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RESEARCH PAPER · Frontiers of Physics · 2023

Advances of machine learning in materials science: Ideas and techniques

Sue Sin Chong, Yi Sheng Ng, Hui‐Qiong Wang, Jin‐Cheng Zheng

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Advances of machine learning in materials science: Ideas and techniquesOriginalInterfacial electronic state between hexagonal ZnO and cubic NiO2Local symmetry-driven interfacial magnetization and electronic states in (ZnO) n /(w-FeO) n superlattices2Prediction of the Tribological Properties of Graphite-Filled Ptfe Composites Based on Machine Learning Algorithms0The “Applicability Domain” Problem in Materials AI: A Theoretical Treatment of When Models Should Stay Silent0Universal scales of electronegativity and ionicity from electron scattering factors12Unsupervised learning and pattern recognition in alloy design15Analysing the Roles of Robotics in Manufacturing Organizations in the Era of Industry 4.03Harnessing the Power of Artificial Intelligence in Materials Science: An Overview14Deep learning in two-dimensional materials: Characterization, prediction, and design68Machine Learning-Based Prediction of Stability in High-Entropy Nitride Ceramics10Enhanced predictive optimization of methane dry reforming via ResponseSurface methodology and artificial neural network approaches: Insights using a novel nickel-strontium-zirconium-aluminum catalyst6A machine learning approach for dynamical modelling of Al distributions in zeolites via 23 Na/ 27 Al solid-state NMR7Low-dimensional N-heterocyclic carbenes nanomaterials: Promising supports of single atom catalysts4Artificial intelligence modeling for power system planning4Multi-iteration active learning for the composition design of potassium–sodium niobate ceramics with enhanced piezoelectric coefficient11From Sunlight to Solutions: Closing the Loop on Halide Perovskites3Feature mining for thermoelectric materials based on interpretable machine learning5Machine learning prediction of materials properties from chemical composition: Status and prospects29Development of an Analytical Model for Predicting the Tensile Modulus of Complex Polypropylene Compounds6Analysis on Mechanical Behavior of Additively Manufactured PLA/Eggshell Composites Using Machine Learning Algorithms5State-of-the-art review on various applications of machine learning techniques in materials science and engineering26Accelerating Perovskite Solar Cells Development with Machine Learning: Optimizing Efficiency Through Modeling and Shap Analysis0Active and transfer learning with partially Bayesian neural networks for materials and chemicals12Advances in van der Waals thermoelectric materials: prospects and challenges12DT-MIM: A network suitable for alloy microstructure evolution prediction and characterization0From synthesis to properties: expanding the horizons of machine learning in nanomaterials research39Machine Learning Interatomic Potentials and Orientational Defects in Polymers2Optimization of nickel-based catalysts for hydrogenolysis of light paraffins using machine learning5Solution-synthesized nanostructured materials with high thermoelectric performance6Modulating the properties of g-C3N4 through two-step annealing and ionic-liquid gating2Development of an Analytical Model for Predicting the Shear Viscosity of Polypropylene Compounds4Application of machine learning in polyimide structure design and property regulation5Machine Learning-Driven Prediction of Composite Materials Properties Based on Experimental Testing Data56The Role of Artificial Intelligence in Microstructural Characterization of Ferrous Materials: A Review of Tools, Findings, and Research Challenges1Detection of COVID-19, lung opacity, and viral pneumonia via X-ray using machine learning and deep learning17Model-Based Prediction of the Tensile Properties of Polypropylene Films Made from Recycled Materials3Development of PP Compound Recipes Using Genetic Algorithms and Analytical Models1A guided review of machine learning in the design and application for pore nanoarchitectonics of carbon materials85Machine learning-based optimization of cytotoxicity testing for assessing Zn-based biodegradable metals8Efficient dataset generation for machine learning halide perovskite alloys7Predicting and Understanding Work Functions of Double Transition Metal MXenes via Interpretable Machine Learning Methods4Machine Learning with Interpretable Local Descriptors for Hydrogen Evolution Reaction on Borophene: Prediction and Physical Insights4A systematic study on the optical properties and photovoltaic performance of SnS solar cells using Bethe-Salpeter equation and device simulation2Machine learning-guided exploration of carbon-based photothermal materials for solar evaporation20Accelerating tribological material discovery: A machine learning framework with predictive insights20Modeling and prediction of tribological properties of graphite-filled PTFE self-lubricating composites based on machine learning algorithms7Fracture behavior of 3D printed geopolymer concrete containing waste ceramic17Prediction of ABX3 Perovskite Formation Energy Using Machine Learning3General Spectral Model for Quantitative Interfacial Electronic State Analysis With Different Growth Modes0Artificial intelligence in materials science and engineering: Current landscape, key challenges, and future trajectories33Predicting unmeasured asymmetry time spectra in μ SR experiments using Random Forest0Accelerating the Discovery of Low-Dielectric Polyimides Based on Interpretable Machine