Optical Review最新文献

Near-infrared spectroscopy and imaging using scattered light potentially evaluate the structural properties of the medium, like the average particle size, based on a relation between its structure and light scattering. A qualitative understanding of light scattering is crucial for developing optical imaging techniques. The scattering properties of dense colloidal suspensions have been extensively investigated using the electromagnetic theory (EMT). The colloidal suspensions are widely used in liquid tissue phantoms for optical imaging techniques and are encountered in various fields, such as the food and chemical industries. The interference between electric fields scattered by colloidal particles significantly influences the scattering properties, so-called the interference effects. Despite many efforts since the 1980s, a complete understanding of the interference effects has still not been achieved. The main reason is the complicated dependence of the interference on the optical wavelength, particle size, and so on. This paper briefly reviews numerical and theoretical studies of the interference effect based on the dependent scattering theory, one of the EMTs, and model equations.

We numerically and experimentally developed a cantilever that provided both fast and analog actuation for THz metamaterials (MMs) by properly geometrizing a dimpled tip. Owing to its small size and light mass, the cantilever had a high mechanical resonance at 705 kHz. Cantilever arrays were fabricated with different tip gaps and integrated into a ladder-shaped MM (LS-MM). By changing the tip gap from 0.80 to 0.32 μm, the resonance of the transmittance spectrum changed from 1.235 to 0.795 THz, indicating that the reconfigurable LS-MM was capable of continuously tuning the resonance of the THz wave transmission with the tip gap. Additionally, the dimple served as an anti-stiction structure, providing the cantilever with a fabrication yield of 99.8%. This work shows a practical pathway to high-performance active metamaterials, which holds potential in advanced THz technologies such as 6G communications and fast imaging.

Imaging is a longstanding research topic in optics and photonics and is an important tool for a wide range of scientific and engineering fields. Computational imaging is a powerful framework for designing innovative imaging systems by incorporating signal processing into optics. Conventional approaches involve individually designed optical and signal processing systems, which unnecessarily increased costs. Computational imaging, on the other hand, enhances the imaging performance of optical systems, visualizes invisible targets, and minimizes optical hardware. Digital holography and computer-generated holography are the roots of this field. Recent advances in information science, such as deep learning, and increasing computational power have rapidly driven computational imaging and have resulted in the reinvention these imaging technologies. In this paper, I survey recent research topics in computational imaging, where optical randomness is key. Imaging through scattering media, non-interferometric quantitative phase imaging, and real-time computer-generated holography are representative examples. These recent optical sensing and control technologies will serve as the foundations of next-generation imaging systems in various fields, such as biomedicine, security, and astronomy.

Increasing the sensitivity of image sensors is a major challenge for current imaging technology. Researchers are tackling it because highly sensitive sensors enable objects to be recognized even in dark environments, which is critical for today’s smartphones, wearable devices, and automobiles. Unfortunately, conventional image-sensor architectures use light-absorptive color filters on every pixel, which fundamentally limits the detected light power per pixel. Recent advances in optical metasurfaces have led to the creation of pixelated light-transmissive color splitters with the potential to enhance sensor sensitivity. These metasurfaces can be used instead of color filters to distinguish primary colors, and unlike color filters, they can direct almost all of the incident light to the photodetectors, thereby maximizing the detectable light power. This review focuses on such metasurface-based color splitters enabling high-sensitivity color-image sensors. Their underlying principles are introduced with a focus on dispersion engineering. Then, their capabilities as optical elements are assessed on the basis of our recent findings. Finally, it is discussed how they can be used to create high-sensitivity color-image sensors.

UV curing hybrid materials via the photo polymerization have significant significance for the lithography fields due to the high resolution. In this work, the UV-curable SiO₂ materials with chelating compound structure are synthesized by photosensitive Sol–Gel approach, which have a wide absorption band at 267 nm. With the UV light irradiation, the chelating compound structure decomposes and the solubility of the film in organic solvent decreases. Based on this premise, the presented material exhibits the ability to fabricating highly ordered SiO₂ microarrays on several substrates through UV photolithography. The SiO₂ micro arrays can be used to as templates to prepare noble metal micro-structures, which own wide potential application prospects in highly ordered SERS substrates with high activity and reproductivity for trace detection.

This paper focuses on the channel impairments separability of two histogram-based features, asynchronous amplitude histograms (AAH) and asynchronous delay-tap plot (ADTP), commonly used in direct-detection optical performance monitoring (OPM) techniques. This paper presents an in-depth study of the conditions under which these two histogram features are applicable in OPM. These high-dimensional features, AAH and ADTP, are dimensionally reduced using a state-of-the-art data visualization algorithm called Uniform Manifold Approximation and Projection (UMAP) algorithm. After data visualization, it can be found these two histogram-based features have some limitations in distinguishing between different levels of impairments in some specific cases. These features cannot achieve high accuracy in monitoring optical performance in these given situations, no matter how complex the classifier is designed. Extensive simulation experiments were performed to study the classification performance of the two histogram features in the single and multiple impairments cases. The results show that both AAH and ADTP can be used to monitor cumulative dispersion (CD) and optical signal to noise ratio (OSNR) in the case of the single impairment. In addition, the monitoring performance of both features is better for dispersion in the case of multiple impairments coexistence, while both have limitations for OSNR monitoring. However, the anti-dispersion interference ability of ADTP is better than that of AAH. The plausibility of the study results is verified by estimating the channel impairments under different conditions using a deep neural network-based (DNN) identifier. The impairments separation visualization results of UMAP are highly consistent with the estimation results of the DNN-based classifier, achieving the interconnection of usefulness and practicality.