Search Results (237)

Bird-dropping fouling and hotspot anomalies remain the most prevalent and detrimental defects in utility-scale photovoltaic (PV) plants; their co-occurrence on a single module markedly curbs energy yield and accelerates irreversible cell degradation. However, markedly disparate visual–thermal signatures of the two phenomena impede high-fidelity concurrent detection in existing robotic inspection systems, while stringent onboard compute budgets also preclude the adoption of bulky detectors. To resolve this accuracy–efficiency trade-off for dual-defect detection, we present YOLOv8-SG, a lightweight yet powerful framework engineered for mobile PV inspectors. First, a rigorously curated multi-modal dataset—RGB for stains and long-wave infrared for hotspots—is assembled to enforce robust cross-domain representation learning. Second, the HSV color space is leveraged to disentangle chromatic and luminance cues, thereby stabilizing appearance variations across sensors. Third, a single-head self-attention (SHSA) block is embedded in the backbone to harvest long-range dependencies at negligible parameter cost, while a global context (GC) module is grafted onto the detection head to amplify fine-grained semantic cues. Finally, an auxiliary bounding box refinement term is appended to the loss to hasten convergence and tighten localization. Extensive field experiments demonstrate that YOLOv8-SG attains 86.8% mAP@0.5, surpassing the vanilla YOLOv8 by 2.7 pp while trimming 12.6% of parameters (18.8 MB). Grad-CAM saliency maps corroborate that the model’s attention consistently coincides with defect regions, underscoring its interpretability. The proposed method, therefore, furnishes PV operators with a practical low-latency solution for concurrent bird-dropping and hotspot surveillance. Full article

This study aims to develop a stress-optimized ultra-broadband beam-splitting coating that integrates four spectral bands by analyzing the beam-splitting properties of coatings spanning visible to medium and long-wave infrared regions. A beam-splitting coating was deposited on a Ge substrate using ion-beam-assisted thermal evaporation, employing Ge, ZnS, and YbF₃ as coating materials. The designed coating exhibits high reflectance in the 0.5–0.8 μm and 0.9–1.7 μm wavelength bands while maintaining high transmittance in the 3–5 μm and 8–12 μm bands. The optimal deposition process for a single-layer coating was established, at a 45° incidence angle, the beam-splitting coating achieved an average reflectance (Rave) of 86.6% in the 0.9–1.7 μm band and 93.7% in the 0.9–1.7 μm band, alongside an average transmittance (Tave) of 91.36% in the 3–5 μm band and 91.3% in the 8–12 μm band. The antireflection coating achieved a single-side Tave of 98.5% in the 3–5 μm band and 97% in the 8–12 μm band. The coating uniformity exceeded 99.6%. To optimize the surface profile, a single-layer Ge coating was added to the rear surface, resulting in a root mean square deviation of less than 0.0007 μm, achieved the same precision of the surface profile successfully. The deposited beam-splitting coating possessed high surface profile precision, and successfully achieved high reflectance in the visible to short-wave infrared range and high transmittance in the medium- and long-wave infrared range. The coating demonstrated excellent adhesion, abrasion resistance, and structural integrity, with no wrinkling, cracking, or delamination. Full article

The generation of hot electrons through non-radiative decay processes of surface plasmons (SPs) has been extensively demonstrated, enabling the preparation of high-performance hot-electron photodetectors without limitations imposed by material band gap widths. In this paper, a near-infrared wideband hot-electron metal semiconductor photodetector (WHEMSPD) is proposed based on a metal grating plasmonic structure, and its optical and electrical properties are numerically verified. This structure exhibits excellent broadband characteristics within the long-wave near-infrared range (LW-NIR) of 1200–1800 nm, achieving an absorption of approximately 0.7 between 1200 and 1700 nm, with a peak of 0.98 at 1400 nm. The metal grating structure can effectively enhance the excitation of plasmons on the surface and thus increase the absorption within a larger bandwidth. In terms of electrical performance, the responsivity of the WHEMSPD reaches over 20 mA/W within the wavelength range of 1200–1500 nm, with the peak responsivity reaching 28.3 mA/W around 1320 nm. WHEMSPDs in the LW-NIR can be widely used in military, remote sensing, communication, and other related fields. Full article

To address the application demands of ultra-wide-field optical systems, we developed a compact, long-infrared waveband optical system using a field-of-view (FoV) stitching method. This system features a refractive–reflective hybrid structure, with the reflective pathway expanding the FoV and the refractive pathway employing germanium to correct field defects and aberrations. By stitching the FoVs of the two structures, we achieved an ultra-wide-field long-infrared-waveband imaging system over a range of 0°~190°, with an operational wavelength range of 8.7~11.5 μm. The system exhibits excellent imaging performance, with a modulation transfer function (MTF) exceeding 0.5 at 17 lp/mm, the blur spot remaining within the airy disk limit