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RESEARCH PAPER · Matter · 2020

AI Applications through the Whole Life Cycle of Material Discovery

Jiali Li, Kaizhuo Lim, Haitao Yang, Zekun Ren, S. Raghavan, Po‐Yen Chen, Tonio Buonassisi, Xiaonan Wang

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AI Applications through the Whole Life Cycle of Material DiscoveryOriginalEthical Concerns: An overview of Artificial Intelligence System Development and Life Cycle4Microfluidic Synthesis of Semiconductor Materials: Toward Accelerated Materials Development in Flow41Self‐Driven Multistep Quantum Dot Synthesis Enabled by Autonomous Robotic Experimentation in Flow95ViscNet: Neural network for predicting the fragility index and the temperature-dependency of viscosity80Accelerated AI development for autonomous materials synthesis in flow68Characterising soft matter using machine learning52Toward autonomous design and synthesis of novel inorganic materials159Machine learning for advanced energy materials208Self‐Driven Multistep Quantum Dot Synthesis Enabled by Autonomous Robotic Experimentation in Flow31Machine Learning for Transition-Metal-Based Hydrogen Generation Electrocatalysts122A robust low data solution: Dimension prediction of semiconductor nanorods13Preparation of Micron-Sized Flower-Shaped SnO2 Particles and Its Application as Anode Materials for Lithium Ion Batteries (LIBs)1Nanoparticle synthesis assisted by machine learning545Microfluidic Studies of Cesium Lead Halide Perovskite Quantum Dots.0Artificial intelligence based operational strategy development and implementation for vibration reduction of a supercritical steam turbine shaft bearing40A deep learning protocol for analyzing and predicting ionic conductivity of anion exchange membranes31Strategic-level performance enhancement of a 660 MWe supercritical power plant and emissions reduction by AI approach67Data-driven design and controllable synthesis of Pt/carbon electrocatalysts for H2 evolution18On-the-fly interpretable machine learning for rapid discovery of two-dimensional ferromagnets with high Curie temperature92Applying Neuromorphic Computing Simulation in Band Gap Prediction and Chemical Reaction Classification4Data-Centric Architecture for Self-Driving Laboratories with Autonomous Discovery of New Nanomaterials23Graph Neural Networks for Materials Property Prediction: A Decadal Review of Advances and Limits0Inference Without Ground Truth: A Conceptual Theory of Validation in Materials AI0Intelligent control of nanoparticle synthesis through machine learning83A compendium and meta-analysis of flatband potentials for TiO2, ZnO, and SnO2 semiconductors in aqueous media60Machine Learning Analysis and Discovery of Zero-Dimensional ns 2 Metal Halides toward Enhanced Photoluminescence Quantum Yield68Automatic strain sensor design via active learning and data augmentation for soft machines101A Survey of Datasets, Preprocessing, Modeling Mechanisms, and Simulation Tools Based on AI for Material Analysis and Discovery48Autonomous Nanocrystal Doping by Self‐Driving Fluidic Micro‐Processors20Smart systems engineering contributing to an intelligent carbon-neutral future: opportunities, challenges, and prospects13Intelligent disassembly of electric-vehicle batteries: a forward-looking overview172MaterialsAtlas.org: a materials informatics web app platform for materials discovery and survey of state-of-the-art70Recent advancements in sustainable upcycling of solid waste into porous carbons for carbon dioxide capture99The case for data science in experimental chemistry: examples and recommendations83Opportunities for machine learning to accelerate halide-perovskite commercialization and scale-up35VenusAI: An artificial intelligence platform for scientific discovery on supercomputers17High-Throughput Synthesis of Thin Films for the Discovery of Energy Materials: A Perspective16Recent Achievements in Experimental and Computational Studies of Positive Electrode Materials for Nonaqueous Ca- and Al-Ion Batteries23Predicting Materials Parameters in Colloidal Quantum Dot Photovoltaic Devices Using Machine Learning Models Trained On Experimental Data0Bridging Multiscale Characterization Technologies and Digital Modeling to Evaluate Lithium Battery Full Lifecycle93Support Vector Machine-Based Phase Prediction of Multi-Principal Element Alloys7Predicting the formation of fractionally doped perovskite oxides by a function-confined machine learning method39A review of computational modeling techniques for wet waste valorization: Research trends and future perspectives52Deep learning-based density functionals empower AI for materials9Artificial Intelligence‐Based Material Discovery for Clean Energy Future47Machine learning for battery research110Materials discovery of ion-selective membranes using artificial intelligence30Identification of chemical compositions from “featureless” optical absorption spectra: Machine learning predictions and experimental validations24Discovery of MOFs for Hydrogen Storage via Machine Learning and First Principles Methods2Accelerated Design of Flame Retardant Polymeric Nanocomposites via Machine Learning Prediction45Borate-Based Compounds as Mixed Polyanion Cathode Materials for Advanced Batteries22Machine learning for membrane design and discovery144Machine learning-aided atomic structure identification of interfacial ionic hydrates from AFM images16Data-driven design of carbon-based materials for high-performance flexible energy storage devices25Computational and Data-Driven Materials Engineering: High-Throughput Computational Screening Platforms, Workflows, and Discovery Outcomes0MODELLING AN IMAGE DETECTION ALGORITHM TO EVALUATE THE DEGREE OF CORROSION0The Application of Novel Functional Materials to Machine Learning0Knowledge-integrated machine learning for materials: lessons from gameplaying and robotics137The rise of self-driving labs in chemical and materials sciences570Integrated data-driven modeling and experimental optimization of granular hydrogel matrices52Advanced ocean wave energy harvesting: current progress and future trends54Latest Advances in Manufacturing and Machine Learning of Bulk Metallic Glasses14Next-generation intelligent laboratories for materials design and manufacturing25Ratio Fluorescent Detecting of Tryptophan and Its Metabolite 5‐Hydroxyindole‐3‐acetic Acid Relevant with Depression via Tb(III) Modified HOFs Hybrids: Further Designing Recyclable Molecular Logic Gate Connected by Back Propagation Neural Network50Reshaping the material research paradigm of electrochemical energy storage and conversion by machine learning34Machine learning for optimal electrode wettability in lithium ion batteries29Modeling and predictive control of nonlinear processes using transfer learning method42Green synthesis of Fe3O4 nanoparticles using Alliaceae waste (Allium sativum) for a sustainable landscape enhancement using support vector regression41Unclonable MXene Topographies as Robust Anti‐Counterfeiting Tags via Fast Laser Scanning and Siamese Neural Networks10Thermochemical upcycling of food waste into engineered biochar for energy and environmental applications: A critical review51Artificial-intelligence-led revolution of construction materials: From molecules to Industry 4.0103AI for Nanomaterials Development in Clean Energy and Carbon Capture, Utilization and Storage (CCUS)122Silicon nanoparticles: Comprehensive review on biogenic synthesis and applications in agriculture96Data Mining in Material Science1Materials research in artificial intelligence era0Tensile Performance Mechanism for Bamboo Fiber-Reinforced, Palm Oil-Based Resin Bio-Composites Using Finite Element Simulation and Machine Learning37Machine Learning-Accelerated Discovery of Novel 2D Ferromagnetic Materials with Strong Magnetization1Recent advances and applications of machine learning in electrocatalysis36Unleashing the Power of Artificial Intelligence in Materials Design179Advancements in High‐Throughput Screening and Machine Learning Design for 2D Ferromagnetism: A Comprehensive Review10Advances in data‐assisted high‐throughput computations for material design112Machine learning-accelerated discovery of novel 2D ferromagnetic materials with strong magnetization21Machine Learning for Heavy Metal Removal from Water: Recent Advances and Challenges48DeepSC-Edge: Scientific Corrosion Segmentation with Edge-Guided and Class-Balanced Losses4Supporting the Demand on Mental Health Services with AI-Based Conversational Large Language Models (LLMs)54Machine learning for expediting next-generation of fire-retardant polymer composites43A Conceptual Basis for Reducing the Number of Complex Multi-Parametric Experiments in Bio-Production Engineering via Artificial Intelligence1A Conceptual Framework for Trustworthy AI Decisions Across the Materials Design Lifecycle1Algorithmic Consensus vs Scientific Consensus in Materials Prediction0Artificial intelligence-enabled optimization of battery-grade lithium carbonate production4ESG and Circular Economy5Introduction0Learning conditional policies for crystal design using offline reinforcement learning4Overview of Applications of Artificial Intelligence (AI) in Diverse Fields9Property Prediction0Sustainable valorisation of food waste into engineered biochars for CO 2 capture towards a circular economy32Sustainably transforming biomass into advanced carbon materials for solid-state supercapacitors: a review19Toward AI/ML-assisted discovery of transition metal complexes4Uncertainty-Aware Surrogate Modeling of High-Throughput DFT Data for Rapid Materials Screening0What Counts as Knowledge in AI-Driven Materials Science? A Philosophical and Practical Reframing0Machine learning for membrane design in energy production, gas separation, and water treatment: a