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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...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2023
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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. |
format | Online Article Text |
id | pubmed-10619927 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
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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