Yanghui Li

Characterizing the intensity, phase, and polarization of engineered light is fundamental to understanding and applying metasurfaces. However, existing characterization frameworks are hindered by several limitations, most notably their inability to account for the polarization of the field. Here, we report polarization sensitive coherent modulation imaging (PS-CMI), a light-weight but robust, high-resolution platform for the full-field characterization of metasurface-modulated light. By supplementing the orthogonal x- and y- complex amplitude components with an additional 45°-component, this approach calculates the retardance between two orthogonal polarization components while eliminating phase offsets, thereby enabling the subsequent recovery of the complete polarization state. We demonstrate the versatility of our method by characterizing light fields produced by a United States Air Force (USAF) target, two kinds of complex polarization field, and a metalens. This compact solution addresses a critical gap in metasurface metrology and is broadly applicable to other fields requiring the mapping of complex, polarized light distributions.

Fabry–Perot (FP) interferometric sensors are widely employed for precise measurements of temperature, strain, and pressure. However, conventional demodulation methods face inherent trade-offs among accuracy, dynamic range, and real-time performance. Herein, we propose and experimentally validate a fiber FP sensor system based on a silicon-on-insulator (SOI) chip. The demodulation principle is on the basis of mapping environmentally induced spectral shifts into speckle patterns through multimode interferences. In this study, an Archimedean spiral bidirectional multimode waveguide (MMW) is employed to replace conventional multimode fibers, enabling higher integration, simplified packaging, and improved environmental robustness. The speckle patterns are subsequently converted into eight-channel intensity signals for easier data acquisition. In the demonstration experiments, a temperature measurement accuracy of 0.02°C was achieved while maintaining excellent long-term stability. Further analysis reveals that the employed SOI chip exhibits a wavelength sensitivity of 1 pm, corresponding to a theoretical temperature resolution better than 0.001°C. Overall, the speckle-based SOI chip provides a solution for FP sensor systems that features high precision, excellent stability, and a broad dynamic range.

Compared with traditional grating-based spectrometers, a coherent optical spectrum analyzer (COSA) can provide much higher resolution by converting optical spectral signals into electrical beat signals via heterodyne detection. However, the heterodyning process produces two symmetric sideband peaks for each spectral component, i.e., the mirror effect, which fundamentally limits the resolution. To overcome this constraint, we introduce an instantaneous frequency masking algorithm to eliminate the mirror effect in this study. Experimental results demonstrate a spectral resolution of 2 MHz using the same hardware previously limited to 6 MHz. Furthermore, a compact silicon-photonic wavelength reference for sweep linearization is utilized in the system, achieving long-term wavelength accuracy of ±0.1 pm. The proposed method establishes a cost-effective new paradigm for surpassing the inherent resolution limits of COSA.

Single‐Molecule Force Spectroscopy (SMFS) provides crucial insights into molecular mechanical properties and interactions. However, the localization of folding events relies on manual operations, which are inefficient and susceptible to subjective errors. Existing automated methods also face limitations in accuracy and robustness. To overcome these challenges, this study introduces an Inception‐based Self‐attention Skip Network (ISSN), combining Inception blocks with a Self‐attention mechanism to classify and localize folding events, including initiation and termination sites. And proposed a Force‐Distance Curve (FDC) simulation method to address the issue of insufficient datasets. Validation on Deoxyribonucleic Acid (DNA) hairpin Force‐Distance Curves (FDCs) demonstrates that ISSN achieves outstanding performance, including 99.8% classification accuracy, a low mean absolute error (MAE) of 0.176 pN for the force site, and 1.57 nm MAE for the distance site, even under high noise conditions. Compared to other classic models, ISSN not only delivers superior accuracy but also exhibits strong generalization and robustness for automated optical tweezers SMFS analysis.

Fiber Bragg gratings (FBGs) are widely used as sensors for temperature, strain, and vibration measurement. However, current FBG demodulation methods face issues with stability, size, and cost. In this study, we proposed a silicon-on-insulator (SOI) chip to demodulate FBGs based on random speckles. A 20-mm-long coiled multimode silicon waveguide was designed to generate the speckle pattern, which was then compressed into 8 single-mode outputs. The architecture similarity between the convolutional neural network (CNN), and the proposed SOI chip was discussed. A multilayer perceptron (MLP) network was applied to regress the speckle data for prediction. The demonstrated experiments indicated that a standard deviation of 0.0414°C was achieved in the single FBG demodulation. Furthermore, we also explored the capability of demodulating multiple FBGs. This speckle-based SOI chip provides a highly stable, compact, and lightweight solution in a FBG sensing system.

Lead halide perovskites have garnered interest in light-emitting diode (LED) applications due to their strong emission and tunable properties. However, conventional synthesis methods involve energy-intensive thermal processes and hazardous organic solvents, raising environmental concerns. In this study, we report a simple and eco-friendly mechanochemical approach that produces phase-pure blue-emitting Cs₃Cu₂I₅ (emission at 440 nm) and yellow-emitting CsCu₂I₃ (emission at 570 nm) phosphors through polarity modulation and control of grinding duration. Our comprehensive analysis of the phase transitions during mechanochemical synthesis reveals that pure Cs₃Cu₂I₅ was synthesized from a 3:2 precursor molar ratio in ethanol for 30 min, while pure CsCu₂I₃ was obtained from a 1:2 precursor molar ratio in an aqueous solution for 7.5 min. Moreover, Raman spectroscopy, X-ray diffraction, and energy-dispersive X-ray spectroscopy analyses confirmed that phase-pure phosphors were achieved through these methods. Finally, we fabricated a series of color-adjustable LEDs by mixing Cs₃Cu₂I₅ and CsCu₂I₃ phosphors in different proportions. This demonstrates the potential of our mechanochemical synthesis for the efficient, large-scale production of next-generation lighting materials with tunable emission.

To provide a lightweight and cost-effective solution for the long-wave infrared imaging using a singlet, we develop a camera by integrating a High-Frequency-Enhancing Cycle-GAN neural network into a metalens imaging system. The High-Frequency-Enhancing Cycle-GAN improves the quality of the original metalens images by addressing inherent frequency loss introduced by the metalens. In addition to the bidirectional cyclic generative adversarial network, it incorporates a high-frequency adversarial learning module. This module utilizes wavelet transform to extract high-frequency components, and then establishes a high-frequency feedback loop. It enables the generator to enhance the camera outputs by integrating adversarial feedback from the high-frequency discriminator. This ensures that the generator adheres to the constraints imposed by the high-frequency adversarial loss, thereby effectively recovering the camera's frequency loss. This recovery guarantees high-fidelity image output from the camera, facilitating smooth video production. Our camera is capable of achieving dynamic imaging at 125 frames per second with an End Point Error value of 12.58. We also achieve 0.42 for Fréchet Inception Distance, 30.62 for Peak Signal to Noise Ratio, and 0.69 for Structural Similarity in the recorded videos.