review111Nature-Inspired Superhydrophobic Coating Materials: Drawing Inspiration from Nature for Enhanced Functionality131Effect of structural parameters on compression performance of autoclaved aerated concrete: Simulation and machine learning13Optimizing high-speed rotating shaft vibration control: Experimental investigation of squeeze film dampers and a comparative analysis using Artificial Neural Networks (ANN) and Response Surface Methodology (RSM)40Single-atom catalysts property prediction via Supervised and Self-Supervised pre-training models15Signal acquisition of brain–computer interfaces: A medical-engineering crossover perspective review67An extended UTAUT model study on the adoption behavior of artificial intelligence technology in construction industry5Introductory Chapter: Current State and Achievements of Data Augmentation1A Data-Centric AI Paradigm for Socio-Industrial and Global Challenges16Machine learning for full lifecycle management of lithium-ion batteries43Unlocking the world of material intelligence with liquid crystal polymers3Machine Learning and Small Data-Guided Optimization of Silica Shell Morphology on Gold Nanorods10Toward an AI Era: Advances in Electronic Skins168Materials With the Help of Mechanical Properties for Electrical Vehicle Chassis using Machine Learning Methods0Predicting PbS Colloidal Quantum Dot Solar Cell Parameters Using Neural Networks Trained on Experimental Data6Pre-training with fractional denoising to enhance molecular property prediction32A prompt-engineered large language model, deep learning workflow for materials classification50Multi-objective optimisation and verification of creep-resistant Ni-base superalloy for electron-beam powder-bed-fusion7Machine learning‐aided process design using limited experimental data: A microwave‐assisted ammonia synthesis case study9New principles and methods for designing corrosion-resistant magnesium alloys0Advancements in spray drying, part I: From critical factors to variegated applications7Machine learning applied to the design and optimization of polymeric materials: A review51Intelligent Generic High‐Throughput Oscillatory Shear Technology Fabricates Programmable Microrobots for Real‐Time Visual Guidance During Embolization8Machine Learning-Aided Inverse Design and Discovery of Novel Polymeric Materials for Membrane Separation95Integration of supervised machine learning for predictive evaluation of chemical looping hydrogen production and storage system5AI-Assisted 3D Modeling Strategy for Microstructure-Based Functional Surfaces Using ChatGPT and Random Forest3Accelerating battery innovation: AI-powered molecular discovery58Advanced scientific information mining using LLM-driven approaches in layered cathode materials for sodium-ion batteries10AI Thinking: a framework for rethinking artificial intelligence in practice14Artificial Intelligence and Economic Activity—The Greatest Challenges, Threats and the Latest Changes in EU Law0Harnessing Nano & AI for Sustainable Energy Application1Recent progress of two-dimensional photothermal nanomaterials in personal thermal management9Scientific Risk in Autonomous Materials Discovery: A Conceptual Framework for Anticipating Unsafe Recommendations1Transition metal phosphide/ molybdenum disulfide heterostructures towards advanced electrochemical energy storage: recent progress and challenges40Optimising the regeneration process of spent lithium‑cobalt oxide cathode through performance analysis model10Machine learning analysis for the rheological mechanism of polysaccharide colloids9Leveraging machine learning for accelerated materials innovation in lithium-ion battery: A review54Deep Learning-Driven Molecular Generation and Electrochemical Property Prediction for Optimal Electrolyte Additive Design8Design and Development of Fire-Safety Materials in Artificial Intelligence Era6Exploration of the Application of Data-Driven and Generation Models in the Design of Thermoplastic Vulcanizate Rubbers1Application of Machine Learning in Nano Research — A Review2An Artificial Intelligence Approach to Evaluating the Sound Absorption Performance of Materials: A Systematic Review0Language models for materials discovery and sustainability: Progress, challenges, and opportunities26Machine learning applications in SEM-based pore analysis: a review31Synthesis of Two-Dimensional Metal Nanomaterials for Electrocatalytic Multielectron Transfer Reactions6Application of generative artificial intelligence in catalysis7Reaching new frontiers in nanoelectronics through artificial intelligence4Artificial intelligence in materials science and engineering: Current landscape, key challenges, and future trajectories33A formulation dataset of poly(lactide-co-glycolide) nanoparticles for small molecule delivery8Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook10

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