Modeling and optimization of Au-GaAs plasmonic nanoslit array structures for enhanced near-infrared photodetector applications

Abstract

, "Modeling and optimization of Au-GaAs plasmonic nanoslit array structures for enhanced near-infrared photodetector applications," J. Nanophoton. 11(1), 016017 (2017), doi: 10.1117/1.JNP.11.016017. Abstract. This theoretical work explores how various geometries of Au plasmonic nanoslit array structures improve the total optical enhancement in GaAs photodetectors. Computational models studied these characteristics. Varying the electrode spacing, width, and thickness drastically affected the enhancement in the GaAs. Peaks in enhancement decayed as Au widths and thicknesses increased. These peaks are resonant with the incident near-infrared wavelength. The enhancement values were found to increase with decreasing electrode spacing. Additionally, a calculation was conducted for a model containing Ti between the Au and the GaAs to simulate the necessary adhesion layer. It was found that optical enhancement in the GaAs decreases for increasing Ti layer thickness. Optimal dimensions for the Au electrode include a width of 240 nm, thickness of 60 nm, electrode spacing of 5 nm, and a minimum Ti thickness. Optimal design has been shown to improve enhancement to values that are up to 25 times larger than for nonoptimized geometries and up to 300 times over structures with large electrode spacing. It was also found that the width of the metal in the array plays a more significant role in affecting the field enhancement than does the period of the array. © The Authors. Published by SPIE under aCreative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

Effect of incidence and sidewall taper angles on plasmonic metal–semiconductor–metal photodetector enhancements

“…This work shows that optimizing the taper angle about doubles the optical enhancement, and optimizing the incident angle almost triples the optical enhancement. These effects are not as large as varying other geometric parameters, such as gap width, which can increase enhancement by 300 times [27]; electrode width, which can increase enhancement by about 5 times [22,27]; or electrode thickness, which can increase the enhancement by about 10 times [27]. Also, optimizing the Raleigh-Wood anomaly by adjusting the period of the grating can improve absorption by about 5 times [9].…”

“…The aim of this paper was to study the effects of the taper and incident light angles on optical and electrical enhancements for plasmonic MSM PDs using single-wavelength detection. The results herein have the potential to be very helpful for the design of photodetection [23][24][25][26][27], photovoltaic [28][29][30], and optical sensing devices [31,32]. Figure 1(a) shows the proposed device with gold nanoelectrodes.…”

Dataset for SERS Plasmonic Array: Width, Spacing, and Thin Film Oxide Thickness Optimization

“…Components of the model held constant during all sweeps include the height of the air above the structure, which was held at 500 nm, the thickness of the Si layer beneath the SiO 2 layer, which was held at 200 nm, and the Ti adhesion layer between each Au grating and the SiO 2 layers, which was held at 1 nm. The Ti layer was kept at this small thickness due to the adhesive properties of Ti between Au and SiO 2 [21] in conjunction with its inherent mitigation of plasmonic effects [21]. The Au grating thickness was held at 15 nm to represent current nanofabrication [22] capabilities.…”

“…The datasets accompanying this paper as supplementary files provide the data compiled during the computational studies in [21]. The primary file is separated into subfolders that are denoted by the figures in [21], with an additional file being the base model used to create the data presented.…”

“…The datasets accompanying this paper as supplementary files provide the data compiled during the computational studies in [21]. The primary file is separated into subfolders that are denoted by the figures in [21], with an additional file being the base model used to create the data presented. In these subfolders are files of three different types: text files containing the data exported by the completed models, Microsoft Excel files containing the line average calculations of models of specific parameters, and visual figures produced by MATLAB (The Mathworks, Natick, MA, USA).…”