Visible Detection Research Articles

Evaluation of large-scale marking with alizarin red S in different age rainbow trout fry for nonlethal field identification

Fry of rainbow trout, Oncorhynchus mykiss (Walbaum, 1792), was subjected to one-hour and four hours immersion in Alizarin red S (ARS) bath 150 mg · L–1. The experiment involved seven age groups (40, 50, 60, 70, 80, 90, and 100 days) and was conducted to estimate the minimal age of salmonids for mass marking with ARS bath enabling subsequent effective, simple field nonlethal identification, based on fin rays checking. The fish were examined at the ages of 200 and 300 days. The results showed a high retention level of ARS traces in caudal fin rays ensured satisfactory visibility and quick detection. A success rate of marking detection was >90% at 200 and 300 days of age and the fish were immersed in ARS solution from 60 days of age (685°D). This treatment provided better results in fish bathed for four hours. Recognition of marks using a laser pointer and protective glasses was successful even in fish, with a 3.5–5.0 times length increase compared to the marking time. The results indicate a high potential for ARS marking and its field identification for juvenile salmonids, which can significantly expand the possibilities of field experiments.

CDYL for infrared and visible light image dense small object detection

To address the phenomenon of many small and hard-to-detect objects in infrared and visible light images, we propose an object detection algorithm CDYL (Convolution to Fully Connect-ed-Deformable Convolution You only Look once) based on the CFC-DC (Convolution to Fully Connected-Deformable Convolution) module. The core operator of CDYL is CFC-DC, making our model not only have a large effective receptive field in infrared and visible light images, but also have adaptive spatial aggregation conditioned by input and task information. As a result, the CDYL reduces the strict inductive bias of traditional CNNs and has long-range dependence for large kernel convolution as well as adaptive spatial aggregation, deeply mining of edge and correlation information in images to enhance sensitivity to small objects, thereby improving performance in dense small object detection tasks. In order to improve the ability of the CFC-DC module to perceive the detailed information of the image, we use the Mish activation function, which has a wider minima which improves the generalization. The effectiveness as well as the generalization of CDYL is evaluated on an infrared image dataset and an UAV image dataset, and it is compared with other state-of-the-art object detection algorithms. Compared to the baseline network YOLOv8l, our model achieved a 3.0% improvement in mAP0.5 in infrared image detection tasks and a 1.1% improvement in mAP0.5 in visible light image detection tasks. The experimental results show that the proposed algorithm achieves superior average precision values on both infrared and visible light images, while maintaining a light weight. Code is publicly available at https://github.com/yangzhu1/CDYL.

2D CuInP2Se6 in High‐Sensitivity UV‐vis And X‐Ray Detection

AbstractMetal thio(seleno)phosphates are renowned for their multifaceted physical characteristics and versatile applications, particularly in optoelectronics. In detection applications, a low and stable dark current is crucial, enhancing the sensitivity and signal‐to‐noise ratio of detectors. Herein, a van der Waals layered material has synthesized, CuInP2Se6. Despite its nanometric scale, 2D CuInP2Se6 detector transcends the conventional absorption inefficiencies tied to ultrathin materials. It delivers exceptional ultraviolet–visible detection, characterized by an ultralow, stable dark current of 150 fA, and a noise power density of 27.7 fA Hz−1/2 at room temperature. The in‐depth investigation reveals a responsivity of 4.47 A W−1, an external quantum efficiency of 1369%, a special detectivity of 1.44 × 1013 Jones, and a rapid response speed of 280 µs, positioning it at the pinnacle of 2D photodetector performance. The CuInP2Se6’s ultralow, stable dark current paves the way for X‐ray detection, achieving an unprecedented sensitivity of 1.32 × 105 µC Gyair−1 cm−2 and a low detection limit of 0.15 µGyair s−1. Furthermore, 2D CuInP2Se6 detector exhibits a remarkable image‐sensing capability, adeptly capturing intricate patterns with high resolution. This discovery indicates its promise in revolutionizing integrated micro/nano optoelectronic devices, opening avenues for advancements in light and X‐ray detection and imaging technologies.

