CaltechAUTHORS
Published September 1, 2021 | Version public
Journal Article Metadata-only

Autonomous experimentation systems for materials development: A community perspective

Creators

  • 1. ROR icon University of Pennsylvania
  • 2. ROR icon National Institute of Standards and Technology
  • 3. ROR icon University of Maryland, College Park
  • 4. ROR icon Boston University
  • 5. ROR icon University at Buffalo, State University of New York
  • 6. ROR icon Fordham University
  • 7. ROR icon Columbia University
  • 8. ROR icon Brookhaven National Laboratory
  • 9. ROR icon Massachusetts Institute of Technology
  • 10. ROR icon Argonne National Laboratory
  • 11. ROR icon University of Chicago
  • 12. ROR icon Cornell University
  • 13. ROR icon California Institute of Technology
  • 14. ROR icon Stanford Synchrotron Radiation Lightsource
  • 15. ROR icon Toyota Motor Corporation (United States)
  • 16. ROR icon Florida State University
  • 17. ROR icon Lawrence Berkeley National Laboratory
  • 18. ROR icon Kebotix (United States)
  • 19. ROR icon Wright-Patterson Air Force Base

Abstract

Solutions to many of the world's problems depend upon materials research and development. However, advanced materials can take decades to discover and decades more to fully deploy. Humans and robots have begun to partner to advance science and technology orders of magnitude faster than humans do today through the development and exploitation of closed-loop, autonomous experimentation systems. This review discusses the specific challenges and opportunities related to materials discovery and development that will emerge from this new paradigm. Our perspective incorporates input from stakeholders in academia, industry, government laboratories, and funding agencies. We outline the current status, barriers, and needed investments, culminating with a vision for the path forward. We intend the article to spark interest in this emerging research area and to motivate potential practitioners by illustrating early successes. We also aspire to encourage a creative reimagining of the next generation of materials science infrastructure. To this end, we frame future investments in materials science and technology, hardware and software infrastructure, artificial intelligence and autonomy methods, and critical workforce development for autonomous research.

Additional Information

© 2021 Published by Elsevier Inc. Available online 26 July 2021. The authors gratefully acknowledge the contributions of the participants of the Autonomous Systems for Materials Development Workshop, held at the University of Pennsylvania Singh Center for Nanotechnology, 4–6 September, 2019, with support from the University of Pennsylvania, the Air Force Research Laboratory, Materials & Manufacturing Directorate, ACS Combinatorial Science, and the NSF through the University of Pennsylvania Materials Research Science and Engineering Center (MRSEC) (DMR-1720530). We also gratefully acknowledge John Russell of the Singh Center for his assistance in organizing this workshop. This research used resources of the Advanced Light Source, which is a DOE Office of Science User Facility under contract no. DE-AC02-05CH11231. Support from the Air Force Research Laboratory Air Force Office of Scientific Research (AFOSR) LRIR no. 19RXCOR322 is gratefully acknowledged. K.A.B. acknowledges support from NSF CMMI-1661412. J.S. acknowledges support from the National Science Foundation (grant no. DMR-1928882), the Defense Advanced Research Projects Agency (contract no. HR001118C0036), and the Camille and Henry Dreyfus Foundation (TH-14-010). S.J.L.B. was supported by the U.S. National Science Foundation through grant DMREF-1922234. J.M.G. and C.P.G. acknowledge support from U.S. Department of Energy Office of Basic Energy Sciences under award DE-SC0020383. C.P. acknowledges support from AFOSR grant FA9550-18-1-0144. The authors acknowledge Lianne M.C. Beltran for professional editing. Declaration of interests: S.K.S. is a founder of Kebotix, Inc. J.S. is a member of the scientific advisory board of Atinary Technologies, Inc. J.M.G. is a co-inventor on United States Patent Application 20200340941 related to the manuscript. Data and code availability: ARES OS Software is available under the AFRL Open Source Software License at https://forms.gle/BetmdJtCAFwRLBiU6.

Additional details

Identifiers

Eprint ID
110087
DOI
10.1016/j.matt.2021.06.036
Resolver ID
CaltechAUTHORS:20210729-223028773

Related works

Describes
10.1016/j.matt.2021.06.036 (DOI)
https://forms.gle/BetmdJtCAFwRLBiU6 (URL)

Funding

University of Pennsylvania
Air Force Research Laboratory (AFRL)
American Chemical Society
NSF
DMR-1720530
Department of Energy (DOE)
DE-AC02-05CH11231
Air Force Office of Scientific Research (AFOSR)
19RXCOR322
NSF
CMMI-1661412
NSF
DMR-1928882
Defense Advanced Research Projects Agency (DARPA)
HR001118C0036
Camille and Henry Dreyfus Foundation
TH-14-010
NSF
DMR-1922234
Department of Energy (DOE)
DE-SC0020383
Air Force Office of Scientific Research (AFOSR)
FA9550-18-1-0144

Dates

Created
2021-08-02
Created from EPrint's datestamp field
Updated
2021-09-13
Created from EPrint's last_modified field

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