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BeyondFingerprinting: AI-guided discovery of robust materials & processes

Technical Report ·
DOI:https://doi.org/10.2172/2462990· OSTI ID:2462990
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  1. Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
  2. Sandia National Laboratories (SNL-CA), Livermore, CA (United States)
  3. US Naval Academy, Annapolis, MD (United States)
+ Show Author Affiliations
BeyondFingerprinting was a 2021-2024 Sandia Grand Challenge LDRD exploring the potential to develop new resilient materials and manufacturing processes by taking an artificial-intelligence (AI)-guided approach that integrates human-subject-matter expertise with algorithms enriched with physics-based constraints to unearth process-structure-property correlations. Such algorithms, trained on high-throughput experiments and simulations, are shown to serve as surrogate models that efficiently detect key “fingerprints” in materials data, prognose material performance, and guide effective process improvements. To accelerate broader adoption across mission areas, this AI-guided approach was demonstrated with three complex process-centric exemplars: electroplating, physical vapor deposition, and laser powder bed fusion. Together, these exemplars impact nearly every hardware component relevant to DOE and NNSA national security missions.
Research Organization:
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA); USDOE Laboratory Directed Research and Development (LDRD) Program
DOE Contract Number:
NA0003525
OSTI ID:
2462990
Report Number(s):
SAND--2024-11708
Country of Publication:
United States
Language:
English

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Related Subjects

36 MATERIALS SCIENCE
97 MATHEMATICS AND COMPUTING