Advancing Breath-Based Diagnostics: 3D Mesh SERS Sensor Via Dielectrophoretic Alignment of Solution-Processed Au Nanoparticle-Decorated TiO2 Nanowires

Abstract

Surface enhanced Raman spectroscopy (SERS) is becoming an attractive analytical technique for the next generation of breath diagnostics. However, current SERS substrates present challenges related to fabrication cost, complexity, signal uniformity, and reproducibility. Here, a low-cost, label-free SERS sensor based on fully solution-processed decoration of TiO₂ nanowires is demonstrated (NW) with plasmonic Au nanoparticles (NP) followed by the dielectrophoretic self-assembly into a 3D mesh with high signal to noise ratio. The sensor performance is tested using 4-aminothiophenol (4-ATP) as a model analyte in gas phase, at concentrations down to 10 ppb_v, and in solution, with limit of detection ≈2.4 pM. Finally, to explore the sensor capability for breath-based diagnostics, a proof-of-concept experiment is performed with exhaled breath condensates (EBCs). The possibility to discriminate EBCs of individuals with upper respiratory tract infection (URTI) from healthy ones is demonstrated. Multiple SERS spectra (n≈50) from each sample are analyzed using orthogonal partial least squares discriminant analysis (OPLS-DA), which identifies spectral features representative of URTI in up to 80% of the infection-related spectra. These results demonstrate the applicability and potential of 1D nanomaterials together with state-of-the-art solution-processed techniques for the development of low-cost and compact SERS breath-based diagnostic platforms for clinical point-of-care applications.