We propose an ML enhanced mixed-variable design optimization framework to efficiently extract useful information from existing data in literature and physics-based simulations to guide the autonomous search for optimal materials designs.
|Effective start/end date||4/28/20 → 11/30/22|
- Advanced Research Projects Agency - Energy (DE-AR0001209)
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