Parallel multi-droplet platform for reaction kinetics and optimization
Name
d3sc02082g.pdf
Description
Published version
Size
1.04 MB
Format
Adobe PDF
Checksum (MD5)
8a05434b4ffee9de76ca9184f64152ab
Author(s)
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
Date Issued
2023
Journal
Chemical Science
Publisher
Royal Society of Chemistry
Citation
Eyke, Natalie S, Schneider, Timo N, Jin, Brooke, Hart, Travis, Monfette, Sebastien et al. 2023. "Parallel multi-droplet platform for reaction kinetics and optimization." Chemical Science, 14 (33).
Version
Final published version
Abstract
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.
MIT Department
Massachusetts Institute of Technology. Department of Chemical Engineering
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1039/D3SC02082G
