectric Materials14DFT-PBE band gap correction using machine learning with a reduced set of features33Mesophase Behavior of Molecules Containing Three Benzene Rings Connected via Imines and Ester Linkages10Discovery of novel materials through machine learning24Lead-Free Double Perovskites Rb2TlSbX6 (X=Cl, Br, and I) As an Emerging Aspirant for Solar Cells and Green Energy Applications75Predicting Crystalline Material Properties with AI: Bridging Molecular to Particle Scales6Machine learning prediction of materials properties from chemical composition: Status and prospects29The amorphous state as a frontier in computational materials design74Data-scientific validation of prediction models for the controlled syntheses of exfoliated nanosheets1Establishing baselines for generative discovery of inorganic crystals10Intermolecular interaction of Al 8 O 12 oxymetallic clusters in the detection of atmospheric pollutants: a DFT exploration of CO, CO 2 , H 2 , N 2 , NO, NO 2 , O 2 , and SO 2 , binding mechanisms7Application of machine learning in polyimide structure design and property regulation5Atomic Scale Modeling via Molecular Dynamics and Machine Learning of Na2O-V2O5-TeO2 Glass-Based Cathodes0Forecasting phase stability, optoelectronic behavior, and transport mechanisms of double perovskites Cs2AuMX6 (M = As, Bi and X = Cl, Br) for applications in renewable energy technologies8Hybrid Nanofluid Thin-Film Dynamics of [PVA/MoS2+Cu]HNF: Synthesis, Characteristics and 3D Electromagnetic Flow Simulation via Variant Thickness Surface0Electronic Consequences of the Formation of Local Tilting in Halide Perovskites2Pathways to crystal chirality: An algorithm to identify displacive chiral phase transitions2Efficient and Accurate Machine Learning Interatomic Potential for Graphene: Capturing Stress–Strain and Vibrational Properties4Artificial Intelligence for Materials Discovery, Development, and Optimization170Accelerating the Discovery of Low-Dielectric Polyimides Based on Interpretable Machine Learning7From setup to analysis: A compact guide to performing Molecular Dynamics simulations of ion transport in solids6Recent progress of crystalline-amorphous heterointerface: design, mechanism and application14MatterGPT: A Generative Transformer for Multi-Property Inverse Design of Solid-State Materials6A data-driven approach to control stimulus responsivity of functional polymer materials: predicting thermoresponsive color-changing properties of polydiacetylene0Dense crystalline–amorphous heterointerface catalysts for freshwater/seawater splitting and small molecule synergistic electrolysis2Machine learning in next-generation AEM fuel cells: a systematic review7Emerging inorganic amorphous solid-state electrolytes in all-solid-state lithium batteries: From crystallographic order to atomic and lattice disorder4Computational design of materials for nuclear reactors2Excitonic, Optical, and Photovoltaic Properties of the 1T-NiO 2 Monolayer3Phonon thermal transport in ferroelectric and antiferroelectric bilayer SnSe0Improving crystal material property prediction with multi-view geometric graph transformer1Enhanced photocatalytic and antibacterial water treatment using phosphorus carbon/zirconia nanocomposite: experimental evaluation supported by DFT0High-efficiency simulation of spin-lattice relaxation in lanthanide single-molecule magnets0

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  1. Organised chaos: entropy in hybrid inorganic–organic systems and other materials

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  2. Computational Screening of All Stoichiometric Inorganic Materials

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  3. Chemical principles for electroactive metal–organic frameworks

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  4. ChemInform Abstract: Computational Materials Design of Crystalline Solids

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  5. Defect Engineering in Multinary Earth‐Abundant Chalcogenide Photovoltaic Materials

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  6. Electroactive Nanoporous Metal Oxides and Chalcogenides by Chemical Design

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  7. Perspective: Theory and simulation of hybrid halide perovskites

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  8. Perspective: Theory and simulation of hybrid halide perovskites

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  9. Developing a Descriptor-Based Approach for CO and NO Adsorption Strength to Transition Metal Sites in Zeolites

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  11. Selection Metric for Photovoltaic Materials Screening Based on Detailed-Balance Analysis

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  12. Diffusion in energy materials: Governing dynamics from atomistic modelling

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  14. Comparison of approximations in density functional theory calculations: Energetics and structure of binary oxides

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  20. The Optical Diode Ideality Factor Enables Fast Screening of Semiconductors for Solar Cells

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  45. Computational functionality‐driven design of semiconductors for optoelectronic applications

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