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RESEARCH PAPER · Journal of Intelligent Manufacturing · 2018

Materials informatics

Seeram Ramakrishna, Tong‐Yi Zhang, Wencong Lu, Quan Qian, Jonathan Sze Choong Low, Jeremy H. Yune, Daren Zong Loong Tan, Stéphane Bressan, Stefano Sanvito, Surya R. Kalidindi

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Materials informaticsOriginalModern Data Analytics Approach to Predict Creep of High-Temperature Alloys112Recent developments of artificial intelligence in drying of fresh food: A review236Multifidelity Information Fusion with Machine Learning: A Case Study of Dopant Formation Energies in Hafnia78On-the-Fly Adaptivity for Nonlinear Twoscale Simulations Using Artificial Neural Networks and Reduced Order Modeling62Heat Transfer Coefficient Prediction of a Porous Material by Implementing a Machine Learning Model on a CFD Data Set5Completing the picture through correlative characterization128Applying Neural-Network-Based Machine Learning to Additive Manufacturing: Current Applications, Challenges, and Future Perspectives525Embedding domain knowledge for machine learning of complex material systems71Accelerated Search for BaTiO3‐Based Ceramics with Large Energy Storage at Low Fields Using Machine Learning and Experimental Design100Zero waste manufacturing: A framework and review of technology, research, and implementation barriers for enabling a circular economy transition in Singapore226Design and Evaluation of Conceptual Ontologies for Electrochemistry as a Domain30Machine Learning at the Atomic Scale6Additive Manufacturing from the Point of View of Materials Research5Machine Learning and Big Data Provide Crucial Insight for Future Biomaterials Discovery and Research104Machine learning in materials modeling—fundamentals and the opportunities in 2D materials22Technical, Economic and Societal Effects of Manufacturing 4.050Machine learning: Accelerating materials development for energy storage and conversion370Plastic recycling in additive manufacturing: A systematic literature review and opportunities for the circular economy410Learning to Predict Crystal Plasticity at the Nanoscale: Deep Residual Networks and Size Effects in Uniaxial Compression Discrete Dislocation Simulations34Machine Learning for Materials Scientists: An Introductory Guide toward Best Practices509Machine-Learning Assisted Screening of Energetic Materials71Machine learning assisted multi-objective optimization for materials processing parameters: A case study in Mg alloy119Feature engineering of material structure for AI-based materials knowledge systems70Mobilising information systems scholarship for a circular economy: Review, synthesis, and directions for future research107Artificial Intelligence-Driven Circular Economy as a Key Enabler for Sustainable Energy Management98Coupling physics in machine learning to predict properties of high-temperatures alloys95Analytic formulas of peak current in cyclic voltammogram: Machine learning as an alternative way?14Tribo-informatics: Concept, architecture, and case study82Uncertainty Quantification of Machine Learning Predicted Creep Property of Alumina-Forming Austenitic Alloys13Modeling process–structure–property relationships in metal additive manufacturing: a review on physics-driven versus data-driven approaches152Artificial intelligence and machine learning in design of mechanical materials690Machine learning-guided design and development of metallic structural materials27Modelling of phase stability: integrating computational materials science and materials informatics3Nonferrous waste aerated concrete1Off-the-shelf deep learning is not enough, and requires parsimony, Bayesianity, and causality56Optimization of the composition in a composite material for microelectronics application using the Ising model16The capabilities of nanoelectronic 2-D materials for bio-inspired computing and drug delivery indicate their significance in modern drug design18Kreislaufführung von Werkstoffen, Komponenten und Produkten: eine ökonomische Herausforderung3Efficient sampling for decision making in materials discovery*10Materials graph ontology23Accelerated Discovery of the Polymer Matrix for Cartilage Repair Through Machine Learning Algorithms0Machine-learning semilocal density functional theory for many-body lattice models at zero and finite temperature1Data analytics approach to predict high-temperature cyclic oxidation kinetics of NiCr-based Alloys21Materials Informatics for Mechanical Deformation: A Review of Applications and Challenges67Machine learning and materials informatics approaches in the analysis of physical properties of carbon nanotubes: A review113Data-driven technologies and artificial intelligence in circular economy and waste management systems: a review17High‐Throughput Experimentation and Computational Freeway Lanes for Accelerated Battery Electrolyte and Interface Development Research140Statistical learning of small data with domain knowledge --- sample size- and pre-notch