Green synthesis of iron oxide nanoparticles for arsenic remediation in water and sludge utilization
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Iron oxide nanoparticles (IONPs) were synthesized via an affordable and environmentally friendly route using waste banana peel extract. The polyphenol-rich extract acted as a stabilizing and reducing agent resulting in formation of α-Fe2O3 with a particle size of around 60 nm. The composition, phase, morphology and size of the nanoparticles were analyzed by X-ray diffraction, field emission scanning electron microscopy, Fourier transform infrared spectroscopy, transmission electron microscopy and a Zetasizer. The efficiency of the IONPs was assessed in terms of arsenic(V) remediation from contaminated water within the range of 0.1–2.0 mg/L. Batch study showed that IONPs had a high As(V) adsorption capacity of about 2.715 mg/g at 40 °C. A statistical approach, viz. an artificial neural network, was adapted for modeling and optimization of the process parameters for achieving maximum As(V) removal efficiency. A set of 54 experimental sets were conducted and the predicted model generated showed an R2 value of 0.9971 and the corresponding mean squared error value was 0.0000601. Surface binding of the As(V) phenomenon on the green synthesized IONPs was explained on the basis of FTIR spectroscopy, X-ray photoelectron spectroscopy, X-ray fluorescence spectroscopy of the control and the As(V)-loaded IONPs.The spent adsorbent was successfully immobilized in phosphate glass matrix with an objective to provide a complete and sustainable solution for arsenic contamination.
KeywordsArsenic removal Iron oxide nanoparticle Groundwater remediation Spent adsorbent management Artificial neural network
The authors would like to acknowledge the Director, CSIR-CGCRI, India, for granting permission to carry out this research work. Author A. Majumder acknowledges the Ministry of Human Resource Development (MHRD), India, for providing the GATE fellowship.
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