Minimizing quantification uncertainty in nanoplasmonic platforms: Multifunctional MoS2-integration for precise biomarker determination

Abstract

Despite growing interest in nanoplasmonic biosensors-particularly surface-enhanced Raman spectroscopy (SERS) platforms-their potential has been limited by high quantification variability rooted in poor uniformity. Previous approaches to address this, such as incorporating internal standards (ISs), often sacrificed sensitivity for uniformity or lacked a clear analytical basis for accurate quantification. Here, a novel approach of integrating MoS2 into a SERS platform is introduced, with a focus on mitigating spot-to-spot relative standard deviation (RSD) and improving quantification accuracy. While maintaining the well-known enhanced sensitivity of MoS2, the Raman signal from a uniform monolayer is utilized to calibrate signal variations. As a result, the platform achieves the lowest RSD (5.29%) among MoS2-based systems, while offering the highest level of sensitivity in rhodamine 6G (R6G) measurements. For albumin, the target proteinuria biomarker, MoS2-based normalization outperforms conventional wafer-based methods and achieves a 42% RSD reduction over non-normalization because the atomic thickness MoS2 enables precise plasmonic calibration. Furthermore, a consistent, exponential relationship between MoS2 signal intensity and albumin concentration is discovered. Quantification trends are consequently highly predictable, resulting in a 4.8-fold increase in data separability. This quantification approach is shown to be effective for albumin mixed in artificial urine under various laser conditions, highlighting the practical potential of our platform for early-stage monitoring of biomarkers.