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Interlocking Au nanospheres-concave nanocubes assemblies on concave anodized aluminum oxide: Tunable plasmonic hotspots for enhanced SERS sensing

  • Guoqiang Fang
  • , Xiaotian Wang
  • , Bing Zhang
  • , Jiheng Zhang
  • , Lizhi Li
  • , Wenhao Li
  • , Jingkun Yuan
  • , Taofei Jiang*
  • , Wuliji Hasi*
  • , Yongkang Dong*
  • *Corresponding author for this work
  • Harbin Institute of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

The plasmonic resonance coupling characteristics of noble metal nanoparticles govern their capacity to modulate light-matter interactions. However, noble metal nanoparticle systems with a single morphology are often constrained by their fixed geometric parameters, thereby enabling only specific types of plasmonic resonance coupling. To address this limitation, this study innovatively combines Au nanospheres (Au NSs) and Au concave nanocubes (Au CNCs) to develop a novel binary plasmonic system. Precise control of the two nanoparticles’ mixing ratio enabled the successful fabrication of three composite hotspot structures: point-to-point, corner-to-corner, and convex-to-concave configurations. Experimental results demonstrate that this binary -plasmonic assembly film exhibits significantly enhanced surface-enhanced Raman scattering (SERS) performance, with further validation of localised electric field enhancement achieved through Finite-Difference Time-Domain (FDTD) simulations. This binary -plasmonic system was innovatively assembled onto a concave anodized aluminium oxide (AAO) template. By leveraging the 3D light trapping effect of the AAO template and the newly generated longitudinal hotspots between the binary nanostructures, a substantial enhancement of SERS signals was achieved. Combined with the multi-interval partial least squares algorithm, this platform enabled proof-of-concept quantitative detection of uric acid in artificial urine with a detection limit of 10−6 M. This study offers novel insights for the design and construction of novel plasmonic hotspots.

Original languageEnglish
Article number130102
JournalTalanta
Volume310
DOIs
StatePublished - 1 Dec 2026

Keywords

  • 3D SERS platform
  • Assembly
  • Binary plasmonic system
  • Machine learning
  • Uric acid detection

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