Suppr超能文献

使用 MIL-53(Fe)金属有机骨架基超滤膜去除纺织废水中的微塑料和染料。

Microplastics and dye removal from textile wastewater using MIL-53 (Fe) metal-organic framework-based ultrafiltration membranes.

机构信息

School of Engineering, Edith Cowan University, Joondalup, WA, 6027, Australia.

School of Engineering, Edith Cowan University, Joondalup, WA, 6027, Australia; Mineral Recovery Research Center (MRRC), School of Engineering, Edith Cowan University, Joondalup, WA, 6027, Australia; UNESCO Centre for Membrane Science and Technology, School of Chemical Engineering, University of New South Wales, Sydney, NSW, 2052, Australia.

出版信息

Chemosphere. 2024 Sep;364:143170. doi: 10.1016/j.chemosphere.2024.143170. Epub 2024 Aug 22.

Abstract

Microplastics (MPs) and other organic matters in textile wastewater have posed a formidable challenge for treatment processes, particularly in the primary stages such as ultrafiltration (UF). UF plays a crucial role in preventing the entry of pollutants into subsequent treatment steps. However, the performance efficiency of UF membranes is compromised by the potential fouling of membrane pores by MPs, dyes and other organic pollutants such as bovine serum albumin (BSA). This study focuses on enhancing UF membrane performance, specifically its antifouling properties, through the development of high-performance membranes using MIL-53(Fe) metal-organic framework (MOF) particles (noted as MIL-53 here). Various concentrations of the MIL-53 (0.05, 0.1, 0.2, and 0.5 wt%) were integrated into the membrane structure through phase inversion process. Streaming zeta potential results confirmed the negatively charged surface of the membranes and their high hydrophilicity was validated through contact angle analysis. FTIR, SEM, EDS, and XRD confirmed the presence of MIL-53 particles on the surface of membranes. The developed membranes were tested for 24 h to assess their antifouling properties, with a subsequent 30-min hydraulic flush to measure their flux recovery ratios. Methylene Blue (MB) dye was used as a cationic dye present in textile wastewater to evaluate the efficiency of the developed membranes in dye removal and the synergistic effects of dye rejection in the presence of organic matters (i.e., MPs and BSA). Since previous studies have not fully addressed the combination of dyes and organic matter, this study thoroughly investigated the effect of particle-type foulants (MPs) and their interactions with dye (MB), as well as water soluble protein-type foulants (BSA) and their interaction with MB. The results indicated that the developed membranes exhibited higher MB rejection when the dye was present with either MP or BSA, along with improved antifouling properties. The optimised UF membrane integrated with 0.1 wt% MIL-53 demonstrated nearly 96% BSA rejection and around 86% MB rejection in the mixed foulant case (BSA-MB). The modified membrane exhibited a substantial increase in water flux from 176 L m.h to 327 L m.h. The findings of this research show the potential of iron-based MOFs in improving the performance of UF membranes and provide a platform for future studies on significant areas such as long-term stability studies and testing with other pollutants found in textile wastewater.

摘要

微塑料(MPs)和纺织废水中的其他有机物对处理过程构成了巨大挑战,尤其是在超滤(UF)等初级阶段。UF 在防止污染物进入后续处理步骤方面发挥着至关重要的作用。然而,MPs、染料和其他有机污染物(如牛血清白蛋白(BSA))可能会堵塞膜孔,从而降低 UF 膜的性能效率。本研究通过使用 MIL-53(Fe) 金属有机骨架(MOF)颗粒(这里称为 MIL-53)开发高性能膜,重点提高 UF 膜的性能,特别是其抗污染性能。通过相转化过程将不同浓度的 MIL-53(0.05、0.1、0.2 和 0.5wt%)整合到膜结构中。流动力zeta 电位结果证实了膜的带负电荷表面,通过接触角分析验证了其高亲水性。FTIR、SEM、EDS 和 XRD 证实了 MIL-53 颗粒存在于膜表面。将开发的膜进行了 24 小时测试,以评估其抗污染性能,随后进行 30 分钟水力冲洗以测量通量恢复比。亚甲蓝(MB)染料用作纺织废水中存在的阳离子染料,以评估开发的膜在染料去除方面的效率以及在存在有机物(即 MPs 和 BSA)时的染料排斥协同效应。由于以前的研究没有充分考虑染料和有机物的组合,因此本研究彻底研究了颗粒型污染物(MPs)及其与染料(MB)的相互作用,以及水溶性蛋白型污染物(BSA)及其与 MB 的相互作用。结果表明,当染料存在于 MP 或 BSA 中的任何一种时,开发的膜对 MB 的排斥率更高,同时表现出更好的抗污染性能。在混合污染物情况下(BSA-MB),添加了 0.1wt%MIL-53 的优化 UF 膜对 BSA 的排斥率接近 96%,对 MB 的排斥率约为 86%。改性膜的水通量从 176L·m-2·h-1 增加到 327L·m-2·h-1。本研究结果表明,铁基 MOFs 具有改善 UF 膜性能的潜力,为今后在长期稳定性研究和测试纺织废水中其他污染物等重要领域的研究提供了平台。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验