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PHOSPHATE REMOVAL ON BIOCHAR
Abstract
Biochar can be used as an alternative and efficient adsorbent for organic and inorganic pollutants. Therefore, based on previous study in which, a biochar loaded with mixed metal oxides of iron, tin or titanium catalysts results as a by-product of levulinic esters synthesis from biomass carbohydrates, this paper aim was to test this residue as biochar for the retention of phosphate from water samples. The obtained adsorbents based on Fe2O3-SnO2 and Fe2O3-La2O3-TiO2 were characterized by FT-IR and TGA analyses. The effects of adsorbent dosage, initial concentrations of phosphate, and adsorption time were investigated. The results showed that each synthetized adsorbent was able to remove phosphate from aqueous samples with efficiency above 80%. The experimental data obtained were used to estimate the equilibrium adsorption capacity for the two adsorbents applying three machine learning methods. The results obtained were in good agreement with the experimental data indicating that Support Vector Machine has a good potential in the prediction of B-Fe2O3-SnO2 and artificial neural network model is the best for Fe2O3-La2O3-TiO2 to predict adsorption capacity..
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