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Description
R. Bruce van Dover1 John Gregoire2 Carla Gomes1 Bart Selman1 Christopher Wolverton3 Alex Zunger4

1, Cornell University, Ithaca, New York, United States
2, California Institute of Technology, Pasadena, California, United States
3, Northwestern University, Evanston, Illinois, United States
4, University of Colorado Boulder, Boulder, Colorado, United States

Many new materials have been suggested, either by first principles theory or by heuristic inference, as having critical enabling properties for technologies such as Li-ion batteries, transparent conductors, and photochemical energy capture. Yet theory has not provided adequate guidance regarding the conditions, if any, under which they can be synthesized. Traditional synthesis of novel compounds often involves laborious and slow manual iterative exploration of composition and processing space. We are radically transforming the ability to identify and synthesize new materials using innovative AI-based strategies for reasoning and conducting science, including the representation, planning, optimization, and learning of materials knowledge. The logical structure of our approach, SARA (Scientific Autonomous Reasoning Agent), is based on a community of software agents that cooperatively generate hypotheses and autonomously test them through autonomous execution of the materials discovery/development process, and is enabled through concomitant development of robotic processing and characterization tools, on-the-fly DFT calculations, and AI-based algorithms. Our approach is further augmented with human insights so that the artificial intelligence leverages the human intelligence of expert scientists, creating an unprecedented platform for human-machine collaboration. SARA includes methods and methodologies for the rational design of functional materials and for discovering the requisite synthesis parameters for both stable and metastable materials.

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