数字化
计算机科学
氧化剂
软件
化学家
天然产物
编码(集合论)
程序设计语言
产品(数学)
工艺工程
软件工程
过程(计算)
嵌入式系统
化学
集合(抽象数据类型)
工程类
有机化学
电信
数学
几何学
作者
S. Hessam M. Mehr,Matthew Craven,Artem I. Leonov,Graham Keenan,Leroy Cronin
出处
期刊:Science
[American Association for the Advancement of Science]
日期:2020-10-02
卷期号:370 (6512): 101-108
被引量:273
标识
DOI:10.1126/science.abc2986
摘要
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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