Computer vision for non-contact monitoring of catalyst degradation and product formation kinetics

Chunhui Yan, Megan Cowie, Calum Howcutt, Katherine M. P. Wheelhouse, Neil S. Hodnett, Martin Kollie, Martin Gildea, Martin H. Goodfellow, Marc Reid*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)
20 Downloads (Pure)


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.
Original languageEnglish
Pages (from-to)5323-5331
Number of pages9
JournalChemical Science
Issue number20
Early online date7 Mar 2023
Publication statusE-pub ahead of print - 7 Mar 2023


  • computer vision
  • non-contact monitoring
  • catalyst degradation
  • product formation kinetics


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