Abstract
Noble metal sculptured thin films are of great interest during last decade as excellent surface-enhanced Raman scattering (SERS) substrates due to remarkable plasmonic properties in the visible and near-infrared range. In this work, Ag columnar thin films (Ag-CTFs) have been prepared by the glancing angle deposition technique. Finite-difference time-domain simulations has been utilized to study plasmonic properties of Ag-CTFs with a more accurate model based on binary scanning electron microscope (SEM) images by taking account of the shape irregularities, size distributions and random arrangement. The calculated absorption spectra based on the model of binarized SEM images show the best agreement with the measured spectra compared with models of periodic array with a regular shape. The near-field plasmonic properties are simulated based on the verified model. The distributions of electric field enhancement and hot spots are confirmed to be spectral and polarization dependent. There are multiple resonance peaks from visible to near-infrared and multiple eigenmodes coexist at the same wavelength and electric field enhancement are mainly excited by the polarized light vertical to the gap orientation. The electric field enhancement is found to distribute unevenly in the films with surface-localized feature. The equations to calculate the simulation SERS enhancement factor (EF) and total number of hot spots (tHN) are modified according to the above discussions. The experimental SERS EFs are on the order of 107–108, which indicates the high sensitivity of the films and the simulation SERS EFs and tHNs show good agreement with the experimental EFs. It is found that the SERS performance of Ag-CTFs is decided by both the cross-section structural characteristics and film thickness, which affect the electric filed enhancement and number of adsorbed molecules, respectively. Our work could be helpful in understanding the SERS mechanism and useful to the optimization of metal sculptured thin films for designing SERS biosensor.
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