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

被引:2
|
作者
Tan, Emily Xi [1 ]
Zhong, Qi-Zhi [1 ]
Ting Chen, Jaslyn Ru [1 ]
Leong, Yong Xiang [1 ]
Leon, Guo Kang [1 ]
Tran, Cam Tu [1 ]
Phang, In Yee [2 ]
Ling, Xing Yi [1 ,2 ,3 ]
机构
[1] Nanyang Technol Univ, Sch Chem Chem Engn & Biotechnol, Singapore 637371, Singapore
[2] Jiangnan Univ, Sch Chem & Mat Engn, Key Lab Synthet & Biol Colloids, Minist Educ,Int Joint Res Lab Nano Energy Composit, Wuxi 214122, Peoples R China
[3] Nanyang Technol Univ, Lee Kong Chian Sch Med, Singapore 636921, Singapore
基金
新加坡国家研究基金会;
关键词
surface-enhanced Raman scattering; SERS; multimodaldetection; chemical analysis; bioimaging; theragnostic; theragnosis; machine learning; SERS DETECTION; LIQUID-CHROMATOGRAPHY; GOLD NANOPARTICLES; FLUORESCENCE; SPECTROSCOPY; SENSORS; QUANTIFICATION; IDENTIFICATION; NANORODS; AGENTS;
D O I
10.1021/acsnano.4c12996
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
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.
引用
收藏
页码:32315 / 32334
页数:20
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