A computer vision sensor for the parallelization of actively regulated capillary slug flow microreactors
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Date
2023-09-11
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Abstract
In this work, a computer vision sensor for the extraction of slug length, slug velocity and phase ratio from capillary liquid–liquid slug flows from video feeds in real-time, including the necessary post-processing algorithms, is developed. The developed sensor is shown to be capable of simultaneously monitoring multiple capillaries and provides reasonable accuracy at less than 3.5% mean relative error. Subsequently, the sensor is used for the control of a parallelized and actively regulated dual-channel slug flow capillary microreactor setup. As a model reaction, the solvent-free epoxidation of methyl oleate with hydrogen peroxide and a phase-transfer catalyst based on tungstophosphoric acid and a quaternary ammonium salt to yield the product 9,10-epoxystearic acid methyl ester is conducted. A space–time yield of 0.679 kg L−1 h−1 is achieved.
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Keywords
Slug flow, Flow sensor, Machine learning, Video imaging, Computer vision, Epoxidation, Methyl oleate, Parallelization, Microreactor