• 文献标题:   The effect of material composition of 3-dimensional graphene oxide and self-doped polyaniline nanocomposites on DNA analytical sensitivity
  • 文献类型:   Article
  • 作  者:   YANG T, CHEN HY, YANG RR, WANG XX, NAN FX, JIAO K
  • 作者关键词:   graphene oxide, selfdoped polyaniline, electrochemical impedance spectroscopy, surface density, hybridization efficiency, detection limit
  • 出版物名称:   COLLOIDS SURFACES BBIOINTERFACES
  • ISSN:   0927-7765 EI 1873-4367
  • 通讯作者地址:   Qingdao Univ Sci Technol
  • 被引频次:   6
  • DOI:   10.1016/j.colsurfb.2015.05.035
  • 出版年:   2015

▎ 摘  要

Until now, morphology effects of 2-dimensional or 3-dimensional graphene nanocomposites and the effect of material composition on the biosensors have been rarely reported. In this paper, the various nanocomposites based on graphene oxide and self-doped polyaniline nanofibres for studying the effect of morphology and material composition on DNA sensitivity were directly reported. The isolation and dispersion of graphene oxide were realized via intercalated self-doped polyaniline and ultrasonication, where the ultrasonication prompts the aggregates of graphite oxide to break up and self-doped polyaniline to diffuse into the stacked graphene oxide. Significant electrochemical enhancement has been observed due to the existence of self-doped polyaniline, which bridges the defects for electron transfer and, in the mean time, increases the basal spacing between graphene oxide sheets. Different morphologies can result in different ssDNA surface density, which can further influence the hybridization efficiency. Compared with 2-dimensional graphene oxide, self-doped polyaniline and other morphologies of nanocomposites, 3-dimensional graphene oxide-self-doped polyaniline nanowalls exhibited the highest surface density and hybridization efficiency. Furthermore, the fabricated biosensors presented the broad detection range with the low detection limit due to the specific surface area, a large number of electroactive species, and open accessible space supported by nanowalls. (C) 2015 Elsevier B.V. All rights reserved.