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Computer Vision Enables Monitoring and Kinetic Analysis of Structurally Diverse Carbon Monoxide Surrogates [machine-readable data]

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Figshare2026-02-04 更新2026-04-28 收录
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https://figshare.com/articles/dataset/Computer_Vision_Enables_Monitoring_and_Kinetic_Analysis_of_Structurally_Diverse_Carbon_Monoxide_Surrogates_machine-readable_data_/31253947
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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 ten 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 sur-rogate activation through gas-phase mass transfer to sensor capture—benchmarked against a CO balloon reference. This approach reveals a four-fold 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 con-centration. The methods presented enable rational surrogate selection and open new possibilities for the quantitative design of synthetic methodologies dependent on controlled gas release.
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2026-02-04
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