CTAC Self-Assembled Alkylated β-Cyclodextrin Loaded onto Functionalized MWCNTs Electrochemical Sensor for NP Detection.
Zhimin LiDongming HeYimin ZhouZi-Yu ZhangZhongai HuXiao-Quan LuPublished in: Analytical chemistry (2024)
Nonylphenol (NP) is an important fine chemical raw material and intermediate that is widely utilized in industry and may be distributed in aquatic ecosystems. Following its entry into the food and water cycles, it can subsequently enter the human body and potentially harm the human reproductive system. For the purpose of monitoring NP in water, it is thus essential to build a straightforward, affordable, and robust electrochemical sensor. Based on a two-step chemical modification proceeding and an electrostatic self-assembly effect, a double-modified β-cyclodextrin functionalized multiwalled carbon nanotube sensor (HE-β-CD-CTAC/F-MWCNTs) has been successfully constructed. It incorporates the excellent host-guest interaction ability of β-cyclodextrin and the high chemical activity of cetyltrimethylammonium chloride (CTAC), and the carbon nanotubes have an enormous particular surface area and strong electrical conductivity. The electrochemical oxidation reaction of NP with the sensor is controlled by a surface adsorption process of equal numbers of protons and electrons. In accordance with the optimized experimental parameters, the limit of detection (LOD) for the sensor is 0.13 μM, and it responds linearly to NP in the concentration range of 1-200 μM. Meanwhile, the sensor has excellent repeatability, stability, and immunity to interference. For the detection of NP in real water samples, the sensor also showed an excellent recovery rate (92.8%-98.5%) and relative standard deviation (1.16%-3.26%).
Keyphrases
- carbon nanotubes
- label free
- ionic liquid
- endothelial cells
- gold nanoparticles
- molecularly imprinted
- loop mediated isothermal amplification
- induced pluripotent stem cells
- quantum dots
- real time pcr
- air pollution
- climate change
- risk assessment
- wastewater treatment
- nitric oxide
- electron transfer
- hydrogen peroxide
- molecular dynamics simulations
- neural network