Microfluidic Wearable Electrochemical Sensor Based on MOF-Derived Hexagonal Rod-Shaped Porous Carbon for Sweat Metabolite and Electrolyte Analysis

化学 电解质 微流控 多孔性 电化学 六方晶系 碳纤维 代谢物 纳米技术 化学工程 可穿戴计算机 电化学气体传感器 电极 有机化学 结晶学 物理化学 复合材料 生物化学 复合数 工程类 计算机科学 嵌入式系统 材料科学
作者
Ziyi Mi,Youyuan Xia,Huo Dong,Yuhang Shen,Ziyou Feng,Yawen Hong,Haoyu Zhu,Binfeng Yin,Zhengping Ji,Qin Xu,Xiaoya Hu,Yun Shu
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:96 (42): 16676-16685 被引量:21
标识
DOI:10.1021/acs.analchem.4c02950
摘要

Wearable sensors enable the noninvasive continuous analysis of biofluid, which is of great importance for healthcare monitoring. In this work, a wearable sensor was seamlessly integrated with a microfluidic chip which was prepared by a three-dimensional printing technology for noninvasive and multiplexed analysis of metabolite and electrolytes in human sweat. The microfluidic chip could enable rapid sampling of sweat, which avoids the sweat evaporation and contamination. Using a Zn metal-organic framework as a sacrificial template, the hexagonal rod-shaped porous carbon nanorod (PCN) with high porosity, a large specific surface area, and excellent conductivity was synthesized and exhibited the robust electrocatalytic ability of uric acid (UA) oxidation. Therefore, the PCN-based sensor showed high sensitivity and good selectivity of UA with a wide linear range of 10-200 μM and a low detection limit of 4.13 μM. Meanwhile, the potentiometry-based ion-selective electrode was constructed for detection of pH and K+, respectively, with good sensitivity, selectivity, reproducibility, and stability. In addition, the testing under different bending states demonstrated that mechanical deformation had little effect on the electrochemical performance of the wearable sensors. Furthermore, we evaluated the utility of the wearable sensor for multiplexed real-time analysis of UA, pH, and K+ in sweat during aerobic exercise, and the effect of the amount of consumed purine-rich foods on uric acid metabolite levels in sweat and urine was further investigated. The relationship between urine UA and sweat UA was obtained. Overall, this wearable sensor enables multiple electrolyte and metabolite analysis in different noninvasive biofluids, suggesting its potential application in personalized disease prevention.
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