A Facile Co-Deposition Approach to Construct Functionalized Graphene Quantum Dots Self-Cleaning Nanofiltration Membranes

Nanomaterials (Basel). 2021 Dec 23;12(1):41. doi: 10.3390/nano12010041.

Abstract

In this study, a novel photocatalytic self-cleaning nanofiltration (NF) membrane was fabricated by constructing aspartic acid-functionalized graphene quantum dots (AGQDs) into the polydopamine/polyethyleneimine (PDA/PEI) selective layer via the co-deposition method. The chemical composition, microstructure, and hydrophilicity of the prepared membranes were characterized by scanning electron microscopy (SEM), atomic force microscopy (AFM), attenuated total reflection (ATR-FTIR), X-ray photoelectron spectroscopy (XPS), and water contact angle (WCA). Meanwhile, the effects of PEI molecular weight and AGQDs concentration on NF membrane structures and separation performance were systematically investigated. The photocatalytic self-cleaning performance of the PDA/PEI/AGQDs membrane was evaluated in terms of flux recovery rate. For constructing high-performance NF membranes, it is found that the optimal molecular weight of PEI is 10,000 Da, and the optimal concentration of AGQDs is 2000 ppm. The introduction of hydrophilic AGQDs formed a more hydrophilic and dense selective layer during the co-deposition process. Compared with the PDA/PEI membrane, the engineered PDA/PEI/AGQDs NF membrane has enhanced water flux (55.5 LMH·bar-1) and higher rejection (99.7 ± 0.3% for MB). In addition, the PDA/PEI/AGQDs membrane exhibits better photocatalytic self-cleaning performance over the PDA/PEI membrane (83% vs. 69%). Therefore, this study provides a facile approach to construct a self-cleaning NF membrane.

Keywords: L-aspartic acid; co-deposition; graphene quantum dots; nanofiltration; self-cleaning.