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AI-driven robotic chemist for autonomous synthesis of organic molecules

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 harness...

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Detalles Bibliográficos
Autores principales: Ha, Taesin, Lee, Dongseon, Kwon, Youngchun, Park, Min Sik, Lee, Sangyoon, Jang, Jaejun, Choi, Byungkwon, Jeon, Hyunjeong, Kim, Jeonghun, Choi, Hyundo, Seo, Hyung-Tae, Choi, Wonje, Hong, Wooram, Park, Young Jin, Jang, Junwon, Cho, Joonkee, Kim, Bosung, Kwon, Hyukju, Kim, Gahee, Oh, Won Seok, Kim, Jin Woo, Choi, Joonhyuk, Min, Minsik, Jeon, Aram, Jung, Yongsik, Kim, Eunji, Lee, Hyosug, Choi, Youn-Suk
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10619927/
https://www.ncbi.nlm.nih.gov/pubmed/37910607
http://dx.doi.org/10.1126/sciadv.adj0461
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author Ha, Taesin
Lee, Dongseon
Kwon, Youngchun
Park, Min Sik
Lee, Sangyoon
Jang, Jaejun
Choi, Byungkwon
Jeon, Hyunjeong
Kim, Jeonghun
Choi, Hyundo
Seo, Hyung-Tae
Choi, Wonje
Hong, Wooram
Park, Young Jin
Jang, Junwon
Cho, Joonkee
Kim, Bosung
Kwon, Hyukju
Kim, Gahee
Oh, Won Seok
Kim, Jin Woo
Choi, Joonhyuk
Min, Minsik
Jeon, Aram
Jung, Yongsik
Kim, Eunji
Lee, Hyosug
Choi, Youn-Suk
author_facet Ha, Taesin
Lee, Dongseon
Kwon, Youngchun
Park, Min Sik
Lee, Sangyoon
Jang, Jaejun
Choi, Byungkwon
Jeon, Hyunjeong
Kim, Jeonghun
Choi, Hyundo
Seo, Hyung-Tae
Choi, Wonje
Hong, Wooram
Park, Young Jin
Jang, Junwon
Cho, Joonkee
Kim, Bosung
Kwon, Hyukju
Kim, Gahee
Oh, Won Seok
Kim, Jin Woo
Choi, Joonhyuk
Min, Minsik
Jeon, Aram
Jung, Yongsik
Kim, Eunji
Lee, Hyosug
Choi, Youn-Suk
author_sort Ha, Taesin
collection PubMed
description 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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spelling pubmed-106199272023-11-02 AI-driven robotic chemist for autonomous synthesis of organic molecules Ha, Taesin Lee, Dongseon Kwon, Youngchun Park, Min Sik Lee, Sangyoon Jang, Jaejun Choi, Byungkwon Jeon, Hyunjeong Kim, Jeonghun Choi, Hyundo Seo, Hyung-Tae Choi, Wonje Hong, Wooram Park, Young Jin Jang, Junwon Cho, Joonkee Kim, Bosung Kwon, Hyukju Kim, Gahee Oh, Won Seok Kim, Jin Woo Choi, Joonhyuk Min, Minsik Jeon, Aram Jung, Yongsik Kim, Eunji Lee, Hyosug Choi, Youn-Suk Sci Adv Physical and Materials Sciences 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. American Association for the Advancement of Science 2023-11-01 /pmc/articles/PMC10619927/ /pubmed/37910607 http://dx.doi.org/10.1126/sciadv.adj0461 Text en Copyright © 2023 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY). https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution license (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Physical and Materials Sciences
Ha, Taesin
Lee, Dongseon
Kwon, Youngchun
Park, Min Sik
Lee, Sangyoon
Jang, Jaejun
Choi, Byungkwon
Jeon, Hyunjeong
Kim, Jeonghun
Choi, Hyundo
Seo, Hyung-Tae
Choi, Wonje
Hong, Wooram
Park, Young Jin
Jang, Junwon
Cho, Joonkee
Kim, Bosung
Kwon, Hyukju
Kim, Gahee
Oh, Won Seok
Kim, Jin Woo
Choi, Joonhyuk
Min, Minsik
Jeon, Aram
Jung, Yongsik
Kim, Eunji
Lee, Hyosug
Choi, Youn-Suk
AI-driven robotic chemist for autonomous synthesis of organic molecules
title AI-driven robotic chemist for autonomous synthesis of organic molecules
title_full AI-driven robotic chemist for autonomous synthesis of organic molecules
title_fullStr AI-driven robotic chemist for autonomous synthesis of organic molecules
title_full_unstemmed AI-driven robotic chemist for autonomous synthesis of organic molecules
title_short AI-driven robotic chemist for autonomous synthesis of organic molecules
title_sort ai-driven robotic chemist for autonomous synthesis of organic molecules
topic Physical and Materials Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10619927/
https://www.ncbi.nlm.nih.gov/pubmed/37910607
http://dx.doi.org/10.1126/sciadv.adj0461
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