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State of the art in flexible SERS sensors toward label-free and onsite detection: from design to applications

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Abstract

Surface-enhanced Raman scattering (SERS) as a powerful non-invasive spectroscopic technique has been intensively used in bio/chemical sensing, enabling ultrasensitive detection of various analytes and high specificity with a fingerprint-like characteristic. Flexible SERS sensors conformally adapting to nonplanar surfaces and allowing swab-sampling or in-situ detection of analytes, which are not achievable for rigid SERS sensors, greatly meet the demand of onsite and real-time diagnostics. However, the rational design and fabrication of flexible SERS-based sensors for point-of-care diagnostics aiming to simultaneously achieve extremely high sensitivity, stability, and good signal reproducibility remain many challenges. We present a state-of-the-art review of the flexible SERS sensors. Attentions are devoted to engineering plasmonic substrates for improving the performance of flexible SERS devices. Strategies of constructing the flexible SERS sensors toward point-of-care detection are investigated in depth. Advanced algorithms assisting the SERS data process are also presented for intelligently distinguishing the species and contents of analytes. The promising applications of flexible SERS sensors in medical diagnostics, environmental analyses, food safety, and forensic science are displayed. The flexible SERS devices serving as powerful analytical tools shed new light on the in-situ and point-of-care detection of real-world analytes in a convenient, facile, and nondestructive manner, and especially are conceivable to serve as next-generation wearable sensors for healthcare.

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Acknowledgments

This work was financially supported by the Fundamental Research Funds for the Central Universities (No. N2019008) and the National Natural Science Foundation of China (No. 81501556).

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Xie, L., Zeng, H., Zhu, J. et al. State of the art in flexible SERS sensors toward label-free and onsite detection: from design to applications. Nano Res. 15, 4374–4394 (2022). https://doi.org/10.1007/s12274-021-4017-4

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