Self-Driving Laboratories for Chemistry and Materials Science

Лаборатории с автономным управлением для химии и материаловедения
Felix Strieth‐Kalthoff, Alán Aspuru‐Guzik, Martin Seifrid, Marta Skreta, Sergio Pablo‐García, Gary Tom, Stefan P. Schmid, Sterling G. Baird, Yang Cao, Kourosh Darvish, Han Hao, Stanley Lo, Ella Miray Rajaonson, Naruki Yoshikawa, Samantha Corapi, Gun Deniz Akkoc
2024-08-13

automated experimental workflowsautonomous experimental planningdrug discoverymaterials discoveryself-driving laboratories
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.
1
Existing real-world SDLs exhibit varying levels of automation, with domain-specific challenges and limitations.
2
SDLs have made significant contributions across drug discovery, materials science, genomics, and chemistry.
3
Self-driving laboratories combine automated experimental workflows with autonomous planning to accelerate scientific research in chemistry and materials discovery.
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The review analyzes SDL enabling technologies across hardware, software, and integration with laboratory infrastructure.
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The review assesses the potential implications of SDL adoption for both scientific research and industry.

Self-driving laboratories (SDLs) for chemistry and materials science

The state of the art, applications, enabling technologies, automation levels, and challenges of SDLs in accelerating scientific research and discovery

Publication Details
Publication Date
2024-08-13
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Authors
Felix Strieth‐Kalthoff
Alán Aspuru‐Guzik
Martin Seifrid
Marta Skreta
Sergio Pablo‐García
Gary Tom
Stefan P. Schmid
Sterling G. Baird
Yang Cao
Kourosh Darvish
Han Hao
Stanley Lo
Ella Miray Rajaonson
Naruki Yoshikawa
Samantha Corapi
Gun Deniz Akkoc
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