Обзорная статья

Self-Driving Laboratories for Chemistry and Materials Science

Gary TomDepartment of Chemistry, University of Toronto, 80 St. George St, Toronto, Ontario M5S 3H6, CanadaStefan P. SchmidDepartment of Chemistry and Applied Biosciences, ETH Zurich, Vladimir-Prelog-Weg 1, CH-8093 Zurich, SwitzerlandSterling G. BairdYang CaoAcceleration Consortium, 80 St. George St, Toronto, Ontario M5S 3H6, CanadaKourosh DarvishAcceleration Consortium, 80 St. George St, Toronto, Ontario M5S 3H6, CanadaHan HaoAcceleration Consortium, 80 St. George St, Toronto, Ontario M5S 3H6, CanadaStanley LoDepartment of Chemistry, University of Toronto, 80 St. George St, Toronto, Ontario M5S 3H6, CanadaSergio Pablo‐GarcíaDepartment of Chemistry, University of Toronto, 80 St. George St, Toronto, Ontario M5S 3H6, CanadaElla Miray RajaonsonDepartment of Chemistry, University of Toronto, 80 St. George St, Toronto, Ontario M5S 3H6, CanadaMarta SkretaDepartment of Computer Science, University of Toronto, 40 St. George St, Toronto, Ontario M5S 2E4, CanadaNaruki YoshikawaDepartment of Computer Science, University of Toronto, 40 St. George St, Toronto, Ontario M5S 2E4, CanadaSamantha CorapiDepartment of Chemistry, University of Toronto, 80 St. George St, Toronto, Ontario M5S 3H6, CanadaGun Deniz AkkocDepartment of Chemical and Biological Engineering, Friedrich-Alexander Universität Erlangen-Nürnberg, Egerlandstr. 3, 91058 Erlangen, GermanyFelix Strieth‐KalthoffDepartment of Chemistry, University of Toronto, 80 St. George St, Toronto, Ontario M5S 3H6, CanadaMartin SeifridDepartment of Chemistry, University of Toronto, 80 St. George St, Toronto, Ontario M5S 3H6, CanadaAlán Aspuru‐GuzikAcceleration Consortium, 80 St. George St, Toronto, Ontario M5S 3H6, Canada

2024en

ABI

Аннотация

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 scientific domains where SDLs have made significant contributions, from drug discovery and materials science to genomics and chemistry. We provide a comprehensive review of existing real-world examples of SDLs, their different levels of automation, and the challenges and limitations associated with each domain.

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Идентификаторы

DOI: 10.1021/acs.chemrev.4c00055

Цитирования и источники

Цитирований: 2Использованных источников: 0

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