Jiaqing Shen | Searcharxiv

arXiv2025

Reality-Infused Deep Learning for Angle-resolved Quasi-optical Fourier Surfaces

Optical Fourier surfaces (OFSs), featuring sinusoidally profiled diffractive elements, manipulate light through patterned nanostructures and incident angle modulation. Compared to altering structural parameters, tuning elevation and azimuth angles offers greater design flexibility for light field control. However, angle-resolved responses of OFSs are often complex due to diverse mode excitations and couplings, complicating the alignment between simulations and practical fabrication. Here, we present a reality-infused deep learning framework, empowered by angle-resolved measurements, to enable real-time and accurate predictions of angular dispersion in quasi-OFSs. This approach captures critical features, including nanofabrication and measurement imperfections, which conventional simulation-based methods typically overlook. Our framework significantly accelerates the design process while achieving predictive performance highly consistent with experimental observations across broad angular and spectral ranges. Our study supports valuable insights into the development of OFS-based devices, and represents a paradigm shift from simulation-driven to reality-infused methods, paving the way for advancements in optical design applications.

physics.optics↗

arXiv2025

Enabling Highly Efficient Infrared Silicon Photodetectors via Disordered Metasurfaces with Upconversion Nanoparticles

Silicon photodetectors are highly desirable for their CMOS compatibility, low cost, and fast response speed. However, their application the infrared (IR) is limited by silicon's intrinsic bandgap, which restricts its detection to photons with wavelengths shorter than 1100 nm. Although several methods have been developed to extend silicon photodetectors further in the IR range, these approaches often introduce additional challenges, such as increased fabrication complexity and compatibility issues with standard CMOS processes. Here, we present an approach to overcome these limitations by integrating disordered metasurfaces with upconversion nanoparticles (UCNPs), enabling IR detection by silicon photodetectors. The disordered design consists of hybrid Mie-plasmonic cavities, which can enhance both the near-field localization and wide-band light absorption from visible to IR, improving photocurrent conversion. Compared to ordered structures, the infrared absorption and near field of the highly disordered configuration are increased by 2.6-folds and 3.9-folds, respectively. UCNPs not only convert near-infrared photons into visible light but also enhance absorption in the mid-infrared range, thereby improving hot electron generation. The measured responsivity of the disordered element for 1550 nm laser is up to 0.22 A/W at room temperature, corresponding to an external quantum efficiency of 17.6%. Our design not only enhances the photocurrent performance significantly, but also extends the working wavelength of silicon photodetectors to IR wavelength, making them suitable for broad spectrum applications.

physics.optics↗