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Linear and nonlinear regression methods for isotherm and kinetic modelling of iron ions bioadsorption using Ocimum sanctum Linn. leaves from aqueous solution
Summary
Researchers tested the ability of holy basil leaf powder to remove excess iron from water, achieving a maximum removal capacity of over 123 milligrams per gram. They compared linear and nonlinear modeling approaches and found that nonlinear regression provided more accurate predictions of the adsorption process. The study presents a low-cost, plant-based water treatment option that could be useful in developing regions where iron contamination is a concern.
Abstract Iron concentration in drinking water higher than the recommended value imposes different health problems. There are advanced chemical-based iron extraction techniques, in spite of having certain limitations in developing countries. Due to this, iron removal by using locally available plants is a paramount sustainable option. Therefore, the current study was intended to explore the iron removal efficiency of the powder of Ocimum sanctum Linn. (OSL) leaves from water and investigate its capability by assessing various conditions of operation. The bioadsorption equilibrium isotherm and kinetics of iron extraction onto OSL leaf powder were studied and modelled. The experimental adsorption equilibrium observations served as the basis for a comparison of linear and nonlinear regression techniques for predicting the optimal isotherms and kinetics. The optimum conditions for the extraction of iron were observed to be pH of 5, biomass concentration of 0.2 g, contact time of 2 h, speed of agitation of 150 rpm at 25 °C temperature, while maximum bioadsorption capacity was 123.26 mg/g. The batch bioadsorption of iron obeys the Fritz–Schlunde isotherm and the pseudo-first-order-kinetic model. The isotherm and kinetics parameters obtained using the nonlinear regression method outperformed the linear approach. Moreover, the potential applicability of OSL leaves-based bioadsorbent could be further examined on a large-scale for industrial application.
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