Preparation and performance of electrocatalytic carbon membranes for treating micro-polluted water
Source abstract
Abstract
Porous carbon membranes (PCMs) with three functions of adsorption, electrocatalytic oxidation and membrane filtration were prepared from coconut shell activated carbon using carboxymethyl cellulose (CMC, 10 wt%) and benzoxazine resin (BR, 10 wt%-40 wt%) as the binder components. The morphology and microstructure of PCMs were characterized by SEM, XRD, Raman and nitrogen adsorption. An electrocatalytic membrane reactor (ECMR) was constructed using PCMs as the anode materials to investigate their water treatment performance. Results show that the PCMs have well-developed hierarchical macro, meso and micropores, whose macropore size decreases with the particle size of the activated carbon. The mechanical strength and electrical conductivity of the PCMs increased with BR content and carbonization temperature. The water flux decreased as the average particle size of the activated carbon decreased and the iodine value decreased with decreasing BR content. The PCM performed best with an excellent comprehensive performance in adsorption, electrocatalytic oxidation and filtration when it was prepared from an activated carbon of average particle size of 37.9 μm using a BR content of 30 wt% and a carbonization temperature of 950 °C. For the micro-polluted Lingshui River water in Dalian, the removal of COD, UV254, turbidity and bacteria with the ECMR reached 94.3%, 90.5%, 96.3% and 100%, respectively, and heavy metal ions (Pb2+, Cu2+, Zn2+, Ni2+) were removed to levels below the detection limits, and the anti-fouling performance was good. The excellent performance in treating micro-polluted water is ascribed to the combined effects of adsorption, electrocatalytic oxidation and filtration.
Source: expertdata · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Membrane Separation Technologies · Membrane-based Ion Separation Techniques · Supercapacitor Materials and Fabrication
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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