• 文献标题:   Copper Nanoparticles/Poly Acrylic Acid/Reduced Graphene Oxide Nanocomposite Modified Glassy Carbon Electrode for Determination of 4-Nitrophenol in Water
  • 文献类型:   Article
  • 作  者:   ZHANG CZ, ZHANG ZF, LIAN H, LIANG CY, LI K, PENG JY
  • 作者关键词:   graphene, 4nitrophenol, copper nanoparticle, chronoamperometry, chronocoulometry, differential pulse voltammetry
  • 出版物名称:   CHINESE JOURNAL OF ANALYTICAL CHEMISTRY
  • ISSN:   0253-3820 EI 1872-2040
  • 通讯作者地址:   Guangxi Normal Univ Nationalities
  • 被引频次:   1
  • DOI:   10.11895/j.issn.0253-3820.160606
  • 出版年:   2017

▎ 摘  要

A moderate and simple in situ growth approach was employed to load copper nanoparticles (CuNPs) noncovalently on graphene for preparation of CuNPs/poly acrylic acid/reduced graphene oxide (CuNPs/PAA/GR) nanocomposites for electro-catalysis of 4-nitrophenol (4-NP). The morphology of the material was observed by scanning electron microscopy (SEM). Tests with various scan rates and pH conditions indicated an adsorption-controlled electrode process occurred. The mechanism of the electrode reaction of 4-NP involved a two-electron process accompanied by a deprotonation step. Electrochemical parameters were calculated with the electron transfer number (n) as 2. 3, the effective area (0. 6275 cm(2)) of CuNPs/PAA/GR/GCE electrode was 2. 22 times as large as that of bare electrode, the adsorption capacity. Gamma(s) value was 1. 6x10(-11) mol/cm(2), and the average value of the calculated k(cat) value was 1. 15x10(4) L/(mol.s). Under the optimal conditions, the differential pulse voltammetric response of the electrode showed a linear relationship with 4-NP concentration in the range of 1-150 mmol/L. The regression equation was I-pa(mu A)= -0. 015C (mu mol/L)-0. 98 (R-2 = 0. 9951), and the detection limit was 0. 23 mu mol/L (S/N = 3). The fabricated sensor exhibited high sensitivity, good stability and high reproducibility. This sensor was applied for detection of 4-NP in water samples with favorable recoveries of 88. 6% - 100. 7% and relative standard deviation (RSD) of 2. 6% -5. 9%.