Surface-Enhanced Raman Scattering-Based Multimodal Techniques: Advances and Perspectives

IF 16 1区 材料科学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Emily Xi Tan, Qi-Zhi Zhong, Jaslyn Ru Ting Chen, Yong Xiang Leong, Guo Kang Leon, Cam Tu Tran, In Yee Phang* and Xing Yi Ling*, 
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引用次数: 0

Abstract

Surface-enhanced Raman scattering (SERS) spectroscopy is a versatile molecular fingerprinting technique with rapid signal readout, high aqueous compatibility, and portability. To translate SERS for real-world applications, it is pertinent to overcome inherent challenges, including high sample variability and heterogeneity, matrix effects, and nonlinear SERS signal responses of different analytes in complex (bio)chemical matrices with numerous interfering species. In this perspective, we highlight emerging SERS-based multimodal techniques to address the key roadblocks to improving the sensitivity, specificity, and reliability of (bio)chemical detection, bioimaging, theragnosis, and theragnostic. SERS-based multimodal techniques can be broadly categorized into two categories: (1) complementary methods or systems that work together to achieve a common goal where each method compensates for the weaknesses of the other to culminate in a single enhanced outcome or (2) orthogonal techniques that are independent and provide separate but corroborating results simultaneously without interfering with each other. These multimodal techniques maximize information gained from a single experiment to achieve enhanced qualitative or quantitative analysis and broaden the range of detectable analytes from small molecules to tissues. Finally, we discuss emerging directions in multimodal platform design, instrument integration, and data analytics that aim to push the analytical limits of holistic detection.

Abstract Image

基于表面增强拉曼散射的多模态技术:进展与展望
表面增强拉曼散射(SERS)光谱是一种多功能的分子指纹识别技术,具有信号读取快、水相容性高和便携性强等特点。要将 SERS 转化为实际应用,就必须克服固有的挑战,包括样品的高变异性和异质性、基质效应以及不同分析物在具有众多干扰物种的复杂(生物)化学基质中的非线性 SERS 信号响应。在本视角中,我们将重点介绍新兴的基于 SERS 的多模态技术,以解决提高(生物)化学检测、生物成像、诊断和治疗的灵敏度、特异性和可靠性的主要障碍。基于 SERS 的多模态技术可大致分为两类:(1) 相互补充的方法或系统,共同实现一个共同目标,每种方法都能弥补其他方法的不足,最终实现单一的增强结果;(2) 相互独立的正交技术,同时提供独立但相互印证的结果,互不干扰。这些多模态技术能最大限度地利用从单一实验中获得的信息,从而加强定性或定量分析,并扩大从小分子到组织的可检测分析物的范围。最后,我们讨论了多模态平台设计、仪器集成和数据分析方面的新方向,旨在突破整体检测的分析极限。
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来源期刊
ACS Nano
ACS Nano 工程技术-材料科学:综合
CiteScore
26.00
自引率
4.10%
发文量
1627
审稿时长
1.7 months
期刊介绍: ACS Nano, published monthly, serves as an international forum for comprehensive articles on nanoscience and nanotechnology research at the intersections of chemistry, biology, materials science, physics, and engineering. The journal fosters communication among scientists in these communities, facilitating collaboration, new research opportunities, and advancements through discoveries. ACS Nano covers synthesis, assembly, characterization, theory, and simulation of nanostructures, nanobiotechnology, nanofabrication, methods and tools for nanoscience and nanotechnology, and self- and directed-assembly. Alongside original research articles, it offers thorough reviews, perspectives on cutting-edge research, and discussions envisioning the future of nanoscience and nanotechnology.
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