Optimizing the SERS Performance of 3D Substrates through Tunable 3D Plasmonic Coupling toward Label-Free Liver Cancer Cell Classification.

Three-dimensional (3D) plasmonic nanostructures are emerging as excellent surface-enhanced Raman spectroscopy (SERS) substrates for chemical and biomedical applications. However, the correlation of 3D (including both in-plane and out-of-plane) plasmonic coupling with the SERS properties to deepen the understanding of 3D SERS substrates remains a challenge. Here, we perform correlation studies of 3D plasmonic coupling and SERS properties of the 3D hierarchical SERS substrates by tuning the multiscale structural elements. The effects of zero-dimensional (0D; the size of the building blocks), one-dimensional (1D; the thickness of the 3D substrates), and two-dimensional (2D; the composition of individual monolayers) structural elements on 3D plasmonic coupling are studied by performing UV-vis-near-infrared (NIR) spectroscopy and measuring SERS performance. It shows that both the extinction spectra and SERS enhancement are tuned at the 3D structural level. It is demonstrated that the plasmonic resonance wavelength (PRW) stemming from the 3D plasmonic coupling correlates with the SERS averaged surface enhancement factor (ASEF) and is improved by more than tenfold at the optimum 3D nanostructure. The optimized substrate is used to quantitatively analyze two small biological molecules. Moreover, as a proof-of-concept study, the substrate is first applied to differentiate between living liver normal and cancer cells with a high prediction accuracy through the spectral features of the cell membranes and the metabolites secreted outside the cells. We expect that the tuning of plasmonic coupling at the 3D level can open up new routes to design high-performance SERS substrates for wide applications.