The prevalence of computer vision systems necessitates hardware-based approaches to relieve the high computational demand of deep neural networks in resource-limited applications. One solution would be to off-load low-level image feature extraction, such as edge detection, from the digital network to the analog imaging system. To that end, this work demonstrates incoherent, broadband, low-noise optical edge detection of real-world scenes by combining the wavefront shaping of a 24-mm aperture metasurface with a refractive lens. An inverse design approach is used to optimize the metasurface for Laplacian-based edge detection across the 7.5- to 13.5-μm LWIR imaging band, allowing for facile integration with uncooled microbolometer-based LWIR imagers to encode edge information. A polarization multiplexed approach leveraging a birefringent metasurface is also demonstrated as a single-aperture implementation. This work could be applied to improve computer vision capabilities of resource-constrained systems by leveraging optical preprocessing to alleviate the computational requirements for high-accuracy image segmentation and classification.

Group IV alloys of GeSn have been extensively investigated as a competing material alternative in shortwave-to-mid-infrared photodetectors (PDs). The relatively large defect densities present in GeSn alloys are the major challenge in developing practical devices, owing to the low-temperature growth and lattice mismatch with Si or Ge substrates. In this paper, we comprehensively analyze the impact of defects on the performance of GeSn p-i-n homojunction PDs. We first present our theoretical models to calculate various contributing components of the dark current, including minority carrier diffusion in p- and n-regions, carrier generation–recombination in the active intrinsic region, and the tunneling effect. We then analyze the effect of defect density in the GeSn active region on carrier mobilities, scattering times, and the dark current. A higher defect density increases the dark current, resulting in a reduction in the detectivity of GeSn p-i-n PDs. In addition, at low Sn concentrations, defect-related dark current density is dominant, while the generation dark current becomes dominant at a higher Sn content. These results point to the importance of minimizing defect densities in the GeSn material growth and device processing, particularly for higher Sn compositions necessary to expand the cutoff wavelength to mid- and long-wave infrared regime. Moreover, a comparative study indicates that further improvement of the material quality and optimization of device structure reduces the dark current and thereby increases the detectivity. This study provides more realistic expectations and guidelines for evaluating GeSn p-i-n PDs as a competitor to the III-V- and II-VI-based infrared PDs currently on the commercial market.

Lattices of plasmonic nanorings with particular geometries exhibit singular, tunable resonance features in the infrared. This work examined effects of nanoring inner radius, wall thickness, and lattice constant on the spectral response of single nanorings and in Fano resonant square lattices, combining use of the discrete and coupled dipole approximations. Increasing nanoring inner radius red-shifted and broadened the localized surface plasmon resonance (LSPR), while wall thickness modulated the LSPR wavelength and decreased absorption relative to scattering. The square lattice constant was tuned to observe diffractively-coupled lattice resonances, which increased resonant extinction 4.3-fold over the single-ring LSPR through Fano resonance. Refractive index sensitivities of 760 and 1075 nm RIU⁻¹ were computed for the plasmon and lattice resonances of an optimized nanoring lattice. Sensitivity of an optimal nanoring lattice to a local change in dielectric, useful for sensing applications, was 4 to 5 times higher than for isolated nanorings or non-coupling arrays. This was attributable to the Fano line-shape in far-field diffractive coupling with near-field LSPR.