Adsorption dynamics of Eriochrome Black dye removal using raw and ultrasonicated Pithecellobium seed biomass: ANN modeling and mechanisms

Abstract

Utilization of Ultrasonic modified Pithecellobium dulce seed biomass, proved the efficacy in Eriochrome black dye remediation. The study investigates the sorption dynamics of Eriochrome Black (EB) dye removal using raw and ultrasonicated Pithecellobium seed biomass combined with Artificial Neural Network (ANN) modeling for the elucidation of underlying mechanisms. To improve the adsorption performance, Pithecellobium dulce biomass has been subjected to ultrasonication. The characterization of modified seed adsorbent revealed the adsorptive properties of biomass for the removal process. Varying impacts of dye adsorption were studied revealing the optimal parameters to be pH of 5, temperature of 303 K, contact time of 40 min-Ultrasonicated Pithecellobium dulce (UPDB) biomass; 80 min – Raw Pithecellobium dulce biomass (RPDB), and dose of 5 g/L and 2.5 g/L for RPDB and UPDB respectively. Isotherm and Kinetic analysis revealed the Freundlich and pseudo-first order models to be best fitting for the current system. Ultrasonicated seed biomass exhibited enhanced adsorption capacity of 126.9 mg/g compared to 83.8 mg/g for raw seed biomass. Thermodynamic investigation infers the spontaneity and exothermic nature of adsorption process. The ANN model for the prediction of eriochrome black dye adsorption onto ultrasonic modified Pithecellobium dulce seed biomass exhibited better correlation coefficient of 0.9559 indicating the better prediction of trained model for dye removal process. Thus, ANN model provides a better prediction of the relation between operational factors and dye removal.

Keywords

• Ultrasonication
• Artificial Neural Network
• Pithecellobium dulce biomass
• Isotherm
• Kinetics