Ultrasensitive and Visible Detection of Influenza A Virus Based on Enzymatic Properties of Layered Gold Nanoparticles

Considering the urgent demand for reliable and rapid detection of infectious respiratory viruses during unpredictable pandemics, an innovative ultrasensitive colorimetric immunoassay for influenza A (H1N1) virus detection is developed herein. The proposed approach leverages dual amplification by combining layer‐by‐layer interactions with the nanozyme effect of biotinylated gold nanoparticles (BGNPs). BGNPs assemble around the target via repeated incubation cycles under optimized conditions, resulting in a layered structure that increases optical density, producing a more intense signal proportional to the viral titer. Additionally, the nanozyme effect of the layered BGNPs induces oxidation of 3,3',5,5'‐tetramethylbenzidine, which further enhances the visible signal detectable by the naked eye. This synergetic nanoprobe‐based system demonstrates remarkable sensitivity, with a limit of detection of 101.29 EID50 mL−1, which is 2500‐fold higher than that of commercial rapid kits and conventional enzyme‐linked immunosorbent assays, within a rapid 55 min timeframe. Furthermore, the anti‐interference capability and portability of the developed system reinforce its practicality, making it a promising tool for field diagnostic tests that offers advanced, ultrasensitive, and early detection of respiratory viruses.

GT-YOLO: Nearshore Infrared Ship Detection Based on Infrared Images

Traditional visible light target detection is usually applied in scenes with good visibility, while the advantage of infrared target detection is that it can detect targets at nighttime and in harsh weather, thus being able to be applied to ship detection in complex sea conditions all day long. However, in coastal areas where the density of ships is high and there is a significant difference in target scale, this can lead to missed detection of some dense and small targets. To address this issue, this paper proposes an improved detection model based on YOLOv5s. Firstly, this article designs a feature fusion module based on a fusion attention mechanism to enhance the feature fusion of the network and introduces SPD-Conv to improve the detection accuracy of small targets and low-resolution images. Secondly, by introducing Soft-NMS, the detection accuracy is improved while also addressing the issue of missed detections in dense occlusion situations. Finally, the improved algorithm in this article increased mAP0.5 by 1%, mAP0.75 by 5.7%, and mAP0.5:0.95 by 5% on the infrared ship dataset. A large number of comparative experiments have shown that the improved algorithm in this article is effective at improving detection capabilities.

Co, Fe Dual-Doped MoS2 Nanosheets on Polypyrrole Microtubes as Effective Peroxidase Mimics for Glutathione Sensing.

Heteroatom doping is considered an effective way to enhance the catalytic activity of MoS2 nanosheets (NSs). In the paper, dual-metal doping was proposed to incorporate Fe and Co into hierarchical MoS2 ultrathin NSs, which grew directly on polypyrrole microtubes (Fe, Co-MoS2@PPy), for the enhanced enzyme-like catalytic reaction. The particular hollow tubular structure realized effective electron transfer. The doped Fe and Co tuned the electronic architecture of the MoS2 NSs to enhance the enzyme-like catalytic activity. The abundant exposed void spaces facilitated ion diffusion/penetration between the PPy interlayer and Fe-Co doped MoS2 shell, leading to heterostructured synergistic effects. Therefore, the synthesized Fe and Co-MoS2@PPy composites showed remarkable catalytic activity. The high catalytic efficiency of Fe and Co-MoS2@PPy was confirmed with the reaction of tetramethylbenzidine (TMB) and H2O2 for visible detection. The blue color disappeared after adding glutathione (GSH). Thus, this procedure was used as a convenient way to detect GSH with a detection limit of 0.76 μM. The dual-metal-doped strategy was confirmed to improve the performance of MoS2 nanocomposites and could be used as a promising matrix for other applications, such as electrochemical energy conversion, medical diagnosis, and others.

