BIOADSORPTIVE BEHAVIOUR OF Cyperus rotundusTOWARDS ALUMINUM EXTRACTION: COMPREHENSIVE ISOTHERM-KINETICS, THERMODYNAMICAN ALYSIS AND ANN, SVM, GPR PREDICTION
Excessive aluminium concentrations in drinking water have detrimental effects on human health and aquaticecosystems. While innovative chemical-based methods for aluminium extraction exist, they can be costly. Therefore, a more sustainable approach involves utilising readily available plant materials for aluminium removal. This studyinvestigates the bioadsorption of aluminium using biomass from Cyperus rotundus roots (CRR), considering variousparameters such as pH, biomass quantity, contact time, initial aluminium concentration, and temperature. Thebioadsorption process exhibited an efficiency of up to 97.99% under optimal conditions, including pH6, 3gbiomass, 90 minutes of contact, and a temperature of 25°C with agitation at 150 rpm. The adsorption process isfound to be spontaneous, feasible, and exothermic. Batch adsorption experiments follow the Fritz-Schlunder (five- parameter) isotherm and pseudo-first-order kinetic model. Monolayer adsorption capacities are determinedas148.03 mg/g. Predictive models using Artificial Neural Network (ANN), Support Vector Machine (SVM) andGaussian Process Regression (GPR) are developed, demonstrating strong abilities in forecasting aluminiumremoval percentages. The performance of ANN, SVM and GPR models is evaluated through statistical methods such as R2 and MSE, with GPR outperforming ANN and SVM in prediction accuracy. For future applications of CRRbioadsorbents in industrial settings, comprehensive research is recommended, particularly involving real wastewater samples containing aluminium and/or other heavy metals.
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