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Artificial intelligence for materials discovery

Gomes, Carla P. and Selman, Bart and Gregoire, John M. (2019) Artificial intelligence for materials discovery. MRS Bulletin, 44 (7). pp. 538-544. ISSN 0883-7694. https://resolver.caltech.edu/CaltechAUTHORS:20190801-085714793

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Abstract

Continued progress in artificial intelligence (AI) and associated demonstrations of superhuman performance have raised the expectation that AI can revolutionize scientific discovery in general and materials science specifically. We illustrate the success of machine learning (ML) algorithms in tasks ranging from machine vision to game playing and describe how existing algorithms can also be impactful in materials science, while noting key limitations for accelerating materials discovery. Issues of data scarcity and the combinatorial nature of materials spaces, which limit application of ML techniques in materials science, can be overcome by exploiting the rich scientific knowledge from physics and chemistry using additional AI techniques such as reasoning, planning, and knowledge representation. The integration of these techniques in materials-intelligent systems will enable AI governance of the scientific method and autonomous scientific discovery.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1557/mrs.2019.158DOIArticle
ORCID:
AuthorORCID
Gregoire, John M.0000-0002-2863-5265
Additional Information:© 2019 Materials Research Society. Published online by Cambridge University Press: 12 July 2019. This work was supported by an award from the Toyota Research Institute; NSF Award Nos. CCF-1522054 and CNS-0832782 (Expeditions), CNS-1059284 (Infrastructure), and IIS-1344201 (INSPIRE); ARO Award No. W911-NF-14-1-0498; AFOSR Multidisciplinary University Research Initiatives (MURI) Program FA9550-18-1-0136; and US DOE Award No. DE-SC0004993.
Group:JCAP
Funders:
Funding AgencyGrant Number
Toyota Research InstituteUNSPECIFIED
NSFCCF-1522054
NSFCNS-0832782
NSFCNS-1059284
NSFIIS-1344201
Army Research Office (ARO)W911-NF-14-1-0498
Air Force Office of Scientific Research (AFOSR)FA9550-18-1-0136
Department of Energy (DOE)DE-SC0004993
Issue or Number:7
Record Number:CaltechAUTHORS:20190801-085714793
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20190801-085714793
Official Citation:Gomes, C., Selman, B., & Gregoire, J. (2019). Artificial intelligence for materials discovery. MRS Bulletin, 44(7), 538-544. doi:10.1557/mrs.2019.158
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:97575
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:01 Aug 2019 16:05
Last Modified:03 Oct 2019 21:33

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