Removal of Thymol Blue from Aqueous Solution by Natural and Modified Bentonite: Comparative Analysis of ANN and ANFIS Models for the Prediction of Removal Percentage

Document Type : Original Research Paper

Authors

1 Department of Chemical Engineering, Faculty of Engineering and Natural Sciences, University of Bursa Technical, P.O.Box 16310, Bursa, Turkey

2 Department of Chemical Engineering, Faculty of Engineering, University of Van Yüzüncü Yıl, P.O.Box 65080, Van, Turkey

3 Department of Chemistry, Faculty of Science, University of Van Yüzüncü Yıl, P.O.Box 65080, Van, Turkey

4 Department of Computer Engineering, Faculty of Engineering, University of Van Yüzüncü Yıl, P.O.Box 65080, Van, Turkey

Abstract

In this study natural bentonite (NB) and acid-thermal co-modified bentonite (MB) were utilized as adsorbents for the removal of Thymol Blue (TB) from aqueous solution. The batch adsorption experiments were conducted under different experimental conditions. The artificial neural network (ANN) and adaptive neuro fuzzy inference systems (ANFIS) were applied to estimate removal percentage (%) of TB. Mean squared error (MSE), root mean square error (RMSE) and coefficient of determination (R2) values were used to evaluate the results. In addition, the experimental data were fitted isotherm models (Langmuir, Freundlich and Temkin) and kinetic models (pseudo first order (PFO), pseudo second order (PSO) and intra-particle diffusion (IPD)). The adsorption of TB on both the NB and MB followed well the PSO kinetic model, and was best suited Langmuir isotherm model. When the temperature was increased from 298 K to 323 K for 20 mg/L of TB initial concentration, the removal percentage of TB onto the NB and MB increased from 74.91% to 84.07% and 81.19% to 93.12%, respectively. This results were confirmed by the positive ΔH° values indicated that the removal process was endothermic for both the NB and MB. The maximum adsorption capacity was found as 48.7805 mg/g and 117.6471 mg/g for the NB and MB, respectively (at 323 K). As a result, with high surface area and adsorption capacity, the MB is a great candidate for TB dye removal from wastewater, and the ANFIS model is better than the ANN model at estimating the removal percentage of the dye.

Keywords

References

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Pollution
Volume 7, Issue 4
October 2021
Pages 959-980

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