An autonomous laboratory for the accelerated synthesis of inorganic materials

, we introduce the A-Lab, an autonomous laboratory for the solid-state synthesis of inorganic powders. Analysis of the failed syntheses provides direct and actionable suggestions to improve current techniques for materials screening and synthesis design.

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• 1 This platform uses computations, historical data from the literature, machine learning (ML) and active learning to plan and interpret the outcomes of experiments performed using robotics.
• 2 Over 17 days of continuous operation, the A-Lab realized 41 novel compounds from a set of 58 targets including a variety of oxides and phosphates that were identified using large-scale ab initio phase-stability data from the Materials Project and Google DeepMind.
• 3 Synthesis recipes were proposed by natural-language models trained on the literature and optimized using an active-learning approach grounded in thermodynamics.

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

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