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Toward Development of Digital Twins for Materials via In-Situ Scanning Electron Microscope Experiments for Multiscale Validation Using Machine Learning
Completed
TRL 2 (started at 2, targeting 3)
Description
Deliver a novel in-situ mechanical testing capability for materials at the microscale and develop a machine learning (ML) toolset for validation of NASA physics-based micromechanics models
Benefits
Enable development of material digital twins at multiple length scales; ultimately accelerating material selection; design; and optimization for NASA space exploration missions
Details
| Technology area | Materials, Structures, Mechanical Systems, and Manufacturing > Materials > Computational Materials |
| Program | Center Innovation Fund: GRC CIF (GRC CIF) |
| Lead organization | Glenn Research Center, Cleveland, OH |
| Start date | 2024-10-01 |
| End date | 2025-09-30 |
Project contacts
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How to get involved
This is early/mid-stage (TRL 2) — the most realistic path in is NASA SBIR/STTR, which funds small businesses and research institutions to develop technology aligned with NASA's needs (equity-free, phased funding). Check whether a current SBIR/STTR solicitation topic overlaps with this project's technology area, or contact the project directly (above) to ask.
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