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RESEARCH PAPER · Applied Materials Today · 2018

Materials 4.0: Materials big data enabled materials discovery

Rajan Jose, Seeram Ramakrishna

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Materials 4.0: Materials big data enabled materials discoveryOriginalPatent Tigers: The New Geography of Global Innovation18Materials informatics167Smart grid communication and information technologies in the perspective of Industry 4.0: Opportunities and challenges392Analysis of Self Concept and Graduation Capability in the Era of Industrial Revolution 4.0 to Increase Absorption of Vocational Student Graduates1Analysis of the Necessity for Heutagogical Approach Through 4Cs Skills as Innovation for Vocational Lectures in the Education 4.07Critical insight: challenges and requirements of fibre electrodes for wearable electrochemical energy storage132Estimating Regions of Deterioration in Electron Microscope Images of Rubber Materials via a Transfer Learning-Based Anomaly Detection Model8Nanomaterials Discovery and Design through Machine Learning113Why Are Carbon-Based Materials Important in Civilization Progress and Especially in the Industry 4.0 Stage of the Industrial Revolution32Gas separation by adsorption: technological drivers and opportunities for improvement123Applications of Laser Processing of Materials in Surface Engineering in the Industry 4.0 Stage of the Industrial Revolution28Sustainable engineering challenges towards Industry 4.0: A comprehensive review20A perspective on inverse design of battery interphases using multi-scale modelling, experiments and generative deep learning120A review of emerging industry 4.0 technologies in remanufacturing372Zero waste manufacturing: A framework and review of technology, research, and implementation barriers for enabling a circular economy transition in Singapore226Assessing relations between Circular Economy and Industry 4.0: a systematic literature review732Quantum Grover search-based optimization for innovative material discovery7Industry 4.0, digitization, and opportunities for sustainability2110Additive Manufacturing from the Point of View of Materials Research5Approach to the Design and Manufacturing of Prosthetic Dental Restorations According to the Rules of Industry 4.021Big-data driven approaches in materials science: A survey20Discovery and design of soft polymeric bio-inspired materials with multiscale simulations and artificial intelligence83Machine learning in materials modeling—fundamentals and the opportunities in 2D materials22Machine-learning-assisted search for functional materials over extended chemical space25Materials Design, Development, and Deployment in Manufacturing Industry2Single-step calibration method for nano indentation testing machines22Smart polymeric materials applied to industry 4.0: A review on electrochromic textiles2Technical, Economic and Societal Effects of Manufacturing 4.050The proposal of an agile model for the digital transformation of the University Hassan II of Casablanca 4.038Texture, 2D diffraction and piezoelectricity4Data Assessment Method to Support the Development of Creep-Resistant Alloys11Abnormal Detection and Classification in i-Ceramic Images6Artificial Intelligence to Power the Future of Materials Science and Engineering153A brief review of data-driven ICME for intelligently discovering advanced structural metal materials: Insight into atomic and electronic building blocks36Exploring the landscape between synthetic and biosynthetic materials discovery: important considerations via systems connectivity, cooperation and scale-driven convergence in biomanufacturing9Machine-learning structural and electronic properties of metal halide perovskites using a hierarchical convolutional neural network164Dentistry 4.0 Concept in the Design and Manufacturing of Prosthetic Dental Restorations88Smart remanufacturing: a review and research framework158Machine learning in materials genome initiative: A review231DID Code: A Bridge Connecting the Materials Genome Engineering Database with Inheritable Integrated Intelligent Manufacturing11Application Solid Laser-Sintered or Machined Ti6Al4V Alloy in Manufacturing of Dental Implants and Dental Prosthetic Restorations According to Dentistry 4.0 Concept28Enhanced Hyperbox Classifier Model for Nanomaterial Discovery10A new data-driven topology optimization framework for structural optimization54Advanced Aluminium Composites and Alloys8Preliminary investigation of Industry 4.0 readiness among small and medium aviation companies in Malaysia4Thin Chemisorbed Polyaniline Film on Cobalt Oxide as an Electrode for Hybrid Energy Storage Devices27Predictions and mechanism analyses of the fatigue strength of steel based on machine learning85Development Status and Prospects of Artificial Intelligence in the Field of Energy Conversion Materials14Mobilising information systems scholarship for a circular economy: Review, synthesis, and directions