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Functionalized Activated Carbon Fibers by Hydrogen Peroxide and Polydopamine for Efficient Trace Lead Removal from Drinking Water

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journal contribution
posted on 2021-12-30, 21:13 authored by Qi Zuo, Hong Zheng, Pengyi Zhang, Yu Zhang
To achieve efficient and selective trace heavy metals removal from drinking water, a low-cost purification material polydopamine/activated carbon fibers (PDA/H-ACF) was successfully prepared by polymerizing dopamine on the surface of activated carbon fibers pretreated with hydrogen peroxide. The morphology, phase, surface functional groups, specific surface, and pore size distribution of the as-prepared sample were analyzed using FESEM, XPS, BET and pore size distribution test (PST), and FTIR, and orthogonal experiments were used to investigate the influences of concentration of H2O2, pretreatment time, and reflux temperature on trace lead removal. The results showed that the sample pretreated under optimized conditions could produce different pore structures, and the content of functional group −COOH obviously increased. After further modification by polydopamine, the contents of −NH–, −NH2, and −OH functional groups on the surface obviously enhanced, which were beneficial to increase adsorption site and promote trace lead removal. The effluent lead concentration decreased from initial 150 to 3.18 ppb within 5 min, meeting the requirement of NSF International Standard/American National Standard for Drinking Water Treatment Units (NSF/ANSI 53–2020) (5 ppb). The isothermal adsorption process and adsorption kinetics could be well-fitted by the Langmuir isotherm and pseudo-second-order kinetics model, indicating that the adsorption process of trace lead by PDA/H-ACF belonged to monolayer and chemical adsorption. Moreover, the as-prepared PDA/H-ACF also showed superior trace lead adsorption performance in the presence of high concentration competitive metal ions, in a wide pH range and in tap water, and therefore had good application prospect in the field of drinking water purification.

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