Armchair zinc chalcogenide nanoribbons for high-performance photodetectors: A computational study

In this study, we employ density functional theory and non-equilibrium Green's function methods to investigate the electronic and photoelectric response properties of one-dimensional hexagonal ZnX (X = S, Se) nanoribbons (NRs). Remarkably, armchair (ARM) NRs demonstrate superior photoelectric response in the visible and near-ultraviolet regions. It is worth noting that for all considered photon energies, the photocurrent exhibits a cosine dependence on the polarization angle, which is consistent with the photogalvanic effect. when the width of NR is eight atoms, the zinc blende ZnSe/ARM NR-based device achieves a maximum extinction ratio of 63.9 at the photon energy of 3.0 eV. The significant photocurrent and high polarization sensitivity suggest the potential of ZnX NRs for applications in optoelectronic devices, particularly in visible and near-ultraviolet light detection.

Visible detection of chilled beef freshness using a paper-based colourimetric sensor array combining with deep learning algorithms

This study developed an innovative approach that combines a colourimetric sensor array (CSA) composed of twelve pH-response dyes with advanced algorithms, aiming to detect amine gases and assess the freshness of chilled beef. With the assistance of multivariate statistical analysis, the sensor array can effectively distinguish five amine gases and enable rapid quantification of trimethylamine vapour with a limit of detection (LOD) of 8.02 ppb and visually monitor the fresh levels of chilled beef. Moreover, the utilization of deep learning models (ResNet34, VGG16, and GoogleNet) for chilled beef freshness evaluation achieved an overall accuracy of 98.0 %. Furthermore, t-distributed stochastic neighbour embedding (t-SNE) visualized the feature extraction process and provided explanations to understand the classification process of deep learning. The results demonstrated that applying deep learning techniques in the process of pattern recognition of CSA can help in realizing the rapid, robust, and accurate assessment of chilled beef freshness.

16-channel snapshot multispectral imaging based on integrated Fabry Perot microcavity array

<sec>By designing and fabricating a narrow-band Fabry-Perot multi-beam interference spectroscopic microcavity array, and integrating it with a visible light detector focal plane array, we demonstrate a small compact multispectral imaging detector. The micro-cavity filter array with 4×4 basic repeating units and a total of 2048×2048 pixels is obtained on a quartz substrate by the four-fractal combination lithograph-etching process. Then the micro miniatured multispectral imaging detector is formed by fitting with the detector chip. The depth and precision of the etching will determine the distribution and offset of the central wavelength of the narrowband spectral channel respectively. The results show that the etching rate of reactive ion is (3.6 ± 0.2) Å/s, and the process is stable and controllable. Due to the different etching depths, the basic repeating unit forms 16 different levels of steps, and the process achieves the design expectation well.</sec><sec>The results are obtained as follows: the response spectrum peak of the microcavity array sample varies from 520 to 680 nm, the free spectrum range is 160 nm, the full width at the half-peak is less than 10 nm, the transmittance is about 70%, the relative half-width of the transmittance peak at 590 nm is 1.19%, and the waveform coefficient is 2.78. A 16-channel multispectral camera is constructed by using the optical micro-precision assembly device to realize the precise alignment and the fitting of the micro-cavity filter array and the image sensor. Xenon lamp and monochromator are used as tunable wavelength monochromatic cooperative light source to detect the effect of 16-channel snapshot multispectral imaging on a pixel scale. The results show that the multispectral imaging detector has 16 different narrow-band response spectra. The characteristic spectrum of the target can be clearly distinguished by spectral channel.</sec><sec>When imaging the target with known spectral characteristics, for a certain frame of multi-spectral image, selecting a suitable spectral channel can eliminate the background in the field of view through image subtraction and improve the contrast of the target. In the dark room condition, we take the LED light source with center wavelength varying in a range between 528 and 589 nm as the target (the wavelength coincides with the working wavelength of the spectral channel), and effectively suppress the background through the spectral differential intensity subtraction, which can improve the accuracy and sensitivity of the target capture. The 16-channel snapshot multi-spectral imaging detector based on integrated Fabry-Perot microcavity array has the advantages of small size, high integration and strong environmental adaptability, and is expected to play a role in realizing the real-time detection of weak moving targets, auxiliary diagnosis of skin surface observation, and high dynamic range imaging of target observation under backlight conditions.</sec>

Enhanced exciton-phonon coupling in pseudohalide 2D perovskite for X-ray to visible light detection.

