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Research Article Open access CC BY 4.0

Optimized Adsorption of Pb(II) ION from Aqueous Solution Using Sharp Sand: Ann and RSM Modelling

C. I. Egwuatu, P. C. Okafor, J. O. Ndubuisi, P. C. Ezeagwu

Asian Journal of Applied Chemistry Research · pp. 1–15 · Published 4 Aug 2023

10.9734/ajacr/2023/v14i2259

Abstract

Aim: This study was aimed at using sharp sand as an adsorbent to optimize the removal of Pb ionsfrom simulated water and water obtained from Enyigba River. Study Design: Adsorption experiment was designed using Response Surface Methodology (RSM). Artificial Neural Network (ANN) was also used to predict % Pb(II)removal. Place and Duration of Study: Department Of Pure and Industrial Chemistry, Nnamdi Azikiwe University, Awka, June 2012 to June 2023. Methodology: Sharp sand was modified with salicylic acid, noted as SSM and then characterized. Experiments were carried out by varying four adsorption factors: concentration, time, pH and temperature. Adsorption experiments were also done for equilibrium isotherm, kinetics and thermodynamic studies. Results: The modified sharp sand showed a high percentage of silicon. RSM and ANN predicted the sorption of Pb(II) well with R2 values > 0.9. The optimal values for concentration, time, pH and temperature are 0.0125mg/l, 100sec, 2, 20oC respectively. Langmuir isotherm gave the better fit and adsorption was endothermic with positive ∆H. Adsorption followed second-order kinetics. FTIR analysis showed the presence of functional groups that were responsible for adsorption. Enyigba River water is slightly polluted with lead ions with concentrations higher than WHO standard. Conclusion: The adsorbent was able to remove over 70% of the metal ions from both the simulated and Enyigba River water.

Adsorption neural network kinetics optimization

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Cited by 3

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سليمة عبدالله عبجه, علي محمد الهليب, خالد عبدالمجيد سويب · Journal of Basic Sciences · 2024

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