4.7 Article

Adsorption studies of benzophenone-3 onto clay minerals and organosilicates: Kinetics and modelling

Journal

APPLIED CLAY SCIENCE
Volume 202, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.clay.2020.105937

Keywords

Adsorption kinetics; Reaction models; Diffusion models; Organosilicates; Montmorillonite; LAPONITE (R)

Funding

  1. Ecole de Biologie Industrielle (EBI)

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This study investigated the adsorption kinetics of benzophenone-3 onto three different adsorbents in ethanol, finding that various models accurately described the adsorption process, indicating that adsorption involved multiple steps with different kinetically limiting factors.
This study is devoted to the experimental and the theoretical investigations of the adsorption kinetics of the benzophenone-3 (BZ-3) as a template molecule onto three adsorbents: lipophilic organosilicates (OSL), clay minerals LAPONITE (R) and montmorillonite (Mt) in ethanol. To elucidate the adsorption phenomena, kinetic behavior was analyzed with reaction-adsorption models in batch system such as pseudo-first-order (PFO), pseudo-second-order (PSO) and Elovich models. In the kinetic study, equilibrium was reached after 24 h and within 3 h. The adsorptive capacity was 291, 128 and 194 mg g(-1) for OSL, LAPONITE (R) and Mt., respectively. PSO model represented the experimental data with high precision for the three adsorbents. Weber-Morris (WM) model and surface diffusion adsorbed-model (SDM) were also used as mechanism models. The multilinearity shown with the WM model indicated that the adsorption phenomenon involved more than one step including surface diffusion of BZ-3 followed by pi-pi interaction between the aromatic nuclei of BZ-3 and the adsorbent. The organic molecule-adsorbent interaction was the kinetically limiting step in the case of OSL and Mt. while the surface diffusion was the kinetically limiting step in the case of LAPONITE (R). Numerical resolution of the ordinary (ODE) and partial (PDE) differential equations were determined for the PFO-PSO and SDM respectively to optimize the adsorption prediction.

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