Computer vision for kinetic analysis of lab- and process-scale mixing phenomena

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Barrington, Henry and Dickinson, Alan and McGuire, Jake and Yan, Chunhui and Reid, Marc (2022) Computer vision for kinetic analysis of lab- and process-scale mixing phenomena. Organic Process Research and Development, 26 (11). pp. 3073-3088. ISSN 1083-6160 (https://doi.org/10.1021/acs.oprd.2c00216)

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Abstract

A software platform for the computer vision-enabled analysis of mixing phenomena of relevance to process scale-up is described. By bringing new and known time-resolved mixing metrics under one platform, hitherto unavailable comparisons of pixel-derived mixing metrics are exemplified across non-chemical and chemical processes. The analytical methods described are applicable using any camera and across an appreciable range of reactor scales, from development through to process scale-up. A case study in nucleophilic aromatic substitution run on a 5 L scale in a stirred tank reactor shows how camera and offline concentration analyses can be correlated. In some cases, it can be shown that camera data hold the power to predict reaction progress.

ORCID iDs

Barrington, Henry, Dickinson, Alan, McGuire, Jake, Yan, Chunhui and Reid, Marc ORCID logoORCID: https://orcid.org/0000-0003-4394-3132;
  • Item type:Article
    ID code:83278
    Dates:
    Date
    Event
    18 November 2022
    Published
    4 November 2022
    Published Online
    19 October 2022
    Accepted
    Subjects:Science > Chemistry
    Department:Faculty of Science > Pure and Applied Chemistry
    Depositing user: Pure Administrator
    Date deposited:18 Nov 2022 15:44
    Last modified:11 Nov 2024 13:40
    URI:https://strathprints.strath.ac.uk/id/eprint/83278
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