Adsorption of Methyl Red on porous activated carbon from agriculture waste: Characterization and response surface methodology optimization

Abstract

Activated carbon is an internationally recognized adsorbent substance that removes contaminants from industrial discharges. In this study, we evaluate the capacity of Activated carbon produced by the chemical carbonization of Rosemary root, considered agricultural waste, by using phosphoric acid as an activator to adsorb Methyl Red (MR) from aqueous solutions. To identify the optimum conditions for the carbonization process, the effects of several factors on the removal of methyl red were examined. These parameters included carbonization time, temperature, phosphoric acid concentration, and contact time, with the help of experimental design. We found that 550 °C is the optimal temperature for carbonization of rosemary root, and the concentration of H3PO4 was discovered to be 5.5 mol/l. What about the times we determined for contact time and carbonization time, which were 30 min and 120 min, respectively. The resulting Activated Carbon of Rosemary Root (ACRR) material was then characterized using XRD, FTIR, Boehm titration, SEM/EDX, RAMAN, and Zeta potential. A batch system is used to perform our adsorption. In addition to pH effects, initial MR concentration, contact time, and masse effect were examined, and all the results were confirmed via experimental design using full factorial. In the present study, 15 mg of the adsorbent exhibited an adsorption capacity of 154.53 mg/g at pH 3.25 and a temperature of 328.15 k at a concentration of dye 50 mg/l. The adsorption results of methyl red onto ACRR powder showed that the adsorption process was best correlated with Freundlich isotherm and pseudo-second-order kinetic. According to the thermodynamic study, the system is exothermic. In order to understand the activated sites presented on MR and the mechanism of adsorption, density functional theory (DFT) using the B3LYP/6-311G base was used. Furthermore, the experimental results agree with the results of the computational model.