Computer vision for understanding catalyst degradation kinetics

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Yan, Chunhui and Cowie, Megan and Howcutt, Calum and Wheelhouse, Katherine and Hodnett, Neil and Kollie, Martin and Gildea, Martin and Goodfellow, Martin H. and Reid, Marc (2022) Computer vision for understanding catalyst degradation kinetics. Preprint / Working Paper. ChemRxiv, Cambridge. (https://doi.org/10.26434/chemrxiv-2022-n0wf3)

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Abstract

We report a computer vision strategy for the extraction and colorimetric analysis of catalyst degradation and product formation kinetics from video footage. The degradation of palladium(II) pre-catalyst systems to form 'Pd black' is investigated as a widely relevant case study for catalysis and materials chemistries. Beyond the study of catalysts in isolation, investigation of Pd-catalyzed Miyaura borylation reactions revealed informative correlations between colour parameters (most notably ΔE, a colour-agnostic measure of contrast change) and the concentration of product measured by off-line analysis (NMR and LC-MS). The breakdown of such correlations helped inform conditions under which reaction vessels were compromised by air ingress. These findings present opportunities to expand the toolbox of non-invasive analytical techniques, operationally cheaper and simpler to implement than common spectroscopic methods. The approach introduces the capability of analyzing the macroscopic 'bulk' for the study of reaction kinetics in complex mixtures, in complement to the more common study of microscopic and molecular specifics.

ORCID iDs

Yan, Chunhui, Cowie, Megan, Howcutt, Calum, Wheelhouse, Katherine, Hodnett, Neil, Kollie, Martin, Gildea, Martin, Goodfellow, Martin H. ORCID logoORCID: https://orcid.org/0000-0003-2151-8442 and Reid, Marc ORCID logoORCID: https://orcid.org/0000-0003-4394-3132;
CORE (COnnecting REpositories)