Maize cob-derived activated carbon as an adsorbent for the removal of nickel (II) cation from aqueous solution: optimization and kinetic studies

Abstract

Adsorption performance of maize cob-derived activated carbon (MCAC) for the removal of nickel (II) from solution was investigated in the present study. The MCAC was prepared by adsorbent chemical activation method. Afterwards, the MCAC was characterized and utilized as the adsorbent for batch adsorption process. Initial adsorbate concentration, contact time and adsorbent dosage were considered as the independent variables for the adsorption process. The experiments were designed based upon central composite design (CCD) of response surface methodology with the aid of Design Expert. The experimental data were fitted into a model using MATLAB regression analysis, and the developed model was later simulated to obtain the operation parameters that will give the optimum removal efficiency. The analysis of variance (ANOVA) revealed that all the considered independent process variables had significant effect on the adsorption process. The simulated response from MATLAB gave 97.113% removal efficiency of nickel (II) on experimental validation at optimum conditions of 9.75 mg/L initial nickel (II) concentration, 120 min contact time and 0.803 g adsorbent dosage. This result correlates with CCD that predicted 97.6154% nickel (II) removal efficiency. The experimental data were observed to be best fitted to pseudo-second-order kinetic model which showed that the process is chemisorption controlled. Hence, it may be concluded from the present data that MCAC is highly effective for the removal of Ni(II) from aqueous solution and the highly generated agricultural waste (Maize cob) can the easily modified as a adsorbent.

Keywords:

• Characterization
• Matlab
• Ni(II) ion
• response surface methodology

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.