A novel electrochemical nano-platform based on graphene/platinum nanoparticles/nafion composites for the electrochemical sensing of metoprolol

ER E., ÇELİKKAN H., ERK N.

SENSORS AND ACTUATORS B-CHEMICAL, cilt.238, ss.779-787, 2017 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 238
  • Basım Tarihi: 2017
  • Doi Numarası: 10.1016/j.snb.2016.07.108
  • Dergi Adı: SENSORS AND ACTUATORS B-CHEMICAL
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.779-787
  • Anahtar Kelimeler: Metoprolol, Graphene, Platinum nanoparticles, Electrochemical sensor, Modified electrode, Stripping voltammetry, REDUCED GRAPHENE OXIDE, PERFORMANCE LIQUID-CHROMATOGRAPHY, PHARMACEUTICAL DOSAGE FORMS, GLASSY-CARBON ELECTRODE, VOLTAMMETRIC DETERMINATION, ASCORBIC-ACID, HUMAN PLASMA, CAPILLARY-ELECTROPHORESIS, URIC-ACID, SENSOR
  • Gazi Üniversitesi Adresli: Evet

Özet

Herein, we report the first promising graphene-based nanoplatform for the electrochemical sensing of metoprolol (MTP). The electrochemical behavior of and the determination conditions for MTP were analyzed in detail on a graphene/platinum nanoparticles/nafion nanocomposite modified electrode (GRE/PtNPsINFN) by cyclic voltammetry (CV) and adsorptive stripping differential pulse voltammetry (AdsDPV). Graphene nanosheets decorated with platinum nanoparticles were characterized by x-ray diffraction and transmission electron microscopy. A well-defined and irreversible oxidation peak at 1325 mV was observed on GRE/PtNPsINFN using AdsDPV. Under optimized conditions, GRE/PtNPsINFN demonstrated a good analytical performance in the quantification of nanomolar amounts of MTP. In addition, the proposed sensor was highly sensitive to MTP in the linear concentration range from 0.0144 to 7.50 OA with a low detection limit of 4.30 nM (S/N = 3). Therefore, it is concluded that GRE/PtNPsINFN is a simple, environmentally friendly and effective platform for the sensing of anti-hypertensive agents such as MTP in real samples. (C) 2016 Elsevier B.V. All rights reserved.