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The use of banana peel as a sustainable and low-cost precursor for the fabrication of effective biochar was exploited. Here, calcined magnetic biochar (CMB) was fabricated and characterized. CMB possesses surface acidic functional groups (–OH and COO−), porous structures, high saturation magnetization (39.55 emu/g), and larger surface area than the non-magnetic biochar (CB). The CMB adsorption performance (72.8, 75.9, and 83.4 mg/g for Zn2+, Cu2+, and Hg2+, respectively at pH 6) in a single component was described suitably by pseudo-second order kinetic model, Langmuir, and Redlich-Peterson adsorption isotherms. Notably, the selectivity factor values in the extended Langmuir isotherm indicated that CMB has higher adsorption affinity toward Hg2+ than Cu2+ and Zn2+ in the multi-component system. Owing to its high adsorption efficiency and fast and easy separation, the calcined magnetic biochar is considered promising and effective for the purification of heavy metal–bearing wastewater. [ABSTRACT FROM AUTHOR]

Magnetic biocomposite (MB) was fabricated by co-precipitation of palm seed-based biochar in the presence of Fe3O4particles. The MB sorption behaviour was investigated using nickel as the target pollutant. The MB characterisation revealed that its maintained micro-mesoporous character and high saturation magnetisation (65.8 Am2/kg) enable it to be separated from a solution using a magnet. The nickel removal efficiency of MB, 87% (28 mg/g), was achieved at pH 3; however, this was reduced to 45–75% (15–24 mg/g) in the presence of competing ions. The isotherms and kinetics studies revealed a monolayer interaction via a two-stepped sorption mechanism. [ABSTRACT FROM AUTHOR]

Chitosan-based magnetic nanobeads (CBN) were facilely synthesised and applied for selective recovery of boron from highly-saline wastewater. The CBN was characterised, and the results showed that the nanobeads are thermally and mechanically stable to withstand deterioration, had a saturation magnetisation of 65.25 emu/g, the surface area of 635 m 2 /g and nanobeads size of ∼2.6–3.8 nm. An artificial neural network (ANN) model and Box-Behnken design (BBD) were developed and applied to study the relative effect and significance of input variables affecting boron sorption. Under optimised conditions, 89, 78 and 70% boron removal efficiencies were recorded at pH 7.0 in distilled water, highly-saline water and boron-spiked seawater respectively. The combination of intraparticle diffusion model and pseudo-second-order rate equation was applicable to describe the sorption kinetics. [ABSTRACT FROM AUTHOR]