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.