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RESEARCH PAPER · Journal of Materiomics · 2017

Data mining-aided materials discovery and optimization

Wencong Lu, Ruijuan Xiao, Jiong Yang, Hong Li, Wenqing Zhang

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Data mining-aided materials discovery and optimizationOriginalUntitled work0A review and analysis on knowledge discovery and data mining techniques9Applying machine learning to accelerate new materials development22First-principles study of pressure-induced phase transformations in thermoelectric Mg2Si9Committee machine that votes for similarity between materials5Important Descriptors and Descriptor Groups of Curie Temperatures of Rare-earth Transition-metal Binary Alloys34Energy Sustainability Through the Use of Thermoelectric Materials in Waste Heat Recovery Systems Recent Developments and Challenges4Using Data Mining To Search for Perovskite Materials with Higher Specific Surface Area44Empirical modeling of dopability in diamond-like semiconductors46Machine learning in materials design and discovery: Examples from the present and suggestions for the future198Nanoinformatics, and the big challenges for the science of small things92First-principles search for alloying elements that increase corrosion resistance of Mg with second-phase particles of transition metal impurities58Heat Transfer Coefficient Prediction of a Porous Material by Implementing a Machine Learning Model on a CFD Data Set5Database of novel magnetic materials for high-performance permanent magnet development62A property-oriented design strategy for high performance copper alloys via machine learning226QSPR Models for Predicting of the Melting Points and Refractive Indices for Inorganic Substances5Uranium-based materials for thermoelectric applications4Machine Learning Approaches for Thermoelectric Materials Research231Monitoreo de indicadores de valor a través de minería de datos, gestión de procesos de negocio y mejoramiento continuo con gestión del riesgo2Quantum Grover search-based optimization for innovative material discovery7Deep Multi-Layer Perceptron based Prediction of Energy Efficiency and Surface Quality for Milling in The Era of Sustainability and Big Data20Introduction1Machine learning-driven new material discovery296Machine-learning-assisted high-throughput computational screening of high performance metal–organic frameworks158Data-Based Methods for Materials Design and Discovery: Basic Ideas and General Methods10Magnetic and superconducting phase diagrams and transition temperatures predicted using text mining and machine learning98Composition design of 7XXX aluminum alloys optimizing stress corrosion cracking resistance using machine learning26Machine learning in materials genome initiative: A review231Machine Learning Algorithm Identifies an Antibiotic Vocabulary for Permeating Gram-Negative Bacteria33Evolutionary Learning for Soft Margin Problems: A Case Study on Practical Problems with Kernels1Advanced Thermoelectric Design: From Materials and Structures to Devices2524Machine learning assisted materials design and discovery for rechargeable batteries466A review of recent progress in thermoelectric materials through computational methods86Artificial intelligence for photonics and photonic materials63Computational materials design: recent advances and open challenges related to colorimetry2Artificial Intelligence Aided Design of Microtextured Surfaces: Application to Controlling Wettability23Deep Learning for Material recognition: most recent advances and open challenges4Twenty Years Survey of Big Data: Definition, Concepts, and Applications in Engineering1Center-Environment Feature Model for Machine Learning Study of Spinel Oxides Based on First-Principles Computations40Advanced Technologies in Health and Neurodegenerative Diseases1Computational design of structured chemical products3Machine Learning Aided Design of Polymer with Targeted Band Gap Based on DFT Computation57Machine learning for advanced energy materials208Machine learning for perovskite materials design and discovery536Extending Shannon's ionic radii database using machine learning81Computational discovery of energy materials in the era of big data and machine learning: A critical review60A Supervised Learning Neural Network Approach for the Prediction of Supercapacitive Energy Storage Materials5A physics-constrained deep learning based approach for acoustic inverse scattering problems28Physics-Based Feature Makes Machine Learning Cognizing Crystal Properties Simple4Artificial Intelligence Aided Design of Tissue Engineering Scaffolds Employing Virtual Tomography and 3D Convolutional Neural Networks107Artificial Intelligence Applied to Battery Research: Hype or Reality?503Machine learning and materials informatics approaches in the analysis of physical properties of carbon nanotubes: A review113Machine Learning Aided Discovery of the Layered Double Hydroxides with the Largest Basal Spacing for Super-Capacitors14A machine learning-based alloy design system to facilitate the rational design of high entropy alloys with enhanced hardness335Intelligent control of nanoparticle synthesis through machine learning83Intelligent Design of High Strength and High Conductivity Copper Alloys Using Machine Learning Assisted by Genetic Algorithm9Performance Prediction and Experimental Optimization Assisted by Machine Learning for Organic Photovoltaics30Discovery and prediction capabilities in metal-based nanomaterials: An overview of the application of machine learning techniques and some recent advances47Material machine learning for alloys: Applications, challenges and perspectives150Intelligent control of nanoparticle synthesis on microfluidic chips with machine learning102Critical Review of Factors Hindering Scalability of Complex Concentrated Alloys6Accelerated Discovery of Ternary Gold Alloy Materials with Low Resistivity via an Interpretable Machine Learning Strategy7Machine learning-driven design of promising perovskites for photovoltaic applications: A review18Machine learning search for stable binary Sn alloys with Na, Ca, Cu, Pd, and Ag10A critical review on machine-learning-assisted screening and design of effective sorbents for carbon dioxide (CO2) capture35Application of machine learning to reveal relationship between processing-structure-property for polypropylene injection molding38Designing All-Solid-State Batteries by Theoretical Computation: A Review122A Critical Review of Machine Learning Techniques on Thermoelectric Materials66Automatic Identification of the Multiphase Microstructures of Steels based on ASPP‐FCN4Full-scale simulation and experimental