Abstract

Novel concepts for developing a surface-enhanced Raman scattering (SERS) sensor based on biocompatible materials offer great potential in versatile applications, including wearable and in vivo monitoring of target analytes. Here, we report a highly sensitive SERS sensor consisting of a biocompatible silk fibroin substrate with a high porosity and gold nanocracks. Our silk-based SERS detection takes advantage of strong local field enhancement in the nanoscale crack regions induced by gold nanostructures evaporated on a porous silk substrate. The SERS performance of the proposed sensor is evaluated in terms of detection limit, sensitivity, and linearity. Compared to the performance of a counterpart SERS sensor with a thin gold film, SERS results using 4-ABT analytes present that a significant improvement in the detection limit and sensitivity by more than 4 times, and a good linearity and a wide dynamic range is achieved. More interestingly, overlap is integral, and a quantitative measure of the local field enhancement is highly consistent with the experimental SERS enhancement.

Highlights

  • Surface-enhanced Raman scattering (SERS) has been widely employed as a spectroscopic technique for the identification of chemical and biological species due to its advantages of high sensitivity, unique spectroscopic fingerprints, and non-destructive detection [1,2,3]

  • The principal amplification of SERS arises from an enhancement of local electromagnetic fields near or at a nanostructured metallic substrate, which is associated with the resonant excitation of localized surface plasmons [4,5]

  • Conjugated polymers (CPs) as organic macromolecules can combine the high conductivity of metals with the chemical tunability of polymers

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Summary

Introduction

Surface-enhanced Raman scattering (SERS) has been widely employed as a spectroscopic technique for the identification of chemical and biological species due to its advantages of high sensitivity, unique spectroscopic fingerprints, and non-destructive detection [1,2,3].

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