What is missing in autonomous discovery: open challenges for the community

Maffettone, Phillip M.; Friederich, Pascal; Baird, Sterling G.; Blaiszik, Ben; Brown, Keith A.; Campbell, Stuart I.; Cohen, Orion A.; Davis, Rebecca L.; Foster, Ian T.; Haghmoradi, Navid; Hereld, Mark; Joress, Howie; Jung, Nicole; Kwon, Ha-Kyung; Pizzuto, Gabriella; Rintamaki, Jacob; Steinmann, Casper; Torresi, Luca; Sun, Shijing

doi:10.1039/d3dd00143a

Title: What is missing in autonomous discovery: open challenges for the community

Journal Article · 16 October 2023 · Digital Discovery

DOI: https://doi.org/10.1039/d3dd00143a · OSTI ID:2202520

^[1];

^[2]; Baird, Sterling G. ^[3];

^[4];

^[5];

^[6]; Cohen, Orion A. ^[7];

^[8]; Foster, Ian T. ^[4];

^[2];

^[4]; Joress, Howie ^[9]; Jung, Nicole ^[2];

^[10];

^[11]; Rintamaki, Jacob ^[12];

^[13]; Torresi, Luca ^[2]; Sun, Shijing ^[14]

Brookhaven National Laboratory (BNL), Upton, NY (United States). National Synchrotron Light Source II (NSLS-II); BigHat Biosciences, San Mateo, CA (United States)
Karlsruhe Institute of Technology (KIT) (Germany)
University of Utah, Salt Lake City, UT (United States)
University of Chicago, IL (United States); Argonne National Laboratory (ANL), Argonne, IL (United States)
Boston University, MA (United States)
Brookhaven National Laboratory (BNL), Upton, NY (United States). National Synchrotron Light Source II (NSLS-II)
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
University of Manitoba, Winnipeg, MB (Canada)
National Institute of Standards and Technology (NIST), Gaithersburg, MD (United States)
Toyota Research Institute, Los Altos, CA (United States)
University of Liverpool (United Kingdom)
Stanford University, CA (United States)
Aalborg University (Denmark)
Toyota Research Institute, Los Altos, CA (United States); University of Washington, Seattle, WA (United States)

Self-driving labs (SDLs) leverage combinations of artificial intelligence, automation, and advanced computing to accelerate scientific discovery. The promise of this field has given rise to a rich community of passionate scientists, engineers, and social scientists, as evidenced by the development of the Acceleration Consortium and recent Accelerate Conference. Despite its strengths, this rapidly developing field presents numerous opportunities for growth, challenges to overcome, and potential risks of which to remain aware. This community perspective builds on a discourse instantiated during the first Accelerate Conference, and looks to the future of self-driving labs with a tempered optimism. Incorporating input from academia, government, and industry, we briefly describe the current status of self-driving labs, then turn our attention to barriers, opportunities, and a vision for what is possible. Our field is delivering solutions in technology and infrastructure, artificial intelligence and knowledge generation, and education and workforce development. In the spirit of community, we intend for this work to foster discussion and drive best practices as our field grows.

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Research Organization:: Brookhaven National Laboratory (BNL), Upton, NY (United States); Argonne National Laboratory (ANL), Argonne, IL (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities (SUF); USDOE Laboratory Directed Research and Development (LDRD) Program; Federal Ministry of Education and Research (BMBF); The Villum Foundation

Grant/Contract Number:: SC0012704; AC02-06CH11357; 23-039; 01DM21001B; 01DM21002A; 50405

OSTI ID:: 2202520

Alternate ID(s):: OSTI ID: 2203710; OSTI ID: 2475504

Report Number(s):: BNL-224930-2023-JAAM

Journal Information:: Digital Discovery, Vol. 2, Issue 6; ISSN 2635-098X

Publisher:: Royal Society of ChemistryCopyright Statement

Country of Publication:: United States

Language:: English

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