M. Venkata Ratnam Meena Vangalapati K. Nagamalleswara Rao K. Ramesh Chandra

Keywords: Adsorption, Artificial neural network, Experimental design, isotherms, Kinetics, Methyl orange, MgONP-AC

Abstract

ABSTRACT. In this work, an activated carbon composite made with magnesium oxide nanoparticles (MgONP-AC) was effectively utilized for methyl orange (MO) adsorption. The effect of pH (6-10), mass of MgONP-AC (0.1-0.3 g/L), initial MO concentration (10-30 mg/L), and temperature (283-323 K) on MO removal was investigated using a central rotatable composite experimental design based on the response surface technique (RSM) at an equilibrium agitation period of 60 min. The studies predicted the optimal MO removal of 98.99% at pH 7.68, MgONP-AC dosage of 0.24 g/L, and starting MO concentration of 15 mg/L, and temperature of 313 K. Furthermore, an artificial neural network (ANN) was utilized to simulate MO adsorption, and it properly predicted MO removal using mean squared error (MSE) and R2 for the testing data. The ANN predicts a maximum removal of 99.63% with ANN with R2 = 0.9926. The kinetic results suited the pseudo-second order kinetic equation, and the data from the equilibrium investigations corresponded well with the Langmuir isotherm (maximum uptake capacity qmax = 346 mg/g). Endothermic, spontaneous, and physical adsorption were discovered during the thermodynamic investigations.

 

KEY WORDS: Adsorption, Artificial neural network, Experimental design, isotherms, Kinetics, Methyl orange, MgONP-AC

 

Bull. Chem. Soc. Ethiop. 2022, 36(3), 531-544.                                                               

DOI: https://dx.doi.org/10.4314/bcse.v36i3.4