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Paweł Cygański, Paweł Sobieszuk and Ryszard Pohorecki

Abstract

The pressure drop in microreactors for the gas - liquid Taylor flow was measured for 4 different microreactor geometries and 3 different gas - liquid systems. The results have been compared with the existing literature correlations. A selection of the best correlations has been made.

Open access

Władysław Moniuk, Ryszard Pohorecki and Piotr Machniewski

Measurements of the absorption rate of carbon dioxide into aqueous solutions of N-methyldiethanoloamine (MDEA) and 2-ethylaminoethanol (EAE) have been carried out. On this basis a mathematical model of the performance of an absorption column operated with aqueous solution of a blend of the above amines at elevated temperatures and pressures have been proposed. The results of simulations obtained by means of this model are described. The work is a part of a wider program, aimed at the development of a new process.

Open access

Paweł Sobieszuk, Filip Ilnicki and Ryszard Pohorecki

Abstract

Gas-liquid microreactors find an increasing range of applications both in production, and for chemical analysis. The most often employed flow regime in these microreactors is Taylor flow. The rate of absorption of gases in liquids depends on gas-side and liquid-side resistances. There are several publications about liquid-side mass transfer coefficients in Taylor flow, but the data about gas-side mass transfer coefficients are practically non existent. We analysed the problem of gas-side mass transfer resistance in Taylor flow and determined conditions, in which it may influence the overall mass transfer rate. Investigations were performed using numerical simulations. The influence of the gas diffusivity, gas viscosity, channel diameter, bubble length and gas bubble velocity has been determined. It was found that in some case the mass transfer resistances in both phases are comparable and the gas-side resistance may be significant. In such cases, neglecting the gas-side coefficient may lead to errors in the experimental data interpretation.