Time-Dependent 2-D Model for Transport of Species Analysis in Electrodialysis: Concentration Profiles and Fluxes

Time-Dependent 2-D Model for Transport of Species Analysis in Electrodialysis: Concentration Profiles and Fluxes

Electrodialysis (ED) is a separation process that uses an electric field to selectively transport ions through ion exchange membranes. In recent decades, ED has gained increasing relevance in various industrial applications, such as treatment of liquid effluents and water desalination [1,2]. To further advance the technology and bring it to an industrial scale, modeling ED and investigating the fundamental phenomena have become critical. The aim of this work, therefore, is to provide further understanding of the transport of species in ED focused in the analysis of concentration profiles and fluxes. A 2-D computational time-dependent model was developed in COMSOL Multiphysics. Results highlighted electromigration as the main transport mechanism. In addition, a non-stationary model was developed to evaluate concentration profiles along the lengths within the concentrate and diluate channel. The analysis of the concentration profiles revealed that the ion concentration values varied depending on the location. Upon comparing the ion concentration values at half of the diluate channel's length with those at three quarters of the channel's length, it was observed that the latter exhibited a 25.13% higher ion concentration as compared to the former. The lack of spacers in the geometry modeled, along with preferential ion migration, was considered a contributing factor to the uneven ionic distribution. Moreover, evidence of concentration polarization was detected, showing a significant impact on the overall ion flux. Simulations were contrasted with experimental data, taking into account the voltage drop over a single cell pair. The results from the model fitted properly the experimental data; showing small discrepancies only attributed to the presence of water transport, which was not considered in the model, but was evident in the experiments.

 

Speakers

Tamara Leon

Event Quick Information

Date
14 Nov, 2023
Time
02:50 PM - 03:10 PM