Photon-material interaction is generally very weak in silicon and other semiconductors when incident photon wavelengths are close to their optical bandgap. This weakens absorption, requiring thick semiconductor films for efficient light absorption. However, a photodetector with a thick absorption region cannot operate at high speed due to a long carrier drift time. In this talk, we will present emerging technologies based on periodic arrays of micro and nanoscale surface structures to bend normally incident beams of photons into laterally propagating modes along the plane of semiconductor films. Such structures bend light beams, slow them down, and contribute to unprecedented improvement in the light absorption efficiency in devices, even when designed with ultra-thin absorption regions. Slow and trapped photons offer exciting application opportunities, such as ultra-fast photodetectors for data center communication, sensors for advanced bioimaging, LiDAR, and highly efficient solar cells.
A compact assembly of such photodetectors, incorporating specialized surface nanostructures, can significantly enhance imaging capabilities by acquiring multi-dimensional data, including spectral profiles, temporal responses, and spatial resolution. This advancement is achievable by engineering individual ultrafast detectors exhibiting distinct responses to identical illumination while leveraging artificial intelligence (AI)-driven computational imaging. This talk will demonstrate how these capabilities can substantially miniaturize the physical dimensions of existing imaging and spectroscopic systems and elevate overall system sensitivity. These advancements can be applied to various fields, including noninvasive real-time detection and monitoring of molecules for medical diagnostics, biological sensing, and food quality assessment.