Recent Advances in Vertically Aligned Nanowires for Photonics Applications

Over the past few decades, nanowires have arisen as a centerpiece in various fields of application from electronics to photonics, and, recently, even in bio-devices. Vertically aligned nanowires are a particularly decent example of commercially manufacturable nanostructures with regard to its packing fraction and matured fabrication techniques, which is promising for mass-production and low fabrication cost. Here, we track recent advances in vertically aligned nanowires focused in the area of photonics applications. Begin with the core optical properties in nanowires, this review mainly highlights the photonics applications such as light-emitting diodes, lasers, spectral filters, structural coloration and artificial retina using vertically aligned nanowires with the essential fabrication methods based on top-down and bottom-up approaches. Finally, the remaining challenges will be briefly discussed to provide future directions

Wide Field-of-View, High-Resolution Endoscopic Lens Design with Low F-Number for Disposable Endoscopy

In the past few decades, video endoscopy has become one of the primary medical devices in diverse clinical fields for examination, treatment, and early disease diagnosis of the gastrointestinal tract. For an accurate diagnosis, an endoscopic camera offering bright and wide field-of-view images is required while maintaining its compact dimensions to enter the long, narrow, and dark tract inside of the body. Recent endoscopic lenses successfully provide wide fields-of-view and have compact sizes for the system; however, their f-numbers still remain at 2.8 or higher. Therefore, further improvement in f-numbers is required to compensate for the restricted illumination system of the endoscopic probe. Here, we present a low f-number endoscopic lens design while providing wide field-of-view and high-resolution imaging. The proposed lens system achieved a low f-number of 2.2 and a field-of-view of 140 deg. The modulation transfer function (MTF) is over 20% at 180 lp/mm, and relative illumination is more than 60% in the full field. Additionally, the proposed lens is designed for a 1/4” 5-megapixel complementary metal-oxide-semiconductor (CMOS) image sensor with a pixel size of 1.4 µm. This all-plastic lens design could help develop a high-performance disposable endoscope that prevents the risk of infection or cross-contamination with mass manufacture and low cost

Advanced visual components inspired by animal eyes

Artificial vision systems pervade our daily lives as a foremost sensing apparatus in various digital technologies, from smartphones to autonomous cars and robotics. The broad range of applications for conventional vision systems requires facile adaptation under extreme and dynamic visual environments. However, these current needs have complicated individual visual components for high-quality image acquisition and processing, which indeed leads to a decline in efficiency in the overall system. Here, we review recent advancements in visual components for high-performance visual processing based on strategies of biological eyes that execute diverse imaging functionalities and sophisticated visual processes with simple and concise ocular structures. This review first covers the structures and functions of biological eyes (i.e., single-lens eyes and compound eyes), which contain micro-optic components and nanophotonic structures. After that, we focus on their inspirations in imaging optics/photonics, light-trapping and filtering components, and retinomorphic devices. We discuss the remaining challenges and notable biological structures waiting to be implemented

Evolution of natural eyes and biomimetic imaging devices for effective image acquisition

In the natural evolutionary process, biological creatures have developed diverse visual structures apt for their habitational environments. These natural vision structures have inspired the development of artificial vision systems. These systems have numerous advantages in image acquisition compared to conventional imaging devices, including high visual acuity, motion sensitivity, simple accommodation, and low optical aberration. These advantages have contributed to the advances of various imaging devices for autonomous vehicles, mobile electronics, visual prostheses, and machine vision systems. Here, we reviewed recent advances in bio-inspired artificial vision systems that have mimicked the optical and retinal advantages of natural vision structures. These artificial vision systems have overcome many critical challenges in conventional image systems and presented potential for the next-generation image acquisition systems. The remaining challenges and the future outlook are also briefly described in the conclusion section.11Nsciescopu

Vari-Focal Light Field Camera for Extended Depth of Field

The light field camera provides a robust way to capture both spatial and angular information within a single shot. One of its important applications is in 3D depth sensing, which can extract depth information from the acquired scene. However, conventional light field cameras suffer from shallow depth of field (DoF). Here, a vari-focal light field camera (VF-LFC) with an extended DoF is newly proposed for mid-range 3D depth sensing applications. As a main lens of the system, a vari-focal lens with four different focal lengths is adopted to extend the DoF up to ~15 m. The focal length of the micro-lens array (MLA) is optimized by considering the DoF both in the image plane and in the object plane for each focal length. By dividing measurement regions with each focal length, depth estimation with high reliability is available within the entire DoF. The proposed VF-LFC is evaluated by the disparity data extracted from images with different distances. Moreover, the depth measurement in an outdoor environment demonstrates that our VF-LFC could be applied in various fields such as delivery robots, autonomous vehicles, and remote sensing drones

