Suppr超能文献

用于去除痕量全氟辛酸的多孔芳香骨架内独特的亲氟孔道工程

Unique fluorophilic pores engineering within porous aromatic frameworks for trace perfluorooctanoic acid removal.

作者信息

Zhang Chi, Dong Junchao, Zhang Panpan, Sun Lei, Yang Liu, Wang Wenjian, Zou Xiaoqin, Chen Yunning, Shang Qingkun, Feng Danyang, Zhu Guangshan

机构信息

Faculty of Chemistry, Northeast Normal University, Changchun130024, China.

Institute of Molecular Sciences and Engineering, Institute of Frontier and Interdisciplinary Science, Shandong University, Qingdao266237, China.

出版信息

Natl Sci Rev. 2023 Jul 10;10(10):nwad191. doi: 10.1093/nsr/nwad191. eCollection 2023 Oct.

Abstract

Perfluorooctanoic acid (PFOA), a representative of per/polyfluorinated alkyl substances, has become a persistent water pollutant of widespread concern due to its biological toxicity and refractory property. In this work, we design and synthesize two porous aromatic frameworks (PAF) of PAF-CF and PAF-CF using fluorine-containing alkyl based monomers in tetrahedral geometry. Both PAFs exhibit nanosized pores (∼1.0 nm) of high surface areas (over 800 m g) and good fluorophilicity. Remarkable adsorption capacity (˃740 mg g) and superior efficiency (˃24 g mg h) are achieved toward the removal of PFOA with 1 μg L concentration owing to unique C-F···F-C interactions. In particular, PAF-CF and PAF-CF are able to reduce the PFOA concentration in water to 37.9 ng L and 43.3 ng L, below EPA regulations (70 ng L). The reusability and high efficiency give both PAFs a great potential for sewage treatment.

摘要

全氟辛酸(PFOA)作为全氟/多氟烷基物质的代表,因其生物毒性和难降解性,已成为一种备受广泛关注的持久性水污染物。在本研究中,我们使用四面体几何结构的含氟烷基单体设计并合成了两种多孔芳香骨架材料(PAF),即PAF-CF和PAF-CF。两种PAF均呈现出纳米级孔隙(约1.0纳米)、高比表面积(超过800平方米/克)以及良好的亲氟性。由于独特的C-F···F-C相互作用,对于去除浓度为1微克/升的PFOA,两种材料展现出显著的吸附容量(超过740毫克/克)和高效性(超过24克/毫克·小时)。特别地,PAF-CF和PAF-CF能够将水中的PFOA浓度降低至37.9纳克/升和43.3纳克/升,低于美国环保署规定(70纳克/升)。可重复使用性和高效性使得这两种PAF在污水处理方面具有巨大潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34d0/10476896/2e49dc2cfaa9/nwad191fig1.jpg

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