Suppr超能文献

基于木屑膜修饰电极的安培传感器:在百草枯电分析中的应用。

Amperometric sensors based on sawdust film modified electrodes: application to the electroanalysis of paraquat.

机构信息

Laboratoire de Chimie Analytique, Faculté des Sciences, Universite de Yaounde Université de Yaoundé I B.P. 812 Yaoundé, Cameroun.

出版信息

Talanta. 2012 Sep 15;99:478-86. doi: 10.1016/j.talanta.2012.06.013. Epub 2012 Jun 15.

Abstract

Natural or sodium hydroxide treated Ayous sawdusts were used to prepare thin film electrodes (denoted respectively as PSTFE and SSTFE). The sensors obtained exhibit good mechanical stability and a wide electrochemical potential range. Their electrochemical characterization revealed that they present a good capacity to accumulate cations, but are not useful for the electroanalysis of anions. In all cases, the signals were more intense and well defined on SSTFE compared to PSTFE. When applied to the electroanalysis of paraquat, a significant improvement of the current intensities was obtained on these electrodes compared to the bare glassy carbon electrode. The diffusion of this compound through the film which is the main process governing the electrochemical reaction at the electrode surface, is 2.2 times more important with SSTFE compared to PSTFE. After the optimization of the detection parameters, calibration curves were obtained in the concentration range 0.1-0.725 μmol L(-1) for PSTFE and 0.05-0.6 μmol L(-1) for SSTFE. The detection limits determined for a signal/noise ratio=3 are 5.49×10(-9) mol L(-1) for PSTFE and 3.02×10(-9) mol L(-1) for SSTFE.

摘要

天然或氢氧化钠处理的奥古曼锯末被用于制备薄膜电极(分别表示为 PSTFE 和 SSTFE)。所获得的传感器具有良好的机械稳定性和宽的电化学电位范围。它们的电化学特性表明,它们具有良好的阳离子积累能力,但对于阴离子的电化学分析则没有用。在所有情况下,与 PSTFE 相比,SSTFE 上的信号更强烈且更清晰。当应用于百草枯的电化学分析时,与裸玻碳电极相比,这些电极的电流强度得到了显著提高。该化合物通过薄膜的扩散是控制电极表面电化学反应的主要过程,与 PSTFE 相比,SSTFE 中的扩散重要 2.2 倍。在优化检测参数后,对于 PSTFE,在 0.1-0.725 μmol L(-1)的浓度范围内获得了校准曲线,对于 SSTFE,在 0.05-0.6 μmol L(-1)的浓度范围内获得了校准曲线。信噪比为 3 时确定的检测限对于 PSTFE 为 5.49×10(-9) mol L(-1),对于 SSTFE 为 3.02×10(-9) mol L(-1)。

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