Effect of Graphene vs. Reduced Graphene Oxide in Gold Nanoparticles for Optical Biosensors: A Comparative Study

Ana P. G. Carvalho, Elisabete C. B. A. Alegria, Alessandro Fantoni, Ana M. Ferraria, Ana M. Botelho Do Rego, Ana P. C. Ribeiro

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14 Citations (Scopus)
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Abstract

Aiming to develop a nanoparticle-based optical biosensor using gold nanoparticles (AuNPs) synthesized using green methods and supported by carbon-based nanomaterials, we studied the role of carbon derivatives in promoting AuNPs localized surface plasmon resonance (LSPR), as well as their morphology, dispersion, and stability. Carbon derivatives are expected to work as immobi-lization platforms for AuNPs, improving their analytical performance. Gold nanoparticles (AuNPs) were prepared using an eco-friendly approach in a single step by reduction of HAuCl4·3H2O using phytochemicals (from tea) which act as both reducing and capping agents. UV–Vis spectroscopy, transmission electron microscopy (TEM), zeta potential (ζ-potential), and X-ray photoelectron spectroscopy (XPS) were used to characterize the AuNPs and nanocomposites. The addition of reduced graphene oxide (rGO) resulted in greater dispersion of AuNPs on the rGO surface compared with carbon-based nanomaterials used as a support. Differences in morphology due to the nature of the carbon support were observed and are discussed here. AuNPs/rGO seem to be the most promising candidates for the development of LSPR biosensors among the three composites we studied (AuNPs/G, AuNPs/GO, and AuNPs/rGO). Simulations based on the Mie scattering theory have been used to outline the effect of the phytochemicals on LSPR, showing that when the presence of the residuals is limited to the formation of a thin capping layer, the quality of the plasmonic resonance is not affected. A further discussion of the application framework is presented.

Original languageEnglish
Article number163
Number of pages20
JournalBiosensors
Volume12
Issue number3
DOIs
Publication statusPublished - 4 Mar 2022

Keywords

  • AuNPs
  • Biosensors
  • Metal–graphene hybrid
  • Mie theory
  • Simulations

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