Adsorption is a widely employed separation technique valued for its low energy requirements and its applicability to diverse processes, including air separation, water purification, chromatographic analysis, wastewater treatment, and protein immobilization on biomaterials. Industrial adsorption–desorption cycles are typically carried out in parallel packed-bed columns. The accurate design and optimization of these columns rely on experimental breakthrough curves. These curves provide essential information on adsorption capacity and mass-transfer kinetics. In this study, five modelling approaches, based on instantaneous adsorption, non-instantaneous adsorption, Fickian diffusion, and anomalous diffusion, were evaluated for their ability to predict breakthrough behaviour during the adsorption of butanol on activated carbon. The first four models were formulated using conventional partial differential equations of varying complexity, whereas the fifth model incorporated anomalous diffusion through fractional-order differential equations. The results indicate that model performance depended strongly on the adsorbent type: certain models provided superior predictions for one activated carbon, while different models were more accurate for the other.
Shen et al. (Fri,) studied this question.