length- dependent strength of concrete16Recent Progress and Future Prospects on All-Organic Polymer Dielectrics for Energy Storage Capacitors744Acceleration of Density Functional Theory by Optimizing Self-Consistent Field Calculation Conditions0Biomimicry for natural and synthetic composites and use of machine learning in hierarchical design2Domain knowledge-guided interpretive machine learning: formula discovery for the oxidation behavior of ferritic-martensitic steels in supercritical water46Estimating the performance of a material in its service space via Bayesian active learning: a case study of the damping capacity of Mg alloys14In Situ Experiments: Paving Ways for Rapid Development of Structural Metallic Materials for a Sustainable Future2Recent progress in the data-driven discovery of novel photovoltaic materials44Two-dimensional material-based functional aerogels for treating hazards in the environment: synthesis, functional tailoring, applications, and sustainability analysis64The materials tetrahedron has a “digital twin”34A brief review on mechanical designs for 4D printing4Predicting Material Properties Using Machine Learning for Accelerated Materials Discovery0ML Model Optimization–Selection and GFA Prediction for Binary Alloys5Perspective: Predicting and optimizing thermal transport properties with machine learning methods54Split waste from rattan industry? Crafted product and furniture industry fiber bar5A Perspective on Digital Knowledge Representation in Materials Science and Engineering40Accelerated Discovery of the Polymer Blends for Cartilage Repair through Data-Mining Tools and Machine-Learning Algorithm18Machine learning of fake micrographs for automated analysis of crystal growth process5Processing time, temperature, and initial chemical composition prediction from materials microstructure by deep network for multiple inputs and fused data17Autonomous materials discovery and manufacturing (AMDM): A review and perspectives18Resampling Techniques for Materials Informatics: Limitations in Crystal Point Groups Classification11Designing bulk metallic glasses materials with higher reduced glass transition temperature via machine learning9Training data selection for accuracy and transferability of interatomic potentials56Statistical genetics concepts in biomass-based materials engineering0A structure metric for quantitative assessment of fracture surfaces in 3D conceived based on confocal laser scanning microscopy data14Ensemble Machine Learning approach for evaluating the material characterization of carbon nanotube-reinforced cementitious composites84Computational design of magnetic molecules and their environment using quantum chemistry, machine learning and multiscale simulations88Electrochemoinformatics as an Emerging Scientific Field for Designing Materials and Electrochemical Energy Storage and Conversion Devices—An Application in Battery Science and Technology24Intelligent Computing: The Latest Advances, Challenges and Future19A domain knowledge enhanced machine learning method to predict the properties of halide double perovskite A 2 B + B 3+ X 615Alloy Informatics Through Ab Initio Charge Density Profiles: Case Study of Hydrogen Effects in Face-Centered Cubic Crystals0Intelligent Computing: The Latest Advances, Challenges, and Future290Metal AM process-structure-property relational linkages using Gaussian process surrogates42Predicting the Loading Parameters of a Square Panel Upon Linear Deflection0Speeding up high-throughput characterization of materials libraries by active learning: autonomous electrical resistance measurements10The Basin Network : A Model for Data Sharing and Exchange0The Problem of Epistemic Debt in Iterative Materials AI Pipelines0Voxelized Representations of Atomic Systems for Machine Learning Applications2Gaussian process autoregression models for the evolution of polycrystalline microstructures subjected to arbitrary stretching tensors12Discovering a formula for the high temperature oxidation behavior of FeCrAlCoNi based high entropy alloys by domain knowledge-guided machine learning41Recent Progresses in Machine Learning Assisted Raman Spectroscopy250Application of back propagation neural networks and random forest algorithms in material research of hydrogels16Neural network modeling of titanium alloy composition-microstructure-property relationships based on multimodal data23Data-driven machine learning for alloy research: Recent applications and prospects21Voxelized atomic structure framework for materials design and discovery7Application of Machine Learning in Material Synthesis and Property Prediction166Effects of micron–nano composite iron particle powders on the tribological properties of magnetic fluids used for a nonlinear energy sink vibration absorber9Predicting the anion conductivities and alkaline stabilities of anion conducting membrane polymeric materials: development of explainable machine learning models15Superior Prediction of Graphene Nanoflake Properties withUnbiased Graph Embedding2Prediction of