Data-science driven autonomous process optimization

An automated closed-loop system optimizes a stereoselective Suzuki-Miyaura reaction using a machine learning algorithm that incorporates unbiased and categorical process parameters.

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Autores principales: Melodie Christensen, Lars P. E. Yunker, Folarin Adedeji, Florian Häse, Loïc M. Roch, Tobias Gensch, Gabriel dos Passos Gomes, Tara Zepel, Matthew S. Sigman, Alán Aspuru-Guzik, Jason E. Hein
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Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/fc4f62943ff64484b8d72e580bfeb7ba
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spelling oai:doaj.org-article:fc4f62943ff64484b8d72e580bfeb7ba2021-12-02T16:36:40ZData-science driven autonomous process optimization10.1038/s42004-021-00550-x2399-3669https://doaj.org/article/fc4f62943ff64484b8d72e580bfeb7ba2021-08-01T00:00:00Zhttps://doi.org/10.1038/s42004-021-00550-xhttps://doaj.org/toc/2399-3669An automated closed-loop system optimizes a stereoselective Suzuki-Miyaura reaction using a machine learning algorithm that incorporates unbiased and categorical process parameters.Melodie ChristensenLars P. E. YunkerFolarin AdedejiFlorian HäseLoïc M. RochTobias GenschGabriel dos Passos GomesTara ZepelMatthew S. SigmanAlán Aspuru-GuzikJason E. HeinNature PortfolioarticleChemistryQD1-999ENCommunications Chemistry, Vol 4, Iss 1, Pp 1-12 (2021)
institution DOAJ
collection DOAJ
language EN
topic Chemistry
QD1-999
spellingShingle Chemistry
QD1-999
Melodie Christensen
Lars P. E. Yunker
Folarin Adedeji
Florian Häse
Loïc M. Roch
Tobias Gensch
Gabriel dos Passos Gomes
Tara Zepel
Matthew S. Sigman
Alán Aspuru-Guzik
Jason E. Hein
Data-science driven autonomous process optimization
description An automated closed-loop system optimizes a stereoselective Suzuki-Miyaura reaction using a machine learning algorithm that incorporates unbiased and categorical process parameters.
format article
author Melodie Christensen
Lars P. E. Yunker
Folarin Adedeji
Florian Häse
Loïc M. Roch
Tobias Gensch
Gabriel dos Passos Gomes
Tara Zepel
Matthew S. Sigman
Alán Aspuru-Guzik
Jason E. Hein
author_facet Melodie Christensen
Lars P. E. Yunker
Folarin Adedeji
Florian Häse
Loïc M. Roch
Tobias Gensch
Gabriel dos Passos Gomes
Tara Zepel
Matthew S. Sigman
Alán Aspuru-Guzik
Jason E. Hein
author_sort Melodie Christensen
title Data-science driven autonomous process optimization
title_short Data-science driven autonomous process optimization
title_full Data-science driven autonomous process optimization
title_fullStr Data-science driven autonomous process optimization
title_full_unstemmed Data-science driven autonomous process optimization
title_sort data-science driven autonomous process optimization
publisher Nature Portfolio
publishDate 2021
url https://doaj.org/article/fc4f62943ff64484b8d72e580bfeb7ba
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