Palladium Supported on an Amphiphilic Triazine-Urea-Functionalized Porous Organic Polymer as a Highly Efficient Electrocatalyst for Electrochemical Sensing of Rutin in Human Plasma.
A T Ezhil VilianRajamanickam SivakumarYoung-Kyu HanJi Ho YoukYoung-Kyu HanPublished in: ACS applied materials & interfaces (2018)
Metal nanoparticle-containing porous organic polymers have gained great interest in chemical and pharmaceutical applications owing to their high reactivity and good recyclability. In the present work, a palladium nanoparticle-decorated triazine-urea-based porous organic polymer (Pd@TU-POP) was designed and synthesized using 1,3-bis(4-aminophenyl)urea with cyanuric chloride and palladium acetate. The porous structure and physicochemical properties of the electrode material Pd@TU-POP were observed using a range of standard techniques. The Pd@TU-POP material on the electrode surface showed superior sensing ability for rutin (RT) because the Pd dispersion facilitated the electrocatalytic performance of TU-POP by reducing the overpotential of RT oxidation dramatically and improving the stability significantly. Furthermore, TU-POP provides excellent structural features for loading Pd nanoparticles, and the resulting Pd@TU-POP exhibited enhanced electron transfer and outstanding sensing capability in a linear range between 2 and 200 pM having a low detection value of 5.92 × 10-12 M (S/N = 3). The abundant porous structure of Pd@TU-POP not only provides electron transport channels for RT diffusion but also offers a facile route for quantification sensing of RT with satisfactory recoveries in aqueous electrolyte containing human plasma and red wine. These data reveal that the synthetic Pd@TU-POP is an excellent potential platform for the detection of RT in biological samples.
Keyphrases
- highly efficient
- metal organic framework
- reduced graphene oxide
- electron transfer
- gene expression
- label free
- heavy metals
- water soluble
- hydrogen peroxide
- air pollution
- climate change
- particulate matter
- risk assessment
- genome wide
- deep learning
- nitric oxide
- high resolution
- human health
- carbon nanotubes
- simultaneous determination
- visible light