Flexible Surface-Enhanced Raman Scattering Tape Based on Ag Nanostructured Substrate for On-Site Analyte Detection

拉曼散射 基质(水族馆) 分析物 纳米结构 检出限 材料科学 纳米技术 胶粘剂 拉曼光谱 化学 分析化学(期刊) 光学 图层(电子) 色谱法 海洋学 物理 地质学
作者
Hongyan Wu,Chiranjeevi Kanike,Alain Marcati,Xuehua Zhang
出处
期刊:Langmuir [American Chemical Society]
卷期号:40 (8): 4218-4227 被引量:2
标识
DOI:10.1021/acs.langmuir.3c03340
摘要

Surface-enhanced Raman scattering (SERS) has emerged as a powerful surface analytical technique that amplifies Raman scattering signals of molecules adsorbed onto metal nanostructured surfaces. The droplet reaction method has recently been employed to fabricate large-scale microring patterns of silver (Ag) nanostructures on rigid substrates, which enables sensitive detection within the ring area. However, these rigid substrates present limitations for direct on-site detection of analyte residues on irregular sample surfaces. There is a need to develop soft and flexible SERS substrates that can intimately conform to arbitrary surfaces. In this study, we presented a SERS substrate using flexible and adhesive tape as the supporting material. This SERS tape was fabricated by repeatedly transferring presynthesized Ag nanostructures from a rigid substrate to the tape. For a model compound adenine, our SERS tape exhibited a good linear response from 5 × 10–4 M to 5 × 10–5 M with a low limit of detection (LOD) of 5 × 10–7 M and displayed a SERS enhancement factor (EF) of 3.2 × 105. The relative standard deviation (RSD) of SERS intensity achieved was as low as 1.93%, indicating its outstanding uniformity. The as-prepared SERS tape was used for in situ detection of pesticide residue on an apple surface and dye residue on human hair. Leveraging the large surface area of Ag nanostructure patterns from the droplet reaction, the developed SERS tape demonstrates excellent performance in terms of sensitivity and uniformity. The successful detection of analyte residues on arbitrary surfaces of apple and human hair highlights the potential of this flexible SERS tape for real-world applications across various industries for enhanced diagnostic accuracy.
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