glass-forming ability based on multi-model fusion7Review of Material Modeling and Digitalization in Industry: Barriers and Perspectives7Conceptual Treatments of Causality in Materials Informatics — From Correlation to Intervention: A Review Study0Substitutional alloying using crystal graph neural networks3Systems-chart approach to the design of spin relaxation times in molecular qubits5Unsupervised learning and pattern recognition in alloy design15Data-Driven Study on Thermal Shock Resistance Prediction of Copper Alloys0Advances in materials informatics: a review42Application of machine learning‐based read‐across structure‐property relationship (RASPR) as a new tool for predictive modelling: Prediction of power conversion efficiency (PCE) for selected classes of organic dyes in dye‐sensitized solar cells (DSSCs)19Alloy informatics through ab initio charge density profiles: Case study of hydrogen effects in face-centred cubic crystals7Physics mechanisms underlying the optimization of coherent heat transfer across width-modulated nanowaveguides with calculations and machine learning2AI for tribology: Present and future85Graph Similarity-Based Data Management Platform for Advancing Material Informatics0INNOVATIVE MATERIAL PROCESSING TECHNIQUES IN PRECISION MANUFACTURING: A REVIEW37Prediction and Elucidation of Physical Properties of Polycrystalline Materials Using Multichannel Machine Learning of Electron Backscattering Diffraction3Multiscale modeling for enhanced battery health analysis: Pathways to longevity45Machine learning in solid state additive manufacturing: state-of-the-art and future perspectives7Opportunities and challenges of capacitive deionization for uranium extraction from seawater23Unsupervised learning-aided extrapolation for accelerated design of superalloys21Prediction of long-term creep modulus of thermoplastics using brief tests and interpretable machine learning5Digital Technology in Upcycling Craft Industry: A Systematic Review3Semantic segmentation in crystal growth process using fake micrograph machine learning3Machine learning enabled assessment of the vacuum freeze-drying of the kiwifruit12Predicting refractive index of inorganic compounds using machine learning2Graph neural network guided design of novel deep-ultraviolet optical materials with high birefringence23Machine learning prediction of materials properties from chemical composition: Status and prospects29A Conceptual Design of Industrial Asset Maintenance System by Autonomous Agents Enhanced with ChatGPT1Advancements in Agricultural Materials: Machine Learning Models for Precision Fertilizer Prediction4Impact of artificial intelligence for the recycling of organic waste2Introduction0Introduction to Machine Learning for Predictive Modeling II1Machine Learning Tools and Web Services for Materials Science Modeling1New Intelligent Computing Techniques for Engineering Materials—A Comprehensive Review0Similar Experimental Flow Search with Operation Grouping for Chemical Material Development0基于深度神经网络的危险化学品拉曼光谱识别3Green development of molecularly imprinted polymers and the application in CO2 adsorption and separation: A review16Artificial intelligence artificial muscle of dielectric elastomers20Reconfigurable asymmetrical broadband mid-infrared light filter design by materials informatics1Natural Fiber Composites: A Comprehensive Review on Machine Learning Methods29Materials Engineering and Artificial Intelligence Innovations: A Comprehensive Review3Identifying MOFs for electrochemical energy storage via density functional theory and machine learning51A computer vision-based model for predicting the glass-forming ability of alloys without feature engineering2AI‐Powered Visualization of Invisible Mechano‐Information: Stress, Defects, and Beyond2The Prediction of Tensile Strength Performance of Fiber‐Reinforced Composites Based on a Knowledge Graph Constructed From Material Literature4Hypershape Recognition: A General Framework for Moment-Based Molecular Similarity2DiMAT Materials Modeler (DiMM): An Interactive Framework for Materials Property Prediction and Optimization Using a Hybrid Machine Learning - Genetic Algorithm Approach1A comprehensive Ai-driven framework for predictive design of grained materials: Case study on nanoglass4Transfer learning of high-dimensional features via attention-based embedding for Ni-based superalloys4Materials informatics: A review of AI and machine learning tools, platforms, data repositories, and applications to architectured porous materials41A review of forming behavior and influencing mechanisms in laser-welded advanced high-strength steels9A Comprehensive Study on Fatigue Strength Prediction of a Broad Range of Steels Using Machine Learning2Smart design of thermoplastic vulcanizate products: Linking process to performance via interpretable machine learning1Bayesian probabilistic machine learning analysis of ceramic‐coated ultra‐high‐temperature carbon/carbon composites0AI-Driven Sustainable Product Design: Balancing Innovation and Environmental Impact0

