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directly into scientific workflows to enable autonomous, data-driven discovery in areas such as fusion energy, materials science, climate science, and nuclear energy. As part of ORNL’s interdisciplinary
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system) and disordered materials is also desirable. The project will involve developing autonomous materials discovery workflows on HPC platforms that can learn structure-chemistry-property relationship in
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integrated autonomous experimental synthesis and characterization cross-facility agentic-AI platforms that allow real-time guidance and control of these multi-modal experiments for targeted discovery of novel
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