verification of the phase-transition temperature of a VO2 nanofilm as smart window materials6Outliers in Shannon’s effective ionic radii table and the table extension by machine learning34AI powered, automated discovery of polymer membranes for carbon capture48Unleashing the Power of Artificial Intelligence in Materials Design179Advancements in High‐Throughput Screening and Machine Learning Design for 2D Ferromagnetism: A Comprehensive Review10Data science and material informatics in physical metallurgy and material science: An overview of milestones and limitations32Machine Learning in Perovskite Solar Cells: Recent Developments and Future Perspectives76Scope of machine learning in materials research—A review230Drug delivery system tailoring via metal-organic framework property prediction using machine learning: A disregarded approach20Recent advances in metal-organic framework (MOF)-based agricultural sensors for metal ions: a review103Machine-learning guided prediction of thermoelectric properties of topological insulator Bi 2 Te 3− x Se x26The MatHub‐3d first‐principles repository and the applications on thermoelectrics37Advances in materials informatics: a review42A machine-learning-based composition design of ternary Cu-based Rochow-Müller catalyst with high M2 selectivity5Application of machine learning in perovskite materials and devices: A review75Exploring the Ambient-Temperature Degradation Reactions of PET through Two-Step Machine Learning and High-Throughput Experimentation11Advanced ceramics with integrated structures and functions: Machine learning prediction and experimental verification20Diffusion dominant thermal transport in mixed valent Ba4Sn4Se93A Study on Prediction of Size and Morphology of Ag Nanoparticles Using Machine Learning Models for Biomedical Applications24Review on Some Important Research Progresses in Biodegradable Plastics/Polymers15Review of the opportunities and limitations for powder-based high-throughput solid-state processing of advanced functional ceramics36Machine-Learning-Assisted Design of Novel TiZrNbVAl Refractory High-Entropy Alloys with Enhanced Ductility8Fostering creativity in engineering design through constructive dialogues with generative artificial intelligence10High-Performance stacking ensemble learning for thermoelectric figure-of-merit prediction20Introduction to Machine Learning for Predictive Modeling II1Optimizing the Design of Metal Organic Frameworks for Drug Delivery Applications Through Machine Learning Integration0Research on multi-source microstructure image recognition of foam ceramics using convolutional network combine with frequency domain5Machine Learning Descriptors for CO2 Capture Materials21Frontiers in machine learning strategies for dye removal in water treatment20Machine learning-driven optimization of wear-resistant high-manganese steel properties: achieving multi-property matching under specified composition2Identifying Key Factors Influencing Advanced Hydrogen Evolution Reaction Catalysts5What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials2Composition Design and Property Prediction for AlCoCrCuFeNi High-Entropy Alloy Based on Machine Learning4Data-driven property-oriented composition design and feature analysis of lightweight high-entropy alloys8A review of machine learning approaches for the discovery of thermoelectric materials3PINN-DTC: Adaptive partitioning of physics-informed neural network for designing thermal cloak6Predicting the dielectric properties of dielectric films in chip by machine learning methods0Accelerated Discovery of Refractory High-Entropy Alloys via Interpretable Machine Learning8Classification of magnetic ground States and prediction of magnetic moments for ABX3 perovskites utilizing machine learning techniques1Review: Recent progress in titanium alloys development via machine learning and high-throughput preparation4Data-driven high-throughput search for the accelerated discovery of rare-earth-free permanent magnets1Recent advances in chalcogenides for mid-temperature thermoelectric materials4Review: machine learning-driven design and discovery of halide perovskite materials1Artificial intelligence in the development of structural and functional materials: A transformative frontier and complementary enabler of the rational alloy design framework10Machine Learning for Stability Enhancement in Perovskite Solar Cells: A Pathway to Commercial Viability0Beyond predicted zT: Machine learning strategies for the experimental discovery of thermoelectric materials4Machine Learning for Designing Perovskites and Perovskite‐Inspired Solar Materials: Emerging Opportunities and Challenges7Comparative assessment of dilute alloys and complex concentrated alloys: Design principles, processing, mechanisms, properties, and sustainability0Machine Learning Assisted Inverse Design of Low Resistivity In–Ga–Sn–Zn Oxide Sputtering Targets0Optuna-driven interpretable model for refractory multi-principal element alloys yield strength prediction with small dataset0

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  2. A review and analysis on knowledge discovery and data mining techniques

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  3. Applying machine learning to accelerate new materials development

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  4. First-principles study of pressure-induced phase transformations in thermoelectric Mg2Si

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  5. Committee machine that votes for similarity between materials

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  6. Important Descriptors and Descriptor Groups of Curie Temperatures of Rare-earth Transition-metal Binary Alloys

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  7. Energy Sustainability Through the Use of Thermoelectric Materials in Waste Heat Recovery Systems Recent Developments and Challenges

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  8. Using Data Mining To Search for Perovskite Materials with Higher Specific Surface Area

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  9. Empirical modeling of dopability in diamond-like semiconductors

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  11. Nanoinformatics, and the big challenges for the science of small things

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  13. Heat Transfer Coefficient Prediction of a Porous Material by Implementing a Machine Learning Model on a CFD Data Set

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  20. Quantum Grover search-based optimization for innovative material discovery

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