Comparison of ultrasonic with stirrer performance for removal of sunset yellow (SY) by activated carbon prepared from wood of orange tree: Artificial neural network modeling

Abstract

The present work focused on the removal of sunset yellow (SY) dye from aqueous solution by ultrasound-assisted adsorption and stirrer by activated carbon prepared from wood of an orange tree. Also, the artificial neural network (ANN) model was used for predicting removal (%) of SY dye based on experimental data. In this study a green approach was described for the synthesis of activated carbon prepared from wood of an orange tree and usability of it for the removal of sunset yellow. This material was characterized using scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The impact of variables, including initial dye concentration (mg/L), pH, adsorbent dosage (g), sonication time (min) and temperature (°C) on SY removal were studied. Fitting the experimental equilibrium data of different isotherm models such as Langmuir, Freundlich, Temkin and Dubinin–Radushkevich models display the suitability and applicability of the Langmuir model. Analysis of experimental adsorption data by different kinetic models including pseudo-first and second order, Elovich and intraparticle diffusion models indicate the applicability of the second-order equation model. The adsorbent (0.5g) is applicable for successful removal of SY (>98%) in short time (10min) under ultrasound condition.