Suppr超能文献

使用负载多壁碳纳米管的中空纤维进行固相微萃取后,采用气相色谱法测定水和烟熏米样品中的多环芳烃。

Gas chromatographic determination of polycyclic aromatic hydrocarbons in water and smoked rice samples after solid-phase microextraction using multiwalled carbon nanotube loaded hollow fiber.

作者信息

Matin Amir Abbas, Biparva Pourya, Gheshlaghi Mohammad

机构信息

Department of Chemistry, Faculty of Sciences, Azarbijan Shahid Madani University, 53714-161 Tabriz, Iran.

Department of Basic Sciences, Sari Agricultural Sciences and Natural Resources University, Sari, Iran.

出版信息

J Chromatogr A. 2014 Dec 29;1374:50-57. doi: 10.1016/j.chroma.2014.11.048. Epub 2014 Nov 26.

Abstract

A novel solid-phase microextraction fiber was prepared based on multiwalled carbon nanotubes (MWCNTs) loaded on hollow fiber membrane pores. Stainless steel wire was used as unbreakable support. The major advantages of the proposed fiber are its (a) high reproducibility due to the uniform structure of the hollow fiber membranes, (b) high extraction capacity related to the porous structure of the hollow fiber and outstanding adsorptive characteristics of MWCNTs. The proposed fiber was applied for the microextraction of five representative polycyclic aromatic hydrocarbons (PAHs) from aqueous media (river and hubble-bubble water) and smoked rice samples followed by gas chromatographic determination. Analytical merits of the method, including high correlation coefficients [(0.9963-0.9992) and (0.9982-0.9999)] and low detection limits [(9.0-13.0ngL(-1)) and (40.0-150.0ngkg(-1))] for water and rice samples, respectively, made the proposed method suitable for the ultra-trace determination of PAHs.

摘要

基于负载在中空纤维膜孔上的多壁碳纳米管(MWCNTs)制备了一种新型固相微萃取纤维。以不锈钢丝作为不可折断的支撑体。所提出的纤维的主要优点包括:(a)由于中空纤维膜结构均匀,具有高重现性;(b)与中空纤维的多孔结构以及多壁碳纳米管出色的吸附特性相关,具有高萃取能力。将所提出的纤维应用于从水介质(河水和泡泡水)和烟熏大米样品中微萃取五种代表性多环芳烃(PAHs),随后进行气相色谱测定。该方法的分析优点包括水和大米样品分别具有高相关系数[(0.9963 - 0.9992)和(0.9982 - 0.9999)]以及低检测限[(9.0 - 13.0 ngL⁻¹)和(40.0 - 150.0 ngkg⁻¹)],这使得所提出的方法适用于多环芳烃的超痕量测定。

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