C. Dong, Y. Zhao, K.D. Benkstein, S. Semancik, M.E. Zaghloul
The George Washington University,
Keywords: sensor, nanohole array, localized surface plasmon resonance, selectivity
Summary:Nanohole array (NHA) based plasmonic sensors are studied and widely used for their high performance. Plasmonic sensors are based on localized surface plasmon resonance (LSPR). LSPR happens when incident light interacts with the electrons on the surface of a suitable metal nanostructure and generates a resonant oscillation. The oscillation is sensitive to the local environment , . For example, when the analytes interact with the sensor, it causes slight changes in the refractive index. The slight changes will cause shifts of spectrum waveform . However, sensors need not only high sensitivity but also selectivity during real applications, which requires detecting and identifying multiple analytes with unknown concentrations. Sometimes, it is difficult to identify the target analyte from a single sensor response because different analytes may show similar responses . Multi-period based NHA plasmonic sensors have the potential to provide more analytical information to increase the selectivity of the sensor, because the multi-period sensors will have different spectral waveforms, with each spectrum shifting differently when exposed to the same analyte . This work provides a simulation of nanohole array (NHA) based plasmonic sensors. The devices are comprised of gold (Au) nanohole arrays on a SiO2 substrate with varied periods to improve the selectivity over using a NHA sensor with a single configuration. Six different sensing sectors with different periods and diameters were studied using finite difference time domain (FDTD) simulation. Figure 1 shows the schematic of the NHA sensor. The period of nanohole array in each sensing sector was set from 200 nm to 400 nm in 40 nm increments, while the diameter of the holes was kept at 0.5× its corresponding period. The material in the nanohole region is set as air with a refractive index (n) of 1.0. This value was modified to 1.1 and 1.2 in subsequent simulations to simulate the presence of different analytes. Then, an incident light was set to irradiate the Au/SiO2 interface layer. A monitor was placed on the surface of the Au layer to detect the transmitted intensity and waveform of NHAs with different periods under different conditions, i.e. n = 1.0, 1.1 and 1.2. Spectral shifts of different NHAs were recorded to identify different analytes. The results of the simulations (Figure 3) show the relationship between the corresponding wavelength peak shifts relative to air (n = 1.0) when exposed to different analytes (n = 1.1, 1.2) for each NHA sensing sector. It shows that different analytes have unique characteristics for different periods of the NHA, which can help identify different analytes.