Self-Driving Laboratories for Chemistry and Materials Science

Tom, Gary; Schmid, Stefan P.; Baird, Sterling G.; Cao, Yang; Darvish, Kourosh; Hao, Han; Lo, Stanley; Pablo‐García, Sergio; Rajaonson, Ella Miray; Skreta, Marta; Yoshikawa, Naruki; Corapi, Samantha; Akkoc, Gun Deniz; Strieth‐Kalthoff, Felix; Seifrid, Martin; Aspuru‐Guzik, Alán

doi:10.1021/acs.chemrev.4c00055

reviewChemical ReviewsAug 13, 2024BRONZE OA

Self-Driving Laboratories for Chemistry and Materials Science

GTGary Tom SPStefan P. Schmid SGSterling G. Baird YCYang Cao KDKourosh Darvish

University of Toronto · Vector Institute · +6 more institutions

PubMed

Indexed incrossrefpubmed

Abstract

Self-driving laboratories (SDLs) promise an accelerated application of the scientific method. Through the automation of experimental workflows, along with autonomous experimental planning, SDLs hold the potential to greatly accelerate research in chemistry and materials discovery. This review provides an in-depth analysis of the state-of-the-art in SDL technology, its applications across various scientific disciplines, and the potential implications for research and industry. This review additionally provides an overview of the enabling technologies for SDLs, including their hardware, software, and integration with laboratory infrastructure. Most importantly, this review explores the diverse range of…

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444

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FWCI: 74.15
Percentile: 100%
References: 691

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Authors

16

Topics & keywords

Topics

Keywords

Workflow
Automation
Chemistry
Nanotechnology
Scientific discovery
Domain (mathematical analysis)
Data science
Computer science

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