Abstract
In China, both vanadium(V) and chromium(VI) are present in wastewater resulting from vanadate precipitation (AVP wastewater) and from leaching vanadium-chromium reduction slag. Addressing environmental preservation and the comprehensive utilization of metal resources necessitates the extraction and separation of V(V) and Cr(VI) from these mixed solutions. However, their separation is complicated by very similar physicochemical properties. This study establishes a method for the dynamic selective adsorption of V(V) from such mixtures. It evaluates the impact of various operating conditions in columns on dynamic adsorption behavior. This study examines the migration patterns of the mass transfer zone (MTZ) and forecasts its effective adsorption capacity through multivariate polynomial regression and a neural network (NN) model. The NN model's outcomes are notably more precise. Its analysis reveals that C (0) is the most critical factor, with Q and H following in importance. Furthermore, the dynamic properties were analyzed using two established models, Thomas and Klinkenberg, revealing that both intraparticle and liquid film diffusion influence the rates of exchange adsorption, with intraparticle diffusion being the more significant factor. Using 3 wt % sodium hydroxide as the eluent to elute V(V)-loaded resin at a flow rate of 4 mL/min resulted in a chromium concentration of less than 3 mg/L in the V(V) eluate, indicating high vanadium-chromium separation efficiency in this method. These findings offer theoretical insights and economic analysis data that are crucial for optimizing column operation processes.