纳米技术
拉曼散射
光纤
化学
分析物
拉曼光谱
材料科学
计算机科学
光学
物理
电信
物理化学
作者
Rahul Kumar Gangwar,Akhilesh Kumar Pathak,Francesco Chiavaioli,M. H. Abu Bakar,Yasmin Mustapha Kamil,Mohd Adzir Mahdi,Vinod Kumar Singh
标识
DOI:10.1016/j.ccr.2024.215861
摘要
In both the scientific and technological fields, there is a fundamental need for highly sensitive and specific detection of chemical traces or biological targets at the single molecule level. To achieve this, sensor technology based on surface-enhanced Raman scattering (SERS) is a promising approach due to its extremely narrow linewidth, high sensitivity and signal-to-noise ratio, target specificity and ability for non-destructive and multiplexed monitoring of chemical or biological species. Raman scattering is a phenomenon that occurs due to the interaction between photons and molecules depending on the kinetic modes of the analytes, providing unique fingerprints that enable real-time detection of chemical or biological species. By monitoring molecular activity in the vicinity of nanostructured surfaces, SERS-based sensors not only provide valuable insight into molecular interaction or binding, but also serve as a reference for the further development of powerful and optimized detection methods. While the existing reviews on SERS devices mainly focus on classical planar or chip-based substrates, a detailed review covering various strategies for highly sensitive SERS sensors based on optical fibers, nanostructuring of the fiber surface, their working mechanisms and practical applications is still pending. Only recent advances in nanotechnology and related equipment have made it possible to effectively and reliably use optical fibers as SERS substrates. Our aim is therefore to report on the current status of SERS fiber technologies, their detection mechanisms. We also highlight different fiber geometries used so far to develop miniaturized lab-on-fiber devices, and the extensive range of applications associated with these advances by emphasizing the advantages, limitations and future perspectives in this field.
科研通智能强力驱动
Strongly Powered by AbleSci AI