Modeling of Adsorption of Methylene Blue Dye on Ho-CaWO4 Nanoparticles using Response Surface Methodology (RSM) and Artificial Neural Network (ANN) Techniques

Publication date: Available online 19 July 2019Source: MethodsXAuthor(s): Chinenye Adaobi Igwegbe, Leili Mohmmadi, Shahin Ahmadi, Abbas Rahdar, Danial Khadkhodaiy, Rahmin Dehghani, Somayeh RahdarAbstractThe aim of this study is to evaluate the applicability of Ho-CaWO4 nanoparticles prepared using the hydrothermal method for the removal of Methylene blue (MB) from aqueous solution using adsorption process. The effects of contact time, Ho-CaWO4 nanoparticles dose and initial MB concentrationon the removal of MB were studied using the central composite design (CCD) method. Response surface methodology (RSM) and Artificial neural network (ANN) modeling techniques were applied to model the process and their performance and predictive capabilities of the response (removal efficiency) was also examined. The adsorption process was optimized using the RSM and the optimum conditions were determined. The process was also modelled using the adsorption isotherm and kinetic models. The ANN and RSM model showed adequate prediction of the response, with absolute average deviation (AAD) of 0.001 and 0.320 and root mean squared error (RMSE) of 0.119 and 0.993, respectively. The RSM model was found to be more acceptable since it has the lowest RMSE and AAD compared to the ANN model. Optimum MB removal of 71.17% was obtained at pH of 2.03, contact time of 15.16 min,Ho-CaWO4 nanoparticles dose of 1.91 g/L, and MB concentration of 100.65 mg/L. Maximum adsorption capacity (qm) of 103.09 mg...
Source: MethodsX - Category: Science Source Type: research