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Parallel multi-droplet platform for reaction kinetics and optimization
We present an automated droplet reactor platform possessing parallel reactor channels and a scheduling algorithm that orchestrates all of the parallel hardware operations and ensures droplet integrity as well as overall efficiency. We design and incorporate all of the necessary hardware and software...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society of Chemistry
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10445457/ https://www.ncbi.nlm.nih.gov/pubmed/37621435 http://dx.doi.org/10.1039/d3sc02082g |
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author | Eyke, Natalie S. Schneider, Timo N. Jin, Brooke Hart, Travis Monfette, Sebastien Hawkins, Joel M. Morse, Peter D. Howard, Roger M. Pfisterer, David M. Nandiwale, Kakasaheb Y. Jensen, Klavs F. |
author_facet | Eyke, Natalie S. Schneider, Timo N. Jin, Brooke Hart, Travis Monfette, Sebastien Hawkins, Joel M. Morse, Peter D. Howard, Roger M. Pfisterer, David M. Nandiwale, Kakasaheb Y. Jensen, Klavs F. |
author_sort | Eyke, Natalie S. |
collection | PubMed |
description | We present an automated droplet reactor platform possessing parallel reactor channels and a scheduling algorithm that orchestrates all of the parallel hardware operations and ensures droplet integrity as well as overall efficiency. We design and incorporate all of the necessary hardware and software to enable the platform to be used to study both thermal and photochemical reactions. We incorporate a Bayesian optimization algorithm into the control software to enable reaction optimization over both categorical and continuous variables. We demonstrate the capabilities of both the preliminary single-channel and parallelized versions of the platform using a series of model thermal and photochemical reactions. We conduct a series of reaction optimization campaigns and demonstrate rapid acquisition of the data necessary to determine reaction kinetics. The platform is flexible in terms of use case: it can be used either to investigate reaction kinetics or to perform reaction optimization over a wide range of chemical domains. |
format | Online Article Text |
id | pubmed-10445457 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The Royal Society of Chemistry |
record_format | MEDLINE/PubMed |
spelling | pubmed-104454572023-08-24 Parallel multi-droplet platform for reaction kinetics and optimization Eyke, Natalie S. Schneider, Timo N. Jin, Brooke Hart, Travis Monfette, Sebastien Hawkins, Joel M. Morse, Peter D. Howard, Roger M. Pfisterer, David M. Nandiwale, Kakasaheb Y. Jensen, Klavs F. Chem Sci Chemistry We present an automated droplet reactor platform possessing parallel reactor channels and a scheduling algorithm that orchestrates all of the parallel hardware operations and ensures droplet integrity as well as overall efficiency. We design and incorporate all of the necessary hardware and software to enable the platform to be used to study both thermal and photochemical reactions. We incorporate a Bayesian optimization algorithm into the control software to enable reaction optimization over both categorical and continuous variables. We demonstrate the capabilities of both the preliminary single-channel and parallelized versions of the platform using a series of model thermal and photochemical reactions. We conduct a series of reaction optimization campaigns and demonstrate rapid acquisition of the data necessary to determine reaction kinetics. The platform is flexible in terms of use case: it can be used either to investigate reaction kinetics or to perform reaction optimization over a wide range of chemical domains. The Royal Society of Chemistry 2023-08-04 /pmc/articles/PMC10445457/ /pubmed/37621435 http://dx.doi.org/10.1039/d3sc02082g Text en This journal is © The Royal Society of Chemistry https://creativecommons.org/licenses/by/3.0/ |
spellingShingle | Chemistry Eyke, Natalie S. Schneider, Timo N. Jin, Brooke Hart, Travis Monfette, Sebastien Hawkins, Joel M. Morse, Peter D. Howard, Roger M. Pfisterer, David M. Nandiwale, Kakasaheb Y. Jensen, Klavs F. Parallel multi-droplet platform for reaction kinetics and optimization |
title | Parallel multi-droplet platform for reaction kinetics and optimization |
title_full | Parallel multi-droplet platform for reaction kinetics and optimization |
title_fullStr | Parallel multi-droplet platform for reaction kinetics and optimization |
title_full_unstemmed | Parallel multi-droplet platform for reaction kinetics and optimization |
title_short | Parallel multi-droplet platform for reaction kinetics and optimization |
title_sort | parallel multi-droplet platform for reaction kinetics and optimization |
topic | Chemistry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10445457/ https://www.ncbi.nlm.nih.gov/pubmed/37621435 http://dx.doi.org/10.1039/d3sc02082g |
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