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RESEARCH PAPER · Science Advances · 2021

Autonomous materials synthesis via hierarchical active learning of nonequilibrium phase diagrams

Sebastian Ament, Maximilian Amsler, Duncan R. Sutherland, Ming-Chiang Chang, Dan Guevarra, Aine Connolly, John M. Gregoire, Michael O. Thompson, Carla Pedro Gomes, Robert Bruce Van Dover

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Autonomous materials synthesis via hierarchical active learning of nonequilibrium phase diagramsOriginalA Conceptual Theory of Model-Science Interface: Where AI Outputs Become Experimental Inputs0Discovery without Understanding: A Systems Theory of Black-Box Optimization in Autonomous Materials Engineering0Integration of Constraint Programming, Artificial Intelligence, and Operations Research9Metalated covalent organic frameworks: from synthetic strategies to diverse applications326The Treatment of Absence and Null Results in Materials Machine Learning Literature: A Review Study0A self-driving laboratory advances the Pareto front for material properties211Materials Data toward Machine Learning: Advances and Challenges62Towards Automated Design of Corrosion Resistant Alloy Coatings with an Autonomous Scanning Droplet Cell18A comparison of explainable artificial intelligence methods in the phase classification of multi-principal element alloys33Bayesian optimization with experimental failure for high-throughput materials growth53Artificial intelligence for materials research at extremes20Toward autonomous laboratories: Convergence of artificial intelligence and experimental automation118Upcoming Transformations in Integrated Energy/Chemicals Sectors: Some Challenges and Several Opportunities27Human-in-The-Loop for Bayesian Autonomous Materials Phase Mapping0Multimodal, Physics-Informed Machine Learning for Accelerated Materials Design and Discovery0Orchestrating nimble experiments across interconnected labs37Simulation Priors in Machine Learning Materials Models: Hidden Physics Assumptions0Tackling data scarcity with transfer learning: a case study of thickness characterization from optical spectra of perovskite thin films14When Optimization Conflicts with Discovery: A Conceptual Tension in Materials AI0Emerging Trends in Machine Learning: A Polymer Perspective187How to build an effective self-driving laboratory15Next-generation intelligent laboratories for materials design and manufacturing25The Functional Materials Beamline at CHESS20Combinatorial synthesis for AI-driven materials discovery114ET-AL: Entropy-targeted active learning for bias mitigation in materials data30Scalable multi-agent lab framework for lab optimization33Active learning-assisted neutron spectroscopy with log-Gaussian processes20A self-driving laboratory optimizes a scalable process for making functional coatings17Scientific discovery in the age of artificial intelligence1779Robotic pendant drop: containerless liquid for μs-resolved, AI-executable XPCS10Discovery Precision: An effective metric for evaluating performance of machine learning model for explorative materials discovery21Should We Teach AI a Better Scientific Method?5Accelerating CALPHAD-Based Phase Diagram Predictions in Complex Alloys Using Universal Machine Learning Potentials: Opportunities and Challenges0Autonomous millimeter scale high throughput battery research system12Experimental Validation Bottlenecks in AI-Guided Materials Design0Learning material synthesis–process–structure–property relationship by data fusion: Bayesian co-regionalization N-dimensional piecewise function learning9Physics-driven discovery and bandgap engineering of hybrid perovskites12Recent Advances in Machine Learning-Accelerated Materials Discovery — From Descriptors to Autonomous Experiments0Representation Drift in Iterative Materials Learning Systems0Autonomous millimeter scale high throughput battery research system (Auto-MISCHBARES)0Autonomous millimeter scale high throughput battery research system (Auto-MISCHBARES)1Autonomous millimeter scale high throughput battery research system (Auto-MISCHBARES)0Human-in-the-loop for Bayesian autonomous materials phase mapping25Designing workflows for materials characterization22Navigating phase diagram complexity to guide robotic inorganic materials synthesis82Artificial intelligence enabled smart design and manufacturing of advanced materials: The endless Frontier in AI + era51Targeted materials discovery using Bayesian algorithm execution48AIPHAD, an active learning web application for visual understanding of phase diagrams12Classification Of Biomaterials and Their Applications7Self-Driving Laboratories for Chemistry and Materials