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  1. Modern Data Analytics Approach to Predict Creep of High-Temperature Alloys

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  2. Recent developments of artificial intelligence in drying of fresh food: A review

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  3. Multifidelity Information Fusion with Machine Learning: A Case Study of Dopant Formation Energies in Hafnia

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  4. On-the-Fly Adaptivity for Nonlinear Twoscale Simulations Using Artificial Neural Networks and Reduced Order Modeling

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

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  6. Completing the picture through correlative characterization

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  7. Applying Neural-Network-Based Machine Learning to Additive Manufacturing: Current Applications, Challenges, and Future Perspectives

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  8. Embedding domain knowledge for machine learning of complex material systems

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  9. Accelerated Search for BaTiO3‐Based Ceramics with Large Energy Storage at Low Fields Using Machine Learning and Experimental Design

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  10. Zero waste manufacturing: A framework and review of technology, research, and implementation barriers for enabling a circular economy transition in Singapore

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  11. Design and Evaluation of Conceptual Ontologies for Electrochemistry as a Domain

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  12. Machine Learning at the Atomic Scale

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  13. Additive Manufacturing from the Point of View of Materials Research

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  14. Machine Learning and Big Data Provide Crucial Insight for Future Biomaterials Discovery and Research

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  15. Machine learning in materials modeling—fundamentals and the opportunities in 2D materials

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  16. Technical, Economic and Societal Effects of Manufacturing 4.0

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  17. Machine learning: Accelerating materials development for energy storage and conversion

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  18. Plastic recycling in additive manufacturing: A systematic literature review and opportunities for the circular economy

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  19. Learning to Predict Crystal Plasticity at the Nanoscale: Deep Residual Networks and Size Effects in Uniaxial Compression Discrete Dislocation Simulations

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  20. Machine Learning for Materials Scientists: An Introductory Guide toward Best Practices

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  21. Machine-Learning Assisted Screening of Energetic Materials

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  23. Feature engineering of material structure for AI-based materials knowledge systems

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  24. Mobilising information systems scholarship for a circular economy: Review, synthesis, and directions for future research

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  28. Tribo-informatics: Concept, architecture, and case study

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  30. Modeling process–structure–property relationships in metal additive manufacturing: a review on physics-driven versus data-driven approaches

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  38. Kreislaufführung von Werkstoffen, Komponenten und Produkten: eine ökonomische Herausforderung

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  39. Efficient sampling for decision making in materials discovery*

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  40. Materials graph ontology

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  41. Accelerated Discovery of the Polymer Matrix for Cartilage Repair Through Machine Learning Algorithms

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  42. Machine-learning semilocal density functional theory for many-body lattice models at zero and finite temperature

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  43. Data analytics approach to predict high-temperature cyclic oxidation kinetics of NiCr-based Alloys

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  44. Materials Informatics for Mechanical Deformation: A Review of Applications and Challenges

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  45. Machine learning and materials informatics approaches in the analysis of physical properties of carbon nanotubes: A review

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  46. Data-driven technologies and artificial intelligence in circular economy and waste management systems: a review

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  47. High‐Throughput Experimentation and Computational Freeway Lanes for Accelerated Battery Electrolyte and Interface Development Research

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  48. Statistical learning of small data with domain knowledge --- sample size- and pre-notch length- dependent strength of concrete

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  49. Recent Progress and Future Prospects on All-Organic Polymer Dielectrics for Energy Storage Capacitors

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  50. Acceleration of Density Functional Theory by Optimizing Self-Consistent Field Calculation Conditions

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