Model of adsorption of toluene by activated carbon in rotating packed bed: Contribution ratio analysis

Adsorption emerges as an effective method for treating gases contained toluene with low concentrations and high volumes. Rotating packed bed (RPB) has been suggested to enhance this process by introducing centrifugal force. To elucidate the intricate interactions between toluene gas and activated carbon, empirical model and artificial neural network (ANN) model were developed to elucidate the performance characteristics of toluene adsorption in the RPB and contribution ratio of factors, especially considering the adsorbent property of packing density, particle size, and carbon tetrachloride adsorption rate. The empirical model primarily comprised a mass transfer model and an adsorption equilibrium model. The ANN model incorporated various types and algorithms. Subsequently, with the super performance, the ANN model was employed to simulate the influence of adsorbent property, rotational speed, inlet toluene concentration, and gas velocity on adsorption capacity in RPB. To assess the relative impact of each factor, a contribution analysis was conducted.