谷歌Chrome浏览器插件
订阅小程序
在清言上使用

Hollow nanocages heterostructured NiCo-LDH/MWCNTs electrocatalyst for highly sensitive and non-invasive detection of saliva glucose

Yuxuan Zhu,Jing Qian, Ke Xu, Wanru Ouyang,Juan Yang,Nianjun Yang

Chemical Engineering Journal(2024)

引用 0|浏览3
暂无评分
摘要
Monitoring salivary glucose has gained increased attention as a non-invasive approach to prevent and diagnose diabetes. Since the glucose concentration in saliva is lower than that in blood, the development of effective electrocatalysts for highly sensitive glucose detection is thus of great significance. In this study, a hollow nanocage from NiCo-layered double hydroxides (LDH) modified with multi-walled carbon nanotubes (MWCNTs) is designed and further employed as the sensing material to construct a novel non-enzymatic glucose electrochemical sensor with high sensitivity. It is synthesized by utilizing pre-synthesized zeolitic imidazolate framework (ZIF-67)/MWCNTs as a sacrificial template and subsequently conducting a simple solvent-thermal reaction with Ni(NO3)2. Such a hollow nanocage preserves the polyhedral framework structure of the used precursor, where the hollow frame-like structure of NiCo-LDH offers accessible catalytic sites, and MWCNTs provides good conductivity. Their combination brings in a bridging effect between MWCNTs and NiCo-LDH, further leading to a large electrochemical active area and excellent catalytic activity of this hollow nanocage. The constructed sensor exhibits a detection limit as low as 0.03 mu M for the glucose detection as well as wide linear ranges of 0.1-3000 mu M and 3000-9231.8 mu M, corresponding to the sensitivity of 2.55 and 1.15 mu A mM-1 cm-2, respectively. Moreover, this sensor enables the tracking of glucose concentration change in salivary before and after food intake. This work offers new highly sensitive sensing materials and potentially valuable approaches for noninvasive glucose detection.
更多
查看译文
关键词
Saliva glucose,Layered double hydroxides,Multiwalled carbon nanotubes,Nanocages,Electrochemical sensor
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要