Noise Management of Surface-Enhanced Raman Spectroscopy Using Two-Dimensional Materials

Surface-enhanced Raman spectroscopy (SERS) offers high sensitivity for biomolecular detection, but its performance is often constrained by noise arising from signal non-uniformity across substrates. Here, we introduce a noise-management-oriented design strategy for hybrid SERS substrates composed of gold nanoparticles (AuNP) and two-dimensional (2D) materials (graphene, MoS₂, and WSe₂). Compared with conventional AuNP substrates, the hybrids exhibit markedly improved spectral uniformity and signal-to-noise ratio (SNR), with the AuNP/graphene platform reducing noise by ∼67% and increasing SNR by ∼279%. Full-wave simulations based on Maxwell's equations corroborated the experimental results and reveal that optical constants of the 2D material and nanoparticle distribution jointly govern noise characteristics. SNR dependence on nanoparticle density distributions, refractive index (n), and extinction coefficient (k) is further established. As a practical demonstration, the AuNP/graphene substrate enabled detection of the receptor binding domain protein at a limit of detection (LOD) of 10^-9 M, representing a ten-fold improvement over the 10^-8 M LOD of AuNP substrates. These results establish AuNP/2D hybrids as effective platforms for noise-managed SERS, offering enhanced sensitivity for biosensing.