Kinetics, equilibrium thermodynamics and machine learning modeling of the adsorption of acid dyes by corncob derived magnetic modified biomass

Abstract

The removal of Acid dyes (Acid Orange 52, AO-52 and Acid Red 87, AR-87) from aqueous solutions in a batch process using Magnetic modified corncob biomass (Corncob@Fe₃O₄) is reported. The effects of factors such as dyes concentrations, contact time, adsorbent dosage and temperature were investigated. The kinetics and equilibrium data were modeled appropriately while Response Surface Methodology (RSM), Artificial Neural Network (ANN) as well as multiple linear regression (MLR) based on Box–Behnkem design of experiment were used to model the combined effect of the factors. The thermodynamics parameters were obtained from van’t Hoff expression. Although all the kinetic models fitted the data, first order kinetic model best fitted the data with highest R² and lowest Reduced Chi square (χ²). The monolayer adsorption capacities from Langmuir model are 47.85 and 22.48 mg/g for AO-52 and AR-87 respectively. The thermodynamic parameters obtained showed that the process is spontaneously feasible and entropy driven. Statistical evaluation showed that the process is well modeled in the order of ANN > RSM > MLR for AO-52 and MLR > ANN > RSM for AO-87. The study showed that magnetic modified corncob biomass is effective and competed favorably with other adsorbents for the adsorption of AO-52 and AO-87 dyes from aqueous solution.

Keywords:

• ANN
• AO-52
• AO-87
• corncob
• isotherm
• kinetics
• magnetic
• MLR
• RSM
• thermodynamic

Disclosure statement

No potential conflict of interest was reported by the authors.