for future research107Recent Development in Micromanufacturing of Metallic Materials10Artificial Intelligence-Driven Circular Economy as a Key Enabler for Sustainable Energy Management98Benchmarking materials property prediction methods: the Matbench test set and Automatminer reference algorithm386Industry 4.0 Disruption and Its Neologisms in Major Industrial Sectors: A State of the Art169Artificial Intelligence Aided Design of Microtextured Surfaces: Application to Controlling Wettability23Advanced intermetallic iron aluminide coatings for high temperature applications138Benchmarking materials property prediction methods: the Matbench test set and Automatminer reference algorithm246The Concept of Sustainable Development of Modern Dentistry41The Role of Digital Technologies in Business Model Transition Toward Circular Economy in the Building Industry4Inference on errors in industrial parts: Kriging and variogram versus geometrical product specifications standard11Predicting stable crystalline compounds using chemical similarity113Significant Applications of Big Data in Industry 4.091A contemporary approach to the MSE paradigm powered by Artificial Intelligence from a review focused on Polymer Matrix Composites28Machine learning autonomous identification of magnetic alloys beyond the Slater-Pauling limit54Design Engineering in the Age of Industry 4.0125Correlation analysis of materials properties by machine learning: illustrated with stacking fault energy from first-principles calculations in dilute fcc-based alloys33Effect of Biomedical Materials in the Implementation of a Long and Healthy Life Policy50Virtual Approach to the Comparative Analysis of Biomaterials Used in Endodontic Treatment14The Importance of Synthesis and Characterization of Biomedical Materials for the Current State of Medicine and Dentistry9An infrastructure with user-centered presentation data model for integrated management of materials data and services39Digitalization to achieve sustainable development goals: Steps towards a Smart Green Planet914Circular Economy and Sustainability of the Clothing and Textile Industry342A Supervised Learning Neural Network Approach for the Prediction of Supercapacitive Energy Storage Materials5Data‐Driven Approaches Toward Smarter Additive Manufacturing37Comparison of document similarity algorithms in extracting document keywords from an academic paper10Machine learning workflow for microparticle composite thin-film process–structure linkages4Is Gutta-Percha Still the “Gold Standard” among Filling Materials in Endodontic Treatment?20Gaussian process regression‐based detection and correction of disturbances in surface topography measurements22Generation of Computational Data Sets for Machine Learning Applied to Battery Materials0Machine Learning: An Advanced Platform for Materials Development and State Prediction in Lithium‐Ion Batteries411A Perspective on the Commercial Viability of Perovskite Solar Cells48Microstructure–property relation and machine learning prediction of hole expansion capacity of high-strength steels17Artificial Intelligence Aided Design of Tissue Engineering Scaffolds Employing Virtual Tomography and 3D Convolutional Neural Networks106Advanced Composites with Aluminum Alloys Matrix and Their Fabrication Processes3Development of physical property prediction models for polypropylene composites with optimizing random forest hyperparameters53What Are the Chances of Resilon to Dominate the Market Filling Materials for Endodontics?5Development Strategy of Endodontic Filling Materials Based on Engineering and Medical Approaches3Production and maintenance in industries: impact of industry 4.048Big data-assisted digital twins for the smart design and manufacturing of advanced materials: from atoms to products29Functional Nanomaterials Design in the Workflow of Building Machine-Learning Models1Guidance for Materials 4.0 to interact with a digital twin15Optimizing the Catalytic Activity of Pd-Based Multinary Alloys toward Oxygen Reduction Reaction32Sentence Boundary Extraction from Scientific Literature of Electric Double Layer Capacitor Domain: Tools and Techniques16Magnetic performance oriented composition design of Sm-Co based alloys by machine learning and experimental studies22A Supervised Neural Network-based predictive model for petrochemical wastewater treatment dataset5Emergence of local scaling relations in adsorption energies on high-entropy alloys57Integrating circular economy and Industry 4.0 for sustainable supply chain management: a dynamic capability view234Artificial Intelligence‐Based Material Discovery for Clean Energy Future46Application of Machine Learning Algorithms With and Without Principal Component Analysis for the Design of New Multiphase High Entropy Alloys11Predicting the maximum absorption wavelength of azo dyes using an interpretable machine learning strategy51Designing multinary noble metal‐free catalyst for hydrogen evolution reaction27High-throughput data mined