Highly field enhancement by plasmonic field engineering in random distribution of Au-Au nanoparticles as SERS structure


SalmanOgli A., Nasseri B., Piskin E.

JOURNAL OF LUMINESCENCE, cilt.190, ss.386-391, 2017 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 190
  • Basım Tarihi: 2017
  • Doi Numarası: 10.1016/j.jlumin.2017.05.083
  • Dergi Adı: JOURNAL OF LUMINESCENCE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.386-391
  • Hacettepe Üniversitesi Adresli: Evet

Özet

In this work, some typical portable surface-enhanced plasmon Raman scattering systems have been analyzed, modeled, and examined. Initially, the periodic array structure, which has been used for enhancing the portable Raman scattering, is considered. Then an aperiodic array is modeled and its advantages such as low field de localization, which is high, are examined. However, the modeling results show that for high Raman scattering enhancement with aperiodic array, the inter-distance between NPs should be smaller than 17 nm. This is impractical, in fact, cannot be constructed by the electron beam lithography. Hence, we proposed a perturbed aperiodic structure, which allows a smaller inter-distance between nanoparticles and so attaining the highly enhancement of the Raman scattering. By controlling the localization of the plasmonic field in the portable structure, the Raman signal enhancement can be improved. Interestingly, the practical and theoretical results showed that by use of the adjacent nanoparticles plasmonic interaction (nano-lens), the Raman signals are severely enhanced. This means that by interaction of light with the larger nanoparticles, the high intensity near field (hot-spot) around them is created, which dramatically affects smaller nanoparticles. Furthermore, for an accurate estimation of the nanoparticles' plasmonic effect on the Raman signal, we selected a portion of TEM images and modeled it by COMSOL and show the harmony between the modeling results and experiment data.