Science674Active Learning for Rapid Targeted Synthesis of Compositionally Complex Alloys3Automation and Machine Learning for Accelerated Polymer Characterization and Development: Past, Potential, and a Path Forward38Active learning assisted piezoelectric materials synthesis on the basis of composite decision-making10Black-box optimization technique for investigation of surface phase diagram0Polymorphous nature of the local structure of δ − B i 2 O 35Autonomous Laboratories and Closed-Loop Materials Discovery: A Conceptual Framework for Self-Driving Experimentation0Gaussian processes for dynamics learning in model predictive control16Physics-informed Gaussian process classification for constraint-aware alloy design5Resource Allocation without Deliberation: Governance Structures in Autonomous Materials Experimentation0Runaway Discovery Trajectories: Intervention Thresholds in Self-Reinforcing Materials AI Systems0The Problem of Negative Results in Materials AI: A Conceptual Proposal for Failure-Aware Learning Systems0Accelerating CALPHAD-based phase diagram predictions in complex alloys using universal machine learning potentials: Opportunities and challenges66Frequency transfer and inverse design for metasurface under multi-physics coupling by Euler latent dynamic and data-analytical regularizations35Laser‐Induced Crystallization and Oxidation Phase Diagrams for High‐Throughput Evaluation of MoS 2 /MoO x Optical Thin Films4Probabilistic phase labeling and lattice refinement for autonomous materials research9Artificial Intelligence‐Driven Approaches in Semiconductor Research44Machine Learning-Based High Entropy Alloys-Algorithms and Workflow: A Review10Real-time experiment-theory closed-loop interaction for autonomous materials science29Artificial Intelligence for Materials Discovery, Development, and Optimization171AutoSAS: A new human-aside-the-loop paradigm for automated SAS fitting for high throughput and autonomous experimentation1Bayesian Optimization for Multicomponent Supramolecular Systems7Benchmarking self-driving labs13Building an affordable self-driving lab: Practical machine learning experiments for physics education using Internet-of-Things1Dynamical mean field theory for real materials on a quantum computer3PhaseXplorer Creates High-Dimensional Phase Diagrams with Closed-Loop Active Learning5A self-driving physical vapor deposition system making sample-specific decisions on the fly14Machine learning potentials for alloys: a detailed workflow to predict phase diagrams and benchmark accuracy10Intelligent screening of porous materials: A review of active-learning approaches in MOF research6Networking autonomous material exploration systems through transfer learning6Role of the thermomagnetic coupling mechanism in phase-change materials for advanced applications3Bayesian diversity control for batch-based phase diagram determination0Metallurgy-informed Bayesian optimization: rethinking alloy discovery and design0Review of module designs for organic and perovskite solar cells12Instabilities and phase transitions in architected metamaterials: a gradient-enhanced continuum approach2Predicting DNA Origami Stability in Physiological Media by Machine Learning4Machine Learning Toolkits and Frameworks for Materials Design7Next-generation hydrogen storage: Artificial intelligence-powered optimization for clean energy1Active Learning‐Guided Polymorph Control in Co‐Precipitation Synthesis1LLMs, RAG systems, and agents in crystalline materials discovery and characterization: A systematic review0Beyond Molecular Determinism: State‐Convergent Polymerization as a Functional Design Principle Under Chemical Complexity0Real-time Multi-instrument Autonomous Materials Screening for Discovery of Novel Phase-change Memory Materials0Toward autonomous experimentation: Bayesian optimization over problem formulation space for accelerated alloy development0Autonomous Materials Exploration Integrates Automated Phase Identification and AI Agents Enhanced by Human Guidance0AI for Accelerated Materials Discovery: From Generative Design to Autonomous Realization2A review of autonomous experimentation in lignocellulosic bioethanol production: Self-driving laboratory strategies for process optimization0Large-language-model-driven adaptive search space definition for autonomous closed-loop materials exploration0Autonomous Multi‐Objective Nanoscale Characterization of Combinatorial (Al, Sc, B)N Films Reveals Composition‐Dependent Ferroelectric Regimes0From Coprecipitation to Nanostructure: Formation, Morphology, and Reactive-Site Accessibility in Fe-Containing Binary Layered Double Hydroxides0

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