Abstract
In this research work, artificial neural networks (ANNs) were applied to model the sorption of dyes blue No. 1 and red No. 2 in aqueous solutions using magnesium and aluminum double layer hydroxides (LDH) interspersed with nitrate ions, synthesized by coprecipitation and hydrothermal crystallization. LDHs were characterized by scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR). Kinetics and adsorption isotherms experiments were performed, experimental data revealed that adsorption kinetics fit the pseudo-second order model and adsorption isotherms at different temperatures were better adjusted by Langmuir models. The experimental results were compared with data obtained in the ANN modeling, using 4 inputs and one output variable for each dye. The correlation coefficient R2 = 0. 99 and a percentage of removal of 93% were obtained.
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The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
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Acknowledgments
The authors thank Tecnológico Nacional de México (TecNM) for financial support to carrying out this research work (project number 14482.22-P) and CONACYT for the scholarship 894711 awarded to A. Díaz Rivera.
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Díaz-Rivera, A., Zavala-Arce, R.E., García-Rivas, J.L. et al. Modeling of artificial neural networks for the adsorption of synthetic dyes in an aqueous solution using double layer hydroxides. MRS Advances 8, 77–82 (2023). https://doi.org/10.1557/s43580-023-00535-z
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DOI: https://doi.org/10.1557/s43580-023-00535-z