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Updated: Jan 18, 2026

Optical Trapping of Plasmonic Nanoparticles for In Situ Surface-Enhanced Raman Spectroscopy Characterizations
Published on: June 23, 2022
Semiopen Ag@Au Plasmonic Nanotube Arrays Synergizing Molecular Confinement and Multimodal SERS for Lung Cancer Breath
Si Chen1,2,3, Chenge Xu1,2,3, Junzheng Luo1,2,3
1College of Engineering and Applied Sciences, Nanjing University, Nanjing 210093, P. R. China.
Abstract:
Exhaled breath analysis offers noninvasive, early lung cancer detection via volatile organic compound (VOC) biomarkers, surpassing blood-based methods. Surface-enhanced Raman spectroscopy (SERS) is ideal for this purpose, combining molecular fingerprint specificity with single-molecule sensitivity. However, conventional SERS substrates face a fundamental limitation: while porous materials such as metal-organic frameworks effectively adsorb VOCs through their subnanometer pores (0.5-2 nm), their nonmetallic composition and confined pore architecture (orders of magnitude smaller than Raman excitation wavelengths) severely restrict plasmonic enhancement. In contrast, ordered plasmonic arrays deliver strong signal amplification but lack sufficient porosity for efficient VOCs adsorption. Here, we develop semiopen ordered Ag@Au nanotube arrays fabricated through nanoimprint lithography and ion beam etching-induced sidewall growth, which simultaneously function as optical resonators and molecular traps, enabling multimodal plasmonic coupling (localized surface plasmon resonance, surface plasmon resonance, and periodic lattice resonance) for superior light-matter interactions. The substrate's performance is further enhanced through Ag nanoparticle decoration for hotspot amplification and 4-aminothiophenol (4-ATP) functionalization for selective aldehyde capture via Schiff base reaction. The resulting SERS substrate shows strong visible absorption (86.5%), excellent benzaldehyde sensitivity (limit of detection: 10 ppb), and long-term stability (relative standard deviation = 4.9%, >50 days), offering a practical platform for breath-based lung cancer diagnostics.

