Bimetallic Metal-Organic Framework-Derived porous One-Dimensional carbon materials for electrochemical sensing of dopamine
Chemical Engineering Journal(2024)
Abstract
In this work, we report the preparation of one-dimensional (1D) bimetallic zinc-cobalt BTC (BTC = 1,3,5-benzenetricarboxylate) metal–organic frameworks (MOFs) with varying Zn/Co ratios and their conversion to hierarchical porous Co/C hybrids with a trace amount of Zn (<0.05 wt%). The crystallinity, surface area, and degree of graphitization of the resulting Co/C hybrid are governed by the Zn/Co ratio of the parent Zn-Co BTC MOF. The Co/C product derived from the Zn-rich Zn-Co BTC MOF (ZC31-BTC with a Zn/Co precursor ratio of 3:1) shows higher surface area and more amorphous structure than that derived from the Co-rich Zn-Co BTC MOF (ZC13-BTC with a Zn/Co precursor ratio of 1:3). When used for the electrochemical sensing of dopamine (DA), the glassy carbon electrode (GCE) modified with ZC31-BTC700°C (ZC31-BTC carbonized at 700 °C) shows a sensitivity of 0.0995nA nM−1 cm−2, a wide linear range of 0.1–500 µM, and a low limit of detection (LoD) of 0.04 µM (signal-to-noise ratio (S/N) = 3). The superior DA sensing performance of ZC31-BTC700°C is attributed to its high density of defects (evidenced by the high ID/IG ratio), rich mesopores (including small (<5 nm) and large mesopores (>5 nm)), and high surface area, leading to improved ion/electron transfer (based on the EIS analysis), and more electrochemically active sites (confirmed by ECSA measurements) to promote a greater oxidation of DA molecules. The anti-interference test of this ZC31-BTC700°C-modified GCE (ZC31-BTC700°C/GCE) indicates its high selectivity toward DA even in the presence of interferents, such as glucose, ascorbic acid, and uric acid. Moreover, the stability test indicates the good retainment of the current response of ZC31-BTC700°C/GCE toward DA over a period of 2 weeks.
MoreTranslated text
Key words
Metal-organic frameworks,Porous carbon,Dopamine,Electrochemical sensing,Biosensors,Biomolecules
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined