In this work, it was studied the caffeine removal through the adsorption on granular activated carbon (CAG). The influence of pH, contact time and CAG dosage were analyzed by batch experiments. Adsorption Kinetic was studied using the models of pseudo-first-order and pseudo-second-order.
The adsorption equilibrium data was studied with Langmuir, Freundlich, and Redlich-Peterson isotherm models. The process thermodynamic also was studied. It was obtained 88 % of removal under the experimental conditions of natural pH, 60 min of adsorption and 8 g.L-1 of CAG. The
kinetic model that showed the best results was the pseudo-secondorder and Langmuir was the isotherm model that best described the adsorption behavior. The thermodynamic parameters obtained showed a spontaneous, endothermic and reversible process. The desorption efficiency also was studied
by regenerant solvents. The best results were obtained using a solvent combination of ethyl acetate, ethanol, and water (50:25:25), and it was obtained a caffeine removal of 57 %, achieving 70 % when a new solution is used in each regeneration step.
This work studied the removal of paracetamol through the adsorption process using the granular activated carbon. The results indicated that it was possible to obtain 95% of removal under the experimental conditions of pH 6, 120 min of process and 5 g L−1 of solid adsorbent. The kinetic model that best fit the experimental data was the pseudo-first order. The isotherm model that best fit the experimental data was the Sips. The thermodynamic tests indicated that the adsorption process was favorable and spontaneous and confirmed the endothermic nature of the process. In fixed bed column adsorption, the best operating condition found was obtained using the flow rate of 3 mL min−1 and bed mass equal to 0.5 g. In this case, the system presented the highest volume of treated PAR effluent, of 810 mL per gram of carbon in the bed, besides a longer rupture time and bed saturation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.