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Self-Driving Laboratories for Chemistry and Materials Science

November 5, 2024
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Chemical Reviews

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.

For details

Self-Driving Laboratories for Chemistry and Materials Science

Gary Tom 1/2/3/*, Stefan P. Schmid, Sterling G. Baird, Yang Cao, Kourosh Darvish, Han Hao, Stanley Lo, Sergio Pablo-García, Ella M. Rajaonson, Marta Skreta, Naruki Yoshikawa, Samantha Corapi, Gun Deniz Akkoc, Felix Strieth-Kalthoff 1/2/4/*, Martin Seifrid 1/2/5/, Alán Aspuru-Guzik 1/2/3/6/7/8/9/*

  1. Department of Chemistry, University of Toronto, 80 St. George St, Toronto, Ontario M5S 3H6, Canada
  2. Department of Computer Science, University of Toronto, 40 St. George St, Toronto, Ontario M5S 2E4, Canada
  3. Vector Institute for Artificial Intelligence, 661 University Ave Suite 710, Toronto, Ontario M5G 1M1, Canada
  4. School of Mathematics and Natural Sciences, University of Wuppertal, Gaußstraße 20, 42119 Wuppertal, Germany
  5. Department of Materials Science and Engineering, North Carolina State University, Raleigh, North Carolina 27695, United States of America
  6. Acceleration Consortium, 80 St. George St, Toronto, Ontario M5S 3H6, Canada
  7. Department of Chemical Engineering & Applied Chemistry, University of Toronto, Toronto, Ontario M5S 3E5, Canada
  8. Department of Materials Science & Engineering, University of Toronto, Toronto, Ontario M5S 3E4, Canada
  9. Lebovic Fellow, Canadian Institute for Advanced Research (CIFAR), 661 University Ave, Toronto, Ontario M5G 1M1, Canada

*Corresponding author

DOI: https://pubs.acs.org/doi/10.1021/acs.chemrev.4c00055

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