Cost Effective Silver Nanowire-Decorated Graphene Paper for Drop-On SERS Biodetection

The use of SERS for real-world bioanalytical applications represents a concrete opportunity, which, however, is being largely delayed by the inadequacy of existing substrates used to collect SERS spectra. In particular, the main bottleneck is their poor usability, as in the case of unsupported noble metal colloidal nanoparticles or because of the need for complex or highly specialized fabrication procedures, especially in view of a large-scale commercial diffusion. In this work, we introduce a graphene paper-supported plasmonic substrate for biodetection as obtained by a simple and rapid aerosol deposition patterning of silver nanowires. This substrate is compatible with the analysis of small (2 μL) analyte drops, providing stable SERS signals at sub-millimolar concentration and a detection limit down to the nanogram level in the case of hemoglobin. The presence of a graphene underlayer assures an even surface distribution of SERS hotspots with improved stability of the SERS signal, the collection of well-resolved and intense SERS spectra, and an ultra-flat and photostable SERS background in comparison with other popular disposable supports.

Label-free SERS detection of proteins based on machine learning classification of chemo-structural determinants

Establishing standardized methods for a consistent analysis of spectral data remains a largely underexplored aspect in surface-enhanced Raman spectroscopy (SERS), particularly applied to biological and biomedical research. Here we propose an effective machine learning classification of protein species with closely resembled spectral profiles by a mixed data processing based on principal component analysis (PCA) applied to multipeak fitting on SERS spectra. This strategy simultaneously assures a successful discrimination of proteins and a thorough characterization of the chemostructural differences among them, ultimately opening up new routes for SERS evolution toward sensing applications and diagnostics of interest in life sciences.