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RESEARCH PAPER · Advanced Intelligent Systems · 2020

Artificial Intelligence to Power the Future of Materials Science and Engineering

Wuxin Sha, Yaqing Guo, Qing Min Yuan, Shun Tang, Xinfang Zhang, Songfeng Lu, Xin Guo, Yuan‐Cheng Cao, Shijie Cheng

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A review of applications to equine biomechanical research48Machine Learning: An Advanced Platform for Materials Development and State Prediction in Lithium‐Ion Batteries412Convergence of Liquid Metal Biotechnologies for Our Health20Machine-learned, waterproof MXene fiber-based glove platform for underwater interactivities63Influence of erbium doping on zinc oxide nanoparticles: Structural, optical and antimicrobial activity34Ensemble-based machine learning models for phase prediction in high entropy alloys49Practical Aspects of the Design and Use of the Artificial Neural Networks in Materials Engineering24Sustainable and efficient technologies for removal and recovery of toxic and valuable metals from wastewater: Recent progress, challenges, and future perspectives192Integrated Intelligent CAD System for Interactive Design, Analysis and Prototyping of Compression and Torsion Springs3Compositionally graded crystals as a revived approach for new crystal engineering for the exploration of novel functionalities8How Artificial Intelligence and Machine Learning Is Assisting Us to Extract Meaning from Data on Bone Mechanics?15Prospects and challenges for autonomous catalyst discovery viewed from an experimental perspective46Recent trends in computational tools and data-driven modeling for advanced materials85Supported Metal Single‐Atom Photocatalysis0Materials structure–property factorization for identification of synergistic phase interactions in complex solar fuels photoanodes7Lossless multi-scale constitutive elastic relations with artificial intelligence52Metal Nanoparticles–Polymers Hybrid Materials II5Catalytic oxidation of volatile organic compounds over manganese-based oxide catalysts: Performance, deactivation and future opportunities77Graph neural networks predict energetic and mechanical properties for models of solid solution metal alloy phases22A Learning Assisted Approach for Electronic and Optical Characterization of Tin-Doped Titanium Oxide2Prediction of operating dynamics in floating-zone crystal growth using Gaussian mixture model1Effect of microstructural heterogeneity on fatigue strength predicted by reinforcement machine learning22A BERT-based model for coupled biological strategies in biomimetic design9Machine-learning model for prediction of martensitic transformation temperature in NiMnSn-based ferromagnetic shape memory alloys37Artificial neural network-based model to predict the effect of γ-aminobutyric acid on salinity and drought responsive morphological traits in pomegranate24Predictive Molecular Models for Charged Materials Systems: From Energy Materials to Biomacromolecules13Smart data processing for energy harvesting systems using artificial intelligence109Six decades of soybean breeding in Ontario, Canada: a tradition of innovation13Emerging interaction of artificial intelligence with basic materials and oil & gas companies: A comparative look at the Islamic vs. conventional markets28Ensemble hybrid machine learning to 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Enhancing Virtual-Hand Selection with Target Prediction in AR/VR1

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