Bio-Inspired Artificial Vision and Neuromorphic Image Processing Devices

Remarkable technological developments for efficient image recognition (i.e., image acquisition and image data processing) have been reported in the past decade. Such advances in imaging and image processing technologies have driven significant progress in mobile electronics and machine vision applications. In particular, for image acquisition devices, two types of natural eyes (i.e., chambered and compound eyes) have inspired the development of novel multifunctional imaging devices with unique optical geometries. For image data processing devices, novel computing devices based on memristor crossbar arrays, such as electronic synapses, have been developed. More recently, the integration of imaging and image processing devices in a single unit further enhances the system-level efficiency. Herein, such recent advances in the bio-inspired artificial vision and neuromorphic image processing devices, aimed at providing efficient image recognition, are reviewed. First, various imaging devices inspired by the structural and functional features of natural eyes are introduced. Second, artificial synapses and their operation principles are thoroughly discussed. Third, the neuromorphic vision sensor that integrates the imaging and image processing devices is reviewed. Finally, a brief summary and future outlook are presented.

Attention-based solubility prediction of polysulfide and electrolyte analysis for lithium–sulfur batteries

Abstract During the continuous charge and discharge process in lithium-sulfur batteries, one of the next-generation batteries, polysulfides are generated in the battery’s electrolyte, and impact its performance in terms of power and capacity by involving the process. The amount of polysulfides in the electrolyte could be estimated by the change of the Gibbs free energy of the electrolyte, $$\Delta _{mix}\textrm{G}$$ Δ mix G in the presence of polysulfide. However, obtaining $$\Delta _{mix}\textrm{G}$$ Δ mix G of the diverse mixtures of components in the electrolyte is a complex and expensive task that shows itself as a bottleneck in optimization of electrolytes. In this work, we present a machine-learning approach for predicting $$\Delta _{mix}\textrm{G}$$ Δ mix G of electrolytes. The proposed architecture utilizes (1) an attention-based model (Attentive FP), a contrastive learning model (MolCLR) or morgan fingerprints to represent chemical components, and (2) transformers to account for the interactions between chemicals in the electrolyte. This architecture was not only capable of predicting electrolyte properties, including those of chemicals not used during training, but also providing insights into chemical interactions within electrolytes. It revealed that interactions with other chemicals relate to the logP and molecular weight of the chemicals

Cuttlefish eye-inspired artificial vision for high-quality imaging under uneven illumination conditions

With the rise of mobile robotics, including self-driving automobiles and drones, developing artificial vision for high-contrast and high-acuity imaging in vertically uneven illumination conditions has become an important goal. In such situations, balancing uneven illumination, improving image contrast for facile object detection, and achieving high visual acuity in the main visual fields are key requirements. Meanwhile, in nature, cuttlefish (genus Sepia) have evolved an eye optimized for vertically uneven illumination conditions, which consists of a W-shaped pupil, a single spherical lens, and a curved retina with a high-density photoreceptor arrangement and polarized light sensitivity. Here, inspired by the cuttlefish eye, we report an artificial vision system consisting of a W-shaped pupil, a single ball lens, a surface-integrated flexible polarizer, and a cylindrical silicon photodiode array with a locally densified pixel arrangement. The W-shaped pupil integrated on the ball lens balances vertically uneven illumination, and the cylindrical silicon photodiode array integrated with the flexible polarizer enables high-contrast and high-acuity imaging.N

Full‐Control and Switching of Optical Fano Resonance by Continuum State Engineering

Abstract Fano resonance, known for its unique asymmetric line shape, has gained significant attention in photonics, particularly in sensing applications. However, it remains difficult to achieve controllable Fano parameters with a simple geometric structure. Here, a novel approach of using a thin‐film optical Fano resonator with a porous layer to generate entire spectral shapes from quasi‐Lorentzian to Lorentzian to Fano is proposed and experimentally demonstrated. The glancing angle deposition technique is utilized to create a polarization‐dependent Fano resonator. By altering the linear polarization between s‐ and p‐polarization, a switchable Fano device between quasi‐Lorentz state and negative Fano state is demonstrated. This change in spectral shape is advantageous for detecting materials with a low‐refractive index. A bio‐particle sensing experiment is conducted that demonstrates an enhanced signal‐to‐noise ratio and prediction accuracy. Finally, the challenge of optimizing the film‐based Fano resonator due to intricate interplay among numerous parameters, including layer thicknesses, porosity, and materials selection, is addressed. The inverse design tool is developed based on a multilayer perceptron model that allows fast computation for all ranges of Fano parameters. The method provides improved accuracy of the mean validation factor (MVF = 0.07, q‐q') compared to the conventional exhaustive enumeration method (MVF = 0.37)