Stach, Eric and DeCost, Brian and Kusne, A. Gilad and Hattrick-Simpers, Jason and Brown, Keith A. and Reyes, Kristofer G. and Schrier, Joshua and Billinge, Simon and Buonassisi, Tonio and Foster, Ian and Gomes, Carla P. and Gregoire, John M. and Mehta, Apurva and Montoya, Joseph and Olivetti, Elsa and Park, Chiwoo and Rotenberg, Eli and Saikin, Semion K. and Smullin, Sylvia and Stanev, Valentin and Maruyama, Benji (2021) Autonomous experimentation systems for materials development: A community perspective. Matter, 4 (9). pp. 2702-2726. ISSN 2590-2385. doi:10.1016/j.matt.2021.06.036. https://resolver.caltech.edu/CaltechAUTHORS:20210729-223028773
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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.
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| 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. | ||||||||||||||||||||||||||||
| Group: | JCAP | ||||||||||||||||||||||||||||
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| Subject Keywords: | autonomy; artificial intelligence; machine learning; algorithmic development; research methods; human-machine teaming; workforce development; materials discovery; carbon nanotubes; additive manufacturing | ||||||||||||||||||||||||||||
| Issue or Number: | 9 | ||||||||||||||||||||||||||||
| DOI: | 10.1016/j.matt.2021.06.036 | ||||||||||||||||||||||||||||
| Record Number: | CaltechAUTHORS:20210729-223028773 | ||||||||||||||||||||||||||||
| Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20210729-223028773 | ||||||||||||||||||||||||||||
| Official Citation: | Eric Stach, Brian DeCost, A. Gilad Kusne, Jason Hattrick-Simpers, Keith A. Brown, Kristofer G. Reyes, Joshua Schrier, Simon Billinge, Tonio Buonassisi, Ian Foster, Carla P. Gomes, John M. Gregoire, Apurva Mehta, Joseph Montoya, Elsa Olivetti, Chiwoo Park, Eli Rotenberg, Semion K. Saikin, Sylvia Smullin, Valentin Stanev, Benji Maruyama, Autonomous experimentation systems for materials development: A community perspective, Matter, Volume 4, Issue 9, 2021, Pages 2702-2726, ISSN 2590-2385, https://doi.org/10.1016/j.matt.2021.06.036. (https://www.sciencedirect.com/science/article/pii/S2590238521003064) | ||||||||||||||||||||||||||||
| Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | ||||||||||||||||||||||||||||
| ID Code: | 110087 | ||||||||||||||||||||||||||||
| Collection: | CaltechAUTHORS | ||||||||||||||||||||||||||||
| Deposited By: | Tony Diaz | ||||||||||||||||||||||||||||
| Deposited On: | 02 Aug 2021 17:12 | ||||||||||||||||||||||||||||
| Last Modified: | 13 Sep 2021 20:19 |
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