Pyrocatechol Recovery from Aqueous Phase by Nanocellulose-Based Platelet-Shaped Gels: Response Surface Methodology and Artificial Neural Network Design Study

Abstract

The present investigation describes the feasibility of modified nanocellulose platelet-shaped gels toward recovery of pyrocatechol violet (PV) dye from aqueous solution. Batch analyses demonstrated that the dye uptake was highly influenced by different process factors which include solution pH, agitation speed, contact time, and temperature. A maximum recovery efficiency of ≥90.0% (≈180.38 mg/g) was achieved. Optimization attempts were explored via response surface methodology (RSM) and artificial neural network (ANN) models to best predict optimal removal conditions of PV dye. The effect of process variables was investigated by RSM through a three-level, four-factor central composite design matrix. The same design matrix was also applied to achieve the training set for ANN. The results of the two models, on the basis of the experimental data, were compared for their predictive accuracy in terms of coefficient of determination (R2), Chi square (χ2), and sum of squared error (SSE). Results proved that ANN design possesses higher prediction accuracy as compared with RSM. Furthermore, adsorption thermodynamics and kinetic evaluations revealed that the process was exothermic, spontaneous in nature, and was best described by a pseudo 2nd order kinetic model (R2>0.990). These environment-friendly platelet-shaped gels could be potential promising candidates for dye removal from industrial effluent.