3D Light-Direction Sensor Based on Segmented Concentric Nanorings Combined with Deep Learning.

Area of Science:

• Optoelectronics
• Nanotechnology
• Machine Vision

Background:

• Traditional angle sensors face miniaturization limits due to diffraction.
• Existing 3D light-direction sensors lack stability.
• Nanowire-based sensors show promise for compact angle perception.

Purpose of the Study:

• To propose a novel sensor concept for stable, high-precision 3D light-direction detection.
• To design an ultra-thin, micrometer-scale angle sensor using a segmented concentric nanoring structure.
• To validate the sensor's performance through simulations and deep learning analysis.

Main Methods:

• A segmented concentric nanoring structure was designed for sensitivity to elevation (θ) and azimuth (ϕ) angles.
• Simulations were performed to evaluate the sensor's detection range and accuracy.
• Deep learning (DL) was employed for data analysis, prediction, and to address data aliasing.

Main Results:

• The proposed sensor demonstrated a detection range of 0–360° for ϕ and 45°–90° for θ with a 1° step size.
• An average accuracy of 0.19° was achieved.
• DL analysis improved accuracy and expanded the sensing range by resolving data aliasing.

Conclusions:

• The nanoring sensor design offers a stable and miniaturized solution for 3D light-direction sensing.
• Mutual resonance coupling among nanoring segments broadens angle sensing capabilities.
• Flexible adjustments for diverse applications are possible via waveguide implementation or sensor arrays.