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Cited 51 time in webofscience Cited 54 time in scopus
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AI-driven robotic chemist for autonomous synthesis of organic moleculesopen access

Authors
Ha, TaesinLee, DongseonKwon, YoungchunPark, Min SikLee, SangyoonJang, JaejunChoi, ByungkwonJeon, HyunjeongKim, JeonghunChoi, HyundoSeo, Hyung-TaeChoi, WonjeHong, WooramPark, Young JinJang, JunwonCho, JoonkeeKim, BosungKwon, HyukjuKim, GaheeOh, Won SeokKim, Jin WooChoi, JoonhyukMin, MinsikJeon, AramJung, YongsikKim, EunjiLee, HyosugChoi, Youn-Suk
Issue Date
Nov-2023
Publisher
American Association for the Advancement of Science
Citation
Science Advances, v.9, no.44
Indexed
SCIE
SCOPUS
Journal Title
Science Advances
Volume
9
Number
44
URI
https://scholarworks.gnu.ac.kr/handle/sw.gnu/68611
DOI
10.1126/sciadv.adj0461
ISSN
2375-2548
2375-2548
Abstract
The automation of organic compound synthesis is pivotal for expediting the development of such compounds. In addition, enhancing development efficiency can be achieved by incorporating autonomous functions alongside automation. To achieve this, we developed an autonomous synthesis robot that harnesses the power of artificial intelligence (AI) and robotic technology to establish optimal synthetic recipes. Given a target molecule, our AI initially plans synthetic pathways and defines reaction conditions. It then iteratively refines these plans using feedback from the experimental robot, gradually optimizing the recipe. The system performance was validated by successfully determining synthetic recipes for three organic compounds, yielding that conversion rates that outperform existing references. Notably, this autonomous system is designed around batch reactors, making it accessible and valuable to chemists in standard laboratory settings, thereby streamlining research endeavors.
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Park, Young Jin
대학원 (기계항공우주공학부)
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