Learning7Benchmarking optimization methods for materials research: Gradient descent and Bayesian optimization for lithium-ion battery aging diagnostics3Machine learning-driven discovery of multicomponent pharmaceutical solid forms via DualNet: confidence-aware prediction and ranking of salts and cocrystals6Evaluating the use of a machine learning simulator for structure–property prediction: A case study on disordered elastic networks2Adding machine learning to the polymer reaction engineering toolbox13Partitioning adsorption energy: An electronegativity-based descriptor for hydrogen adsorption on group IV and III–V 2D honeycombs0Interpretable Machine Learning for the Design of (K, Na)NbO 3 -Based Piezoceramics Using Combinatorial and Knowledge-Embedded Descriptors3A survey of AI-supported materials informatics7Robust Multiclass Pneumonia Classification via Multi-Head Attention and Transfer Learning Ensemble3Positron annihilation and AI-technology for creation of novel biosensors0Hybrid Architecture Based on Siamese U-Net for Few-Shot Image Segmentation of Nanomaterials0EcoCurrentNet an integrated DNN-CatBoost model for predicting optoelectronic material performance under varying conditions1Enhanced prediction and optimization of thin metal film optical properties using optimized ensemble learning models7Machine Learning Unlocks New Directions in Halide Perovskite Research6Gaining scientific understanding with small data machine learning: explainable molecule representations and their consensus2Accelerating Hydrogen Storage Material Discovery: Machine Learning Approach for Predicting Multi-Step Hydrogenation Energetics in Transition Metal-Doped Phosphorene0Accelerating Hydrogen Storage Material Discovery: Machine Learning Approach for Predicting Multi-Step Hydrogenation Energetics in Transition Metal-Doped Phosphorene0AI and Machine Learning: Revolutionizing Nanomaterial Research Through Synthesis, Characterization, and Applications0AI-powered OLEDs: speeding up innovation in displays3An Exploratory Analysis of Current and Future Trends of Artificial Neural Network (ANN) Paradigms in Wind Energy Systems0Artificial Intelligence for Science: A critical survey and outlook1Artificial intelligence-driven magnetic property prediction and materials discovery for next-generation spintronics0Classification of Perovskite Crystal Systems from Elemental Features Using Machine Learning1Machine learning approaches to quantify nanoscale variations in the mechanical properties of soft nanoparticles0Machine learning molecular dynamics for aqueous systems: Structure, dynamics, and reactivity0The Problem of Convergent Scientific Narratives in Single-Model Materials Regimes0A transferable data driven framework for electrolyte discovery1Pairwise Neural Networks for Ranking Molecular Structures Based on Properties0Machine learning techniques for estimating saturated soil hydraulic conductivity at the watershed scale: advances in pedotransfer functions0TopoChat: Enhancing Topological Materials Retrieval with Large Language Model and Multi-Source Knowledge1Towards a sustainable high-quality materials data ecosystem: frameworks and strategies6DT-MIM: A network suitable for alloy microstructure evolution prediction and characterization0AI-assisted characterization of piezoelectric behavior in hydroxyapatite-graphene nanocomposites for smart bioceramic applications1Machine Learning as a Catalyst in Advanced Materials Research and Development0Semi-Supervised Based Regression Algorithm for Limited Dataset0Roadmaps for dendrite suppression in next generation lithium-ion batteries: Toward sustainable energy solutions3Transfer learning-enabled performance prediction of metallic materials: Methods, applications and prospects6Machine learning prediction of multi-step hydrogenation energetics in transition metal-doped phosphorene2Data-driven design of electrocatalysts: Machine learning workflows, paradigm shifts, and applications4Machine Learning-Based Prediction of Polymer Properties Using Structure–Property Relationship Modeling1MATHEMATICAL MODELING OF THE CHANGE PROCESS IN PHYSICO-MECHANICAL PROPERTIES OF POLYURETHANE FOAMS BASED ON LIMITED EXPERIMENTAL SAMPLES0Harnessing AI for Heat Transfer: The Potential of Physics-Informed Neural Networks (PINNs)0Exploring multiscale modelling combined with machine learning: from electronic structure to pore-scale dynamics in complex materials1A Review of Recent Trends in Machine Learning Applications for Manufacturing Fiber-Reinforced Polymer Composites0Hybrid constitutive law with machine learning for sintering of advanced ceramics0GNNeF: Enhanced GNN PDE Solver with Embedded FNO0From Data Islands to Knowledge Networks in Tribology: Understanding the Modern Data Architecture0Small-sample machine learning for plasma electrolytic oxidation process–microstructure mapping: Minimizing pore size via a multilayer perceptron and Bayesian optimization0Machine learning-assisted formulation design of flame-retardant polyoxymethylene composites0Review and future directions for assessing the durability of glass-fibre reinforced polymer composites within the marine environment0Tutorials on Machine Learning Tools for Simulations in Electrocatalysis1Machine learning driven synthesis of nickel phosphate for advanced hybrid supercapacitors0Predictive Governance: The Management Dilemmas of AI-Driven Anti-Doping Education0Generative artificial intelligence for nanomaterial discovery and nanoengineering: From data-driven design to autonomous laboratories0

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