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Meeting 2027 TMS Annual Meeting & Exhibition
Symposium Hume-Rothery Symposium: Data-Driven Materials Discovery and Phase Stability
Presentation Title AI in the Wild: Autonomous laboratories for materials synthesis
Author(s) Gerbrand Ceder
On-Site Speaker (Planned) Gerbrand Ceder
Abstract Scope A-lab is an autonomous facility for the closed-loop synthesis of inorganic materials from powder precursors and a test bed for the interaction of AI and the physical world of materials experimenting. All synthesis and characterization actions in A-lab and all sample transfers between them are fully automated, leading to a lab that can synthesize and structurally characterize compounds within 10-20 hrs of initiation. The lab can be flexibly organized into workflows to satisfy the varying need of distinct research projects. Autonomous decision making in an automated lab can be challenging as experimental is often noisy, incomplete, or ambiguous. I will show examples of how efficacy of decision making may require statistical priors that are based on chemical or human experience in order to produce reasonable data interpretation.
Proceedings Inclusion? Planned:
Keywords Ceramics, Machine Learning,

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

A Computational Thermodynamics Framework with Intrinsic Chemical Short-Range Order
Accelerating Oxygen Ion Conductor Discovery Through First-Principles Design and Autonomous Materials Optimization
AI in the Wild: Autonomous laboratories for materials synthesis
Alloy theory applied to the anodes of all-solid-state batteries
Alloying effects on deformation modes in wrought magnesium: An integrated computational and experimental investigation
Atomic-Scale Simulations of Metal/Molten-Salt Interfaces by Machine-Learning Interatomic Potentials
Beyond Order: A Disorder-Aware Workflow toward OQMD 2.0
Beyond Randomness: Designing Short-Range Order for Materials Performance
Bonding-Driven Discovery and Design of Thermoelectric Materials
Calibrated Machine-Learning Uncertainty for Data-Driven Alloy Design
Chemical Intuition as a Guide to Data-Driven Materials Discovery
Computational Design of Battery Guided by Degradation Mechanism
Computational discovery of materials for energy storage
Data- and Simulation-Driven Design of Structural and Functional Materials: Successes and Challenges
Data-Driven Discovery of Novel High-Performance Photovoltaics in an Experimentally Known Family of Quaternary Chalcogenides
Data-driven Prediction of Solid-State Synthesis
Elemental Features for Data-Driven Materials Properties Prediction
Elucidating the role of solute-solute interactions on diffusion in Ni-based substitutional solid solutions
Exploring the electronic structure of all known inorganics - from transport to superconductivity to topology.
First-principles modeling of disorder in cathodes and beyond
From Computational Design to Accelerated Discovery of High-Entropy Alloys
Functional Synthesizability: Tuning the Extreme-Properties of High-Entropy Ceramics
High-Throughput Anharmonic Phonons for Data-Driven Materials Discovery, Phase Stability, and Thermal Transport
How Computational Modeling Shapes Materials at Apple
Hume-Rothery Strikes Again: Intrinsic Correlations Permit Tailored Materials With Exceptional Properties
Integrating Automated Computation with Experiment for Accelerated Materials Discovery
Irreversible Thermodynamic Basis for the Phase-field Method of Ordered Stoichiometric Compounds
Lithium Extraction with Ion Exchange at Lilac Solutions
Mapping Lithium-Ion Transport in Sulfide Argyrodites: From Defect Chemistry to Composite Interfaces
Phase Diagrams On-Demand
Relationship Between Configurational and Vibrational Entropies of Mixing and Their Effects on Phase Diagrams
Standing on Chris's Shoulders: From High-Throughput DFT to AI for Materials Discovery
Symmetry Broken DFT Corrects the Stability and Mott Band Gap Errors Without Adding Strong Correlations
The Generalized Aliasing Decomposition, A New Paradigm for Modeling
The Possibility of New Complex Magnet Material
The Spatial Arrangement of Nanoparticles on Substrates and the Role of Phase Transformations
Theoretical Insights Into Hydrogenation and Proton Transport in ABO3 Perovskite
Thermodynamic and Kinetic Stability of M–N–C Active Sites for O₂ Reduction
Towards Ai-enabled High Throughput Characterization and Materials Discovery
Zentropy: A Thermodynamic Framework Bridging Phase Stability, Data-Driven Modeling, and Artificial Intelligence

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