journal article·2022-06

One-step ultrasonication-assisted synthesis of graphitized multi-walled carbon nanotubes@Super P Li nanocomposite for the determination of isoproturon

Dongdong Li, Xuli Hu, Hongyuan Zhao, Kunjie Ding, Fang Li, Shixing Han, Hongliang Wang, Lianyang Bai, Runqiang Liu

Journal of Porous Materials· Volume 29· Issue 3
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Abstract

Carbonaceous nanomaterials have exhibited huge practical prospects as conductive sensitizers for the modification of electrodes. In this work, the nanocomposite of graphitized multi-walled carbon nanotubes@Super P Li carbon nanoparticles (GCNTs@SP-Li) was designed via a simple ultrasonication-assisted strategy, and then the GCNTs@SP-Li/GCE sensor based on the synthesized GCNTs@SP-Li nanocomposite decorating glassy carbon electrode (GCE) was successfully applied in the sensitive detection of isoproturon (ISO). For the GCNTs@SP-Li nanocomposite, GCNTs with porous structure presented excellent adsorption property, which contributed to the preconcentration of ISO and facilitated the electrolyte penetration. Additionally, GCNTs possessed good electrical conductivity owing its higher graphitization degree. More importantly, the interconnected dot-line-like structure of GCNTs@SP-Li nanocomposite acted as conductive “highways” to remarkably reduce the electron transport distance, which could significantly accelerate the process of redox reaction. Benefiting from the synergistic effect of GCNTs and SP-Li, the optimized GCNTs@SP-Li/GCE sensor showed a low detection limit of 0.1653 μM in the linear concentration of 0.7–30 μM. Additionally, the proposed sensor exhibited satisfactory recoveries from 97.2 to 101.6% towards the determination of ISO in river water and tap water. This work offers a feasible and cost-effective idea in developing the high-performance ISO electrochemical sensor.
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Research context

OpenAlex topics: Electrochemical sensors and biosensors · Electrochemical Analysis and Applications · Conducting polymers and applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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