Human-in-the-loop for Bayesian autonomous materials phase mapping
Matter. [All Versions]. Autonomous experimentation achieves user objectives more efficiently than Edisonian studies by combining machine learning and laboratory automation to iteratively select and perform experiments. Integrating knowledge from theory, simulations, literature…
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Balancing autonomy and expertise in autonomous synthesis laboratories nature.com
Nature Computational Science, 2025. [All Versions]. Autonomous synthesis laboratories promise to streamline the plan–make–measure–analyze iteration loop. Here, the authors comment on the barriers in the field, the promise of a human on-the-loop approach, and strategies for…
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AlphaFlow: autonomous discovery and optimization of multi-step chemistry using a self-driven fluidic lab guided by… nature.com
Nature Communications, 2023. [All Versions]. Closed-loop, autonomous experimentation enables accelerated and material-efficient exploration of large reaction spaces without the need for user intervention. However, autonomous exploration of advanced materials with complex…
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Human–machine collaboration for improving semiconductor process development nature.com
Nature, 2023. [All Versions]. [Nature News]. This work studies Bayesian optimization algorithms to investigate how artificial intelligence (AI) might decrease the cost of developing complex semiconductor chip processes. In particular, this work create a controlled virtual…
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A dynamic knowledge graph approach to distributed self-driving laboratories nature.com
Nature Communications, 2024. [All Versions]. This work employs ontologies to capture data and material flows in design-make-test-analyse cycles, utilising autonomous agents as executable knowledge components to carry out the experimentation workflow. Data provenance is recorded…
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Autonomous chemical research with large language models nature.com
Nature, 2023. [All Versions]. An artificial intelligence system driven by GPT-4 that autonomously designs, plans and performs complex experiments by incorporating large language models empowered by tools such as internet and documentation search, code execution and experimental…
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An autonomous laboratory for the accelerated synthesis of novel materials nature.com
Nature, 2023. [All Versions]. This paper introduces the A-Lab, an autonomous laboratory for the solid-state synthesis of inorganic powders. This platform uses computations, historical data from the literature, machine learning (ML) and active learning to plan and interpret the…
AGI & CoCoSci › Papers > Bayesian Modeling > Bayesian Optimization: “Matter. [All Versions]. Autonomous experimentation achieves user objectives more efficiently than Edisonian studies by combining machine learning and laboratory automation to iteratively select and perform experiments. Integrating knowledge from theory, simulations, literature…”