Iranian Journal of Chemical Engineering (IJChE)

Abstract Most of the reactions that occur in microreactors take place on the surface, so it is important to keep the reactants close to the reactive wall. One effective technique in this field is the single-phase hydrodynamic focusing. However, this method has a drawback: a high percentage of reactants penetrate into the sheath fluid. To address this issue, the concept of the two-phase hydrodynamic focusing is introduced in this study. The main idea is to use a highly viscous sheath fluid to create a barrier against reactant penetration into the sheath flow. To demonstrate the effectiveness of this method, a 3D numerical simulation was performed with an irreversible second-order reaction. The results show that the two-phase hydrodynamic focusing increases reaction rates, particularly in downstream regions where the Sherwood number can increase by several orders of magnitude with the use of a highly viscous sheath of liquids. Additionally, it was observed that the use of the two-phase hydrodynamic focusing improves the efficiency, which is defined as the ratio of the solute in the sample flow to the total solute in each cross-section..

Abstract Soil bioremediation, especially in the rhizosphere area, is the result of interaction between plant roots and microorganisms. It can be considered as one of the remarkable ways to eliminate pollutants. Various factors control the process with special relationships in the rhizosphere environment; changing each of them can impress on the system destination. With mathematical modeling, behavior of the process can be predicted and controlled, and improved by appropriate changes in the model. In this study, the effects of different parameters of a simple mathematical model, represented to predict microbial growth and necessary substrate changes in the rhizosphere have been studied using numerical finite difference method. Influences of the parameters on biomass and substrate concentrations were evaluated at different times. A number of variables directly, some negatively, and others neutrally impacted on the biomass and substrate concentrations. Investigating variables differently affecting on a model is important since perfectly tuning them can optimize the system performance, and achieve higher efficiency.