Suppr超能文献

通过分子印迹技术制备的改性铁沸石上亚甲基蓝的选择性类芬顿氧化

Selective Fenton-like oxidation of methylene blue on modified Fe-zeolites prepared via molecular imprinting technique.

作者信息

Zhang Yuanyuan, Shang Jiaobo, Song Yanqun, Rong Chuan, Wang Yinghui, Huang Wenyu, Yu Kefu

机构信息

School of Marine Sciences, Coral Reef Research Center of China, Guangxi University, Nanning 530004, China E-mail:

出版信息

Water Sci Technol. 2017 Feb;75(3-4):659-669. doi: 10.2166/wst.2016.525.

Abstract

A facile strategy to increase the selectivity of heterogeneous Fenton oxidation is investigated. The increase was reached by increasing selective adsorption of heterogeneous Fenton catalyst to a target pollutant. The heterogeneous Fenton catalyst was prepared by a two-step process. First, zeolite particles were imprinted by the target pollutant, methylene blue (MB), in their aggregations, and second, iron ions were loaded on the zeolite aggregations to form the molecule imprinted Fe-zeolites (MI-FZ) Fenton catalyst. Its adsorption amount for MB reached as high as 44.6 mg g while the adsorption amount of un-imprinted Fe-zeolites (FZ) is only 15.6 mg g. Fenton removal efficiency of MI-FZ for MB was 87.7%, being 33.9% higher than that of FZ. The selective Fenton oxidation of MI-FZ for MB was further confirmed by its removal performance for the mixed MB and bisphenol A (BPA) in solution. The removal efficiency of MB was 44.7% while that of BPA was only 14.9%. This fact shows that molecular imprinting is suitable to prepare the Fe-zeolites (FZ)-based Fenton catalyst with high selectivity for removal of target pollutants, at least MB.

摘要

研究了一种提高非均相芬顿氧化选择性的简便策略。通过增加非均相芬顿催化剂对目标污染物的选择性吸附来实现选择性的提高。非均相芬顿催化剂通过两步法制备。首先,在沸石颗粒的聚集体中用目标污染物亚甲基蓝(MB)进行印迹,其次,将铁离子负载在沸石聚集体上以形成分子印迹铁沸石(MI-FZ)芬顿催化剂。其对MB的吸附量高达44.6 mg/g,而未印迹的铁沸石(FZ)的吸附量仅为15.6 mg/g。MI-FZ对MB的芬顿去除效率为87.7%,比FZ高33.9%。MI-FZ对MB的选择性芬顿氧化通过其对溶液中混合的MB和双酚A(BPA)的去除性能进一步得到证实。MB的去除效率为44.7%,而BPA的去除效率仅为14.9%。这一事实表明,分子印迹适用于制备对目标污染物(至少对MB)具有高选择性的基于铁沸石(FZ)的芬顿催化剂。

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