Computer vision enables monitoring and kinetic analysis of structurally diverse carbon monoxide surrogates

Donnachie, Kristin and Griffin, Ciaran and Gray, Morven L. and McCabe, Timothy J.D. and Reid, Marc (2026) Computer vision enables monitoring and kinetic analysis of structurally diverse carbon monoxide surrogates. Angewandte Chemie International Edition. e8888536. ISSN 1521-3773 (https://doi.org/10.1002/anie.8888536)

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Abstract

Carbon monoxide (CO) surrogates are valuable synthetic reagents that circumvent the hazards of handling CO gas directly. However, owing to the structural diversity of available surrogates, their varied triggering conditions, and the requirement for sealed reactor systems, quantitative understanding of their CO release kinetics has remained elusive. Here, we report a non-contact computer vision method for monitoring and comparing vessel-specific CO release from 10 structurally diverse surrogates in two-chamber COware reactors. By tracking the colorimetric response of a ruthenium-based chemosensor, we establish a scoring system based on cumulative CO flux-from surrogate activation through gas-phase mass transfer to sensor capture-benchmarked against a CO balloon reference. This approach reveals a fourfold range in surrogate reactivity scores and enables systematic investigation of how reaction parameters such as base strength, solvent polarity, and stirring rate modulate CO release kinetics. We demonstrate that these kinetic differences translate directly to carbonylation reaction outcomes: in Pd-catalyzed Suzuki-Miyaura carbonylation, surrogate score correlates linearly with product conversion, consistent with an inverse dependence on CO concentration. The methods presented enable rational surrogate selection and open new possibilities for the quantitative design of synthetic methodologies dependent on controlled gas release.

ORCID iDs

Donnachie, Kristin, Griffin, Ciaran, Gray, Morven L., McCabe, Timothy J.D. ORCID logoORCID: https://orcid.org/0009-0002-2524-0513 and Reid, Marc ORCID logoORCID: https://orcid.org/0000-0003-4394-3132;