Suppr超能文献

基于离子载体的含内部水溶液的离子选择性电极的伏安离子传感,提高传感器寿命。

Voltammetric Ion Sensing with Ionophore-Based Ion-Selective Electrodes Containing Internal Aqueous Solution, Improving Lifetime of Sensors.

作者信息

Keresten Valentina, Mikhelson Konstantin

机构信息

Chemistry Institute, Saint Petersburg State University, 26 Universitetsky Prospect, 198504 Saint Petersburg, Russia.

出版信息

Membranes (Basel). 2022 Oct 27;12(11):1048. doi: 10.3390/membranes12111048.

Abstract

The possibility of voltammetric ion sensing is demonstrated, for the first time, for ion-selective electrodes (ISEs) containing an internal aqueous solution. ISEs selective to calcium, lithium and potassium ions are used as model systems. The internal solution of the ISEs contains a chloride salt of the respective cation and a ferrocenemethanol or ferrocyanide/ferricyanide redox couple. A platinum wire is used as the internal reference electrode. It is shown, theoretically and experimentally, that the dependence of oxidation and reduction peak potentials on the sample composition obeys the Nernst law, while the peak currents virtually do not depend on the sample composition. Thus, the electrode behavior is similar to that reported by Bakker's group for solid contact ISEs with ultra-thin membranes (200-300 nm). It is shown that the use of classical ISEs with relatively thick membranes (100-300 µm) and internal aqueous solution allows for the sensor lifetime of about one month. It is also shown that use of a suitable background electrolyte allows for improvement of the detection limits in voltammetric measurements with ISEs.

摘要

首次证明了对于含有内部水溶液的离子选择性电极(ISE),伏安离子传感的可能性。对钙、锂和钾离子具有选择性的ISE被用作模型系统。ISE的内部溶液包含相应阳离子的氯化物盐以及二茂铁甲醇或亚铁氰化物/铁氰化物氧化还原对。铂丝用作内部参比电极。从理论和实验上表明,氧化峰电位和还原峰电位对样品组成的依赖性遵循能斯特定律,而峰电流实际上不依赖于样品组成。因此,电极行为与Bakker小组报道的具有超薄膜(200 - 300 nm)的固体接触ISE相似。结果表明,使用具有相对较厚膜(100 - 300 µm)和内部水溶液的经典ISE可使传感器寿命约为一个月。还表明,使用合适的背景电解质可提高ISE伏安测量中的检测限。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/96f3/9699433/f09449b53f5f/membranes-12-01048-g001.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