Self-Driving Laboratories for Chemistry and Materials Science
Лаборатории с автономным управлением для химии и материаловедения
2024-08-13
SCID: 54.1/nu3t3y8y
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automated experimental workflowsautonomous experimental planningdrug discoverymaterials discoveryself-driving laboratories
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Abstract (AI)
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.
Key Findings
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.
4
The review analyzes SDL enabling technologies across hardware, software, and integration with laboratory infrastructure.
5
The review assesses the potential implications of SDL adoption for both scientific research and industry.
Research Object
Self-driving laboratories (SDLs) for chemistry and materials science
Research Subject
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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