Suppr超能文献

基于 TiC/Ni/Sm 的电化学葡萄糖传感器,用于使用双极电化学进行汗液分析。

TiC/Ni/Sm-based electrochemical glucose sensor for sweat analysis using bipolar electrochemistry.

机构信息

Center of Excellence in Electrochemistry, School of Chemistry, College of Science, University of Tehran, Tehran, 1439817435, Iran.

Nanobiosensors Lab, Department of Life Science Engineering, Faculty of New Sciences & Technologies, University of Tehran, Tehran, 1439817435, Iran.

出版信息

Mikrochim Acta. 2024 Feb 15;191(3):137. doi: 10.1007/s00604-024-06209-3.

Abstract

An innovative electrochemical sensor is introduced that utilizes bipolar electrochemistry on a paper substrate for detecting glucose in sweat. The sensor employs a three-dimensional porous nanocomposite (MXene/NiSm-LDH) formed by decorating nickel-samarium nanoparticles with double-layer MXene hydroxide. These specially designed electrodes exhibit exceptional electrocatalytic activity during glucose oxidation. The glucose sensing mechanism involves enzyme-free oxidation of the analyte within the sensor cell, achieved by applying an appropriate potential. This leads to the reduction of KFe(CN) in the reporter cell, and the resulting current serves as the response signal. By optimizing various parameters, the measurement platform enables the accurate determination of sweat glucose concentrations within a linear range of 10 to 200 µM. The limit of detection (LOD) for glucose is 3.6 µM (S/N = 3), indicating a sensitive and reliable detection capability. Real samples were analysed  to validate the sensor's efficiency, and the results obtained were both promising and encouraging.

摘要

本文介绍了一种创新性的电化学传感器,该传感器利用纸基底上的双极电化学原理来检测汗液中的葡萄糖。该传感器采用了一种由双层 MXene 氢氧化物修饰镍钐纳米粒子形成的三维多孔纳米复合材料 (MXene/NiSm-LDH)。这些经过特殊设计的电极在葡萄糖氧化过程中表现出卓越的电催化活性。葡萄糖的传感机制涉及在传感器单元内无酶氧化分析物,通过施加适当的电势来实现。这导致报告单元中的 KFe(CN) 6 3−被还原,所得电流作为响应信号。通过优化各种参数,该测量平台能够在 10 至 200 μM 的线性范围内准确测定汗液中的葡萄糖浓度。葡萄糖的检测限 (LOD) 为 3.6 μM(S/N=3),表明该传感器具有灵敏可靠的检测能力。对实际样品进行了分析以验证传感器的效率,结果令人鼓舞。

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