查看文章

Ultrasound-supported dispersive solid-phase micro-extraction based on nano sorbent videlicet zinc hydroxide nanoparticles loaded on activated carbon (Zn (OH) 2-NPs-AC) in combination with derivative spectrophotometry method for deletion of Rhodamine B dye in industrial wastewater using response surface methodology (RSM) was the focus of the present article. Through the instrumentality of artificial neural network (ANN) and RSM, influential parameters were determined and optimized. Initial dye concentration (mg L–1), and amount of sorbent (mg), pH, and sonication time (min) as effective variables on the deletion of dye were closely examined. Initial RHB concentration of 26.5 mg L–1, Zn (OH) 2-NPs-AC amount of 0.025 g, ultrasonication time of 4 min, and pH of 4.0 provided us with the perfect removal percentages (> 100.0%). The analysis of variance and estimation of the correlation coefficient corroborated the reliability of the equation obtained by RSM considering both the predicted and experimental values of ultrasound-supported deletion of the analytes. The experimental and prognosticated values were in sound conformity. The thriving application of feed-forward neural network with a topology optimized by response surface methodology in the prediction of ultrasound-supported deletion of RHB dye by Zn (OH) 2-NPs-AC in this study, paved the way for further investigations. For ANN modeling, the number of hidden neurons, R2, MSE, the number of epochs, and error histograms were decided on. Afterwards, for fitting a model to the experimental data, Temkin, Langmuir, D–R isotherm, and Freundlich models were employed. A …