期刊
SCIENCE
卷 370, 期 6512, 页码 101-+出版社
AMER ASSOC ADVANCEMENT SCIENCE
DOI: 10.1126/science.abc2986
关键词
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资金
- EPSRC [EP/H024107/1, EP/J00135X/1, EP/J015156/1, EP/K021966/1, EP/K023004/1, EP/L023652/1]
- ERC [670467 SMART-POM]
- Defense Advanced Research Projects Agency (DARPA)
- EPSRC [EP/J00135X/1, EP/K021966/1, EP/L023652/1, EP/S030603/1, EP/J015156/1, EP/K023004/1, EP/H024107/1, EP/S017046/1] Funding Source: UKRI
Robotic systems for chemical synthesis are growing in popularity but can be difficult to run and maintain because of the lack of a standard operating system or capacity for direct access to the literature through natural language processing. Here we show an extendable chemical execution architecture that can be populated by automatically reading the literature, leading to a universal autonomous workflow. The robotic synthesis code can be corrected in natural language without any programming knowledge and, because of the standard, is hardware independent. This chemical code can then be combined with a graph describing the hardware modules and compiled into platform-specific, low-level robotic instructions for execution. We showcase automated syntheses of 12 compounds from the literature, including the analgesic lidocaine, the Dess-Martin periodinane oxidation reagent, and the fluorinating agent AlkylFluor.
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