Autonomous platforms for data-driven organic synthesis

被引：21

作者：

Gao, Wenhao ^{[1
]}

Raghavan, Priyanka ^{[1
]}

Coley, Connor W. ^{[1
,2
]}

机构：

[1] MIT, Dept Chem Engn, Cambridge, MA 02139 USA

[2] MIT, Dept Elect Engn & Comp Sci, Cambridge, MA 02139 USA

来源：

NATURE COMMUNICATIONS | 2022年 / 13卷 / 01期

关键词：

OPTIMIZATION;

D O I：

10.1038/s41467-022-28736-4

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Achieving autonomous multi-step synthesis of novel molecular structures in chemical discovery processes is a goal shared by many researchers. In this Comment, we discuss key considerations of what an ideal platform may look like and the apparent state of the art. While most hardware challenges can be overcome with clever engineering, other challenges will require advances in both algorithms and data curation.

引用

页数：4

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