prediction of design and preparation of flexible carbon-based conductive materials in energy storage4Nano-vascularized polymers: how nanochannels impact the mechanical behaviour at the macroscale2Materials processing model-driven discovery framework for porous materials using machine learning and genetic algorithm: A focus on optimization of permeability and filtration efficiency46Optimizing diamond-like carbon coatings - From experimental era to artificial intelligence38Advancing MXene Electrocatalysts for Energy Conversion Reactions: Surface, Stoichiometry, and Stability119Advancing MXene Electrocatalysts for Energy Conversion Reactions: Surface, Stoichiometry, and Stability0Accurate property prediction with interpretable machine learning model for small datasets via transformed atom vector17Advances in artificial intelligence applications in corroded reinforced concrete structures0Ceramic-polyaniline composites for asymmetric supercapacitors1Material Named Entity Recognition (MNER) for Knowledge-Driven Materials Using Deep Learning Approach3Synergizing ontologies and graph databases for highly flexible materials-to-device workflow representations7On Uncertainty Quantification in Materials Modeling and Discovery: Applications of GE's BHM and IDACE7Analysis and evaluation of machine learning applications in materials design and discovery33Phase prediction and experimental realisation of a new high entropy alloy using machine learning84Principles of Machine Learning and Its Application to Thermal Barrier Coatings23FAIR Additive Manufacturing Data Management Principles1Determining Homogenization Parameters and Predicting 5182-Sc-Zr Alloy Properties by Artificial Neural Networks4A detailed study of convolutional neural networks for the identification of microstructure13FFMDFPA: A FAIRification Framework for Materials Data with No-Code Flexible Semi-Structured Parser and Application Programming Interfaces5An automated materials and processes identification tool for material informatics using deep learning approach12MICROSIM® AND PHASTRANSIM® SIMULATIONS: METALLURGICAL PROPERTIES VARIABILITY (σ) REDUCTION FOR SAE1045 WIRE-RODS0Computational materials discovery and development for Li and non-Li advanced battery chemistries8Accelerated Discovery, Development, Manufacturing, and Deployment of New Materials Using Integrated Computational Materials Engineering (ICME) Tools and Digital Platforms0Exploiting 3-D Printing for Designing Circular Business Models: A Novel Framework23Core Competences and Core Resources as Catalysts for the Design of Circular Business Models1Lean manufacturing practices and industry 4.0 technologies in food manufacturing companies: the Greek case20A Holistic Treatise on Artificial Intelligence (AI) and Machine Learning (ML) Tools for Green Supercapacitors5Artificial Intelligence in Nanomaterials and Polymers: A Detailed Review Approach on Nano-informatics, Polymer Informatics, and Informational Materials Science0An Interpretable Machine Learning Frame to Facilitate Rational Design of Mg-Based Amorphous Alloys0Industry 4.0 and food sustainability: role of automation, digitalization, and green technologies3Material informatics for functional magnetic material discovery7Polymer and Nanocomposite Informatics: Recent Applications of Artificial Intelligence and Data Repositories8Examining interdependencies among solution dimensions for sustainable development in SMEs based on Industry 4.0 concept6Advances in materials informatics: a review42Wide‐Gap Perovskites for Indoor Photovoltaics23Mechanics 4.0 and Mechanical Engineering Education12Crystal structure map for materials classification and modeling1Exploring the Core-shell Structure of BaTiO3-based Dielectric Ceramics Using Machine Learning Models and Interpretability Analysis3The importance of precise and suitable descriptors in data‐driven approach to boost development of lithium batteries: A perspective12A perspective on additives for flexible packaging12Visual analytics of an interpretable prediction model for the glass transition temperature of fluoroelastomers4NJmat: Data-Driven Machine Learning Interface to Accelerate Material Design12Fostering creativity in engineering design through constructive dialogues with generative artificial intelligence10Machine Learning Approaches for Designing Electrode Materials for Lithium‐Ion Batteries2Accelerated discovery of Magnesium-based amorphous alloys through a property-driven active learning strategy4A review of computational approaches used in the modelling, design, and manufacturing of biodegradable and biobased polymers57Machine Learning as a “Catalyst” for Advancements in Carbon Nanotube Research36Machine learning-enhanced band gaps prediction for low-symmetry double and layered perovskites39Theoretical and machine learning models for reaction-barrier predictions: acrylate and methacrylate radical reactions5Introduction to Materials Informatics1

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