Two-dimensional Cs2Pb(SCN)2I2 perovskite has an ultra-small interlayer spacing, inducing a series of interesting semiconductor properties, such as efficient interlayer carrier transport as well as lower exciton binding energy compared to perovskites with long alkylammonium cations. The prepared Cs2Pb(SCN)2I2 photodetector achieves a high on/off ratio of 2.1 × 104 with a specific detectivity of 6.2 × 1011 jones to 450 nm visible light, and a high sensitivity of 2747 μC Gyair-1 cm-2 to X-rays.

Visible ozone detection and removal in two-dimensional Mn(ii)-based metal–organic frameworks

Highly stable and hydrophobic two-dimensional Mn(ii)-based MOFs effectively detect and remove trace O3 with discernible color change as the response.

Role of Quantum Dots and Nanostructures in Photovoltaic Energy Conversion

Nanostructures and quantum dots have substantial effects on enhancing photovoltaic energy conversion efficiency, as evidenced in this comprehensive study. Materials that are nanostructured and nanosized particles are commonly used to address the urgent issues related to energy conversion. The use of nanostructured substances to address issues with energy and natural resources has garnered a lot of interest lately. Directional nanostructures in particular show promise for the conversion, collection, and storage of energy. Due to their unique properties, such as electrical conductivity, mechanical energy, and photoluminescence, quantum dots made from carbon (CQDs) and graphene quantum dots (GQDs) have been integrated into hybrid photovoltaic-thermoelectric systems (PV-TE). It evaluates the effects of nanostructures on solar energy technologies, in particular how they can improve power conversion and light absorption in solar cells. Optical light detectors, which transform photonic energy into signals that are electrical, are among the many optoelectronic uses of CQDs that have drawn attention because they are essential components of contemporary imaging and communication systems, such as visible light cameras, machine vision, medical X-ray and near-infrared image processing, and visible light detection devices. Besides supercapacitors, the study investigates how nanostructures could play a crucial role in contributing to addressing the global energy crisis sustainably, by working as photocatalysts for hydrogen synthesis and supercapacitors.

Two new Cd-based metal–organic frameworks for afterglow detection of Fe3+ and NH3

The present study showcases two Cd-based MOFs that exhibit potential as afterglow probes for the “turn off” and “turn on” detection of Fe3+ ions and NH3, respectively.

Barely visible impact damage detection and location on a real scale curved CFRP fuselage panel with optical fibre Bragg grating sensors

Current CFRP aircraft structures can suffer from barely visible impact damage (BVID). These BVIDs can grow due to the operational loads applied on the damaged structure and can eventually even compromise their load-bearing functionality. To detect these BVIDs as soon as possible, aircraft are frequently submitted to on-ground inspections, which increase downtimes and associated costs. A permanently installed sensor network could overcome these shortcomings. Optical fibre sensors have been proposed as possible candidates for such networks owing to their light weight, their small diameter, and their immunity to electromagnetic interference. In this work we use a network of four flight-compatible optical fibres, with a total of 120 fibre Bragg grating (FBG) sensors, to monitor the damage-prone stiffener feet on a large curved CFRP panel of 5 × 3 m2. We created BVIDs of calibrated size at the damage-prone locations and we use the response of all 120 sensors to detect and locate the BVIDs. To do so, we first consider temperature effects between the baseline and inspection measurement, and second, we quantify the health of the component based on all sensor readings and test it against a damage threshold.

Highly selective, sensitive, and visible detection of fluoride ions through transforming their roles from reactants to catalysts in the silicon corrosion reaction

Transforming fluoride ions from reactants to catalysts in the silicon corrosion reaction enables their detection at high selectivity and sensitivity.

