Dimensional Design for Surface-Enhanced Raman Spectroscopy.

ACS materials Au(2022)

引用 12|浏览2
暂无评分
摘要
Surface-enhanced Raman spectroscopy (SERS) is a vibrational spectroscopy technique that enables specific identification of target analytes with sensitivity down to the single-molecule level by harnessing metal nanoparticles and nanostructures. Excitation of localized surface plasmon resonance of a nanostructured surface and the associated huge local electric field enhancement lie at the heart of SERS, and things will become better if strong chemical enhancement is also available simultaneously. Thus, the precise control of surface characteristics of enhancing substrates plays a key role in broadening the scope of SERS for scientific purposes and developing SERS into a routine analytical tool. In this review, the development of SERS substrates is outlined with some milestones in the nearly half-century history of SERS. In particular, these substrates are classified into zero-dimensional, one-dimensional, two-dimensional, and three-dimensional substrates according to their geometric dimension. We show that, in each category of SERS substrates, design upon the geometric and composite configuration can be made to achieve an optimized enhancement factor for the Raman signal. We also show that the temporal dimension can be incorporated into SERS by applying femtosecond pulse laser technology, so that the SERS technique can be used not only to identify the chemical structure of molecules but also to uncover the ultrafast dynamics of molecular structural changes. By adopting SERS substrates with the power of four-dimensional spatiotemporal control and design, the ultimate goal of probing the single-molecule chemical structural changes in the femtosecond time scale, watching the chemical reactions in four dimensions, and visualizing the elementary reaction steps in chemistry might be realized in the near future.
更多
查看译文
关键词
SERS, dimensional design, enhancing substrates, nanoparticle, nanowire, 2D material, nanostructure array, spatiotemporal resolution
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要