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Shaping the Future of Self-Driving Autonomous Laboratories Workshop

Technical Report ·
DOI:https://doi.org/10.2172/2481197· OSTI ID:2481197
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  1. Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
  2. Air Force Research Lab. (AFRL), Wright-Patterson AFB, OH (United States)
  3. SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States)
  4. University of Southern California, Information Sciences Institute
  5. Argonne National Laboratory (ANL), Argonne, IL (United States)
  6. Johns Hopkins Univ., Baltimore, MD (United States)
  7. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  8. Princeton Plasma Physics Laboratory (PPPL), Princeton, NJ (United States)
  9. Univ. of Wisconsin, Madison, WI (United States)
  10. University of North Carolina, Chapel Hill, Renaissance Computing Insitute (RENCI)
  11. Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
  12. Carnegie Mellon Univ., Pittsburgh, PA (United States)
  13. Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
  14. North Carolina State University, Raleigh, NC (United States)
  15. Univ. of Tennessee, Knoxville, TN (United States)
+ Show Author Affiliations

The "Shaping the Future of Self-Driving Autonomous Laboratories" workshop, held in Denver on November 7-8, 2024, brought together leading experts from materials science and computing to address the growing need to revolutionize scientific research through AI-driven autonomous laboratories. The workshop identified critical challenges, including the integration of heterogeneous data, development of AI systems that understand fundamental physical principles, and comprehensive safety protocols. Key recommendations emerged around developing universal laboratory equipment interfaces, implementing automated metadata collection systems, and creating hybrid AI approaches that combine data-driven learning with scientific principles. The workshop emphasized maintaining human oversight while leveraging automation, transforming scientific education to prepare the next generation of researchers, and establishing a national consortium leveraging DOE facilities as anchors for broader collaboration with academia and industry. Participants stressed the urgency of addressing the growing disconnect between human decision-making timescales and modern instrumentation capabilities, highlighting the need for strategic automation while preserving essential human insight and oversight in the research process.

Research Organization:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
Sponsoring Organization:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR); USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities (SUF)
DOE Contract Number:
AC05-00OR22725
OSTI ID:
2481197
Report Number(s):
ORNL/TM--2024/3714
Country of Publication:
United States
Language:
English

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Related Subjects

36 MATERIALS SCIENCE
97 MATHEMATICS AND COMPUTING