Experimental Investigation and Proposal of Artificial Neural Network Models of Lead and Cadmium Heavy Metal Ion Removal from Water Using Porous Nanomaterials

This study used porous nanomaterials MCM-41 and SBA-15, as well their modified species, to remove lead cadmium ions from water. We X-ray diffraction (XRD), a scanning electron microscope (SEM), the Brunauer–Emmett–Teller (BET), Fourier transform infrared (FT-IR) method investigate characteristics of nanomaterials. Additionally, atomic absorption spectroscopy (AAS) measured concentration ions. The stratigraphic analysis showed samples’ isothermal shape be type IV. investigated amount, absorbent, pH changes, adsorption time parameters. observed that efficiency by synthesized samples was higher than cadmium. Mesoporous structures also displayed increased due amino group. Four testing stages were conducted determine reproducibility samples, with results showing no significant changes. As result process, structure recycled sample NH2-MCM-41 preserved. artificial neural networks (ANN) propose predictive models based on experimental results. ANN very accurate, such mean absolute error (MAE) less 2% R2 0.98.