Characterization of axial dispersion in a vertical helical coil for gas–liquid–liquid flow at low Reynolds numbers. Issue 5 (16th February 2022)

• Record Type: Journal Article
• Authors: Khan, Muzammil; Joshi, Sunil; Ranade, Vivek
• Is Part Of: Reaction chemistry & engineering. Volume 7:Issue 5(2022)
• Page Start: 1083
• Page End: 1095
• Publication Date: 2022-02-16
• Subjects: Reaction mechanisms (Chemistry) -- Periodicals; Chemical engineering -- Periodicals; Chemical engineering; Reaction mechanisms (Chemistry); Periodicals; 547.705
• DOI: 10.1039/d1re00309g
• Languages: English
• ISSNs: 2058-9883

Abstract

Abstract : The RTD of a helical coiled reactor was determined from light absorbance by the tracer step input for various cases of flows. The axial dispersion was quantified in terms of dispersion coefficients using the axial dispersion model. Abstract : Gas–liquid–liquid (GLL) slug flow reactors offer several advantages like higher interfacial area, excellent mass transfer, and lower backmixing. Mesoscale (diameter ∼ a few mm) helical coiled reactors operating in a slug flow regime can be used as GLL reactors even for reactions with long residence times. The long residence time invariably leads to low Reynolds number flows, which makes the backmixing or axial dispersion an important parameter influencing reactor performance. In this work, we have characterized the residence time distribution (RTD) and axial dispersion for single, gas–liquid, liquid–liquid, and gas–liquid–liquid flows through a vertical helical coil. Slow flows with low Reynolds numbers (<100) were considered. RTD measurements were carried out with a step input and the outlet concentration was tracked by measuring light absorbance using a spectrophotometer. The applicability of the axial dispersion model was examined and verified for the studied systems. The axial dispersion was quantified in terms of dispersion coefficients. A significant reduction in the axial dispersion was observed by virtue of multiphase operation, in the order single > gas–liquid > liquid–liquid > gas–liquid–liquid flow. This characterization of backmixing for multiphase flows in curved geometries will be helpful in the optimization of slow reactions in flow and also for processes like nanoparticle synthesis, crystallization, etc.