Study on the Combination of Multi-wavelength Calibration and Liquid Chromatography with UV–Vis Detector for the Determination of the Synthetic Dye Sunset Yellow FCF in Soft Drinks

Study on the Combination of Multi-wavelength Calibration and Liquid Chromatography with UV–Vis Detector for the Determination of the Synthetic Dye Sunset Yellow FCF in Soft Drinks

Research on Pedestrian Detection Based on Multimodal Infor-mation Fusion

Aiming at the matter that pedestrian detection in the autonomous driving system is vulnerable to the influence of the external environment and the detector supported single sensor modal detector has poor performance beneath the condition of enormous amendment of unrestricted light-weight, this paper proposes a fusion of light and thermal infrared dual mode pedestrian detection methodology. Firstly, 1 × 1 convolution and expanded convolution square measure are introduced within the residual network, and also the ROI Align methodology is employed to exchange the ROI Pooling method-ology to map the candidate box to the feature layer to optimize the Faster R-CNN. Secondly, the loss performance of the generalized intersection over union (GIoU) is employed because of the loss performance of the prediction box positioning regression; finally, supported by the improved Faster R-CNN, four forms of multimodal neural network structures square measure designed to fuse visible and thermal infrared pictures. According to experimental findings, the proposed technique outperforms current mainstream detection algorithms on the KAIST dataset. As compared to the conventional ACF + T + THOG pedestrian detector, the AP is 8.38 percentage points greater. Compared to the visible light pedestrian detector, the miss rate is 5.34 percentage points lower.

Asphalt pavement crack detection based on infrared thermography and deep learning

ABSTRACT The current intelligent detection of asphalt pavement cracks relies on visible images, which are ineffective in handling temporary shadow and reflection. In contrast, infrared images reflect thermal radiation intensity, making them suitable for crack detection by mitigating environmental interference. The GSkYOLOv5 method is proposed in this study for accurate crack detection in infrared images of asphalt pavement. Firstly, an infrared dataset consisting of 2400 images of asphalt pavement cracks was captured and produced, including three types of cracks – strip cracks, cross cracks and reticular cracks. And the imbalanced samples were balanced using generative adversarial networks. Secondly, GhostNet and Selective Kernel Networks were added to enhance crack information perception, and the SPPF module was replaced to improve feature learning for different scale cracks. Lastly, GSkYOLOv5 was tested with a self-built infrared dataset of asphalt pavement cracks. GSkYOLOv5 improved detection accuracy by 4.7% and recall rate by 1.3% compared to YOLOv5s, outperforming the other tested algorithms. This method can be combined with visible image-based crack detection for comprehensive intelligent detection of asphalt pavement cracks using dual lenses for visible and infrared images.

Fully Flexible Yarn-Based Phototransistors for UV–Visible Light Detection

Fully Flexible Yarn-Based Phototransistors for UV–Visible Light Detection

Enhancing broad-band light and CO gas sensing with BDT/ZnO nanocomposites

Gas/light dual sensors based on benzodithiophene-based derivates (BDT)/zinc oxide (ZnO) nanocomposites are fabricated for the monitoring of hazardous light and the detection of toxic gases. The lethal threat posed by colorless and odorless carbon monoxide (CO) gas, as well as the potential dangers of ultraviolet-A (UV-A) and visible light, emphasize the need for sensitive and portable gas/light dual sensor. Organic BDT/inorganic ZnO hybrid materials have gained attention for their cost-effectiveness, and enhanced gas/light sensing performance. This study explores the incorporation of the organic material, BDT, onto the ZnO nanorods (NRs) to enhance the UV and visible light detection, and CO gas sensing capabilities. The results demonstrate that improved light absorption and gas detection are attributed to the broad absorption wavelength range of BDT and efficient charge transfer from BDT to ZnO NRs. The study introduces a novel approach for dual sensing applications, highlighting the promising future of BDT/ZnO nanocomposites in environmental monitoring and wearable devices.