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Whereas previous efforts reported methods to extract bulk kinetics of one reaction from one video, this new approach enables one video to capture bulk kinetics of multiple reactions running in parallel. Case studies, in and beyond well\u2010plate high throughput settings, are described. Analysis of parallel dye\u2010quenching hydroxylations, DMAP\u2010catalysed esterification, solid\u2010liquid sedimentation dynamics, metal catalyst degradation, and biologically\u2010relevant sugar\u2010mediated nitro reduction reactions have each provided insight into the scope and limitations of camera\u2010enabled high throughput kinetics as a means of widening known analytical bottlenecks in HTE for reaction discovery, mechanistic understanding, and optimisation. It is envisaged that the nature of the multi\u2010reaction time\u2010resolved datasets made available by this analytical approach will later serve a broad range of downstream efforts in machine learning approaches to exploring chemical space.<\/jats:p>","DOI":"10.1002\/anie.202413395","type":"journal-article","created":{"date-parts":[[2024,8,21]],"date-time":"2024-08-21T20:04:26Z","timestamp":1724270666000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Parallel and High Throughput Reaction Monitoring with Computer Vision"],"prefix":"10.1002","volume":"64","author":[{"given":"H.","family":"Barrington","sequence":"first","affiliation":[{"name":"Department of Pure &amp; Applied Chemistry University of Strathclyde  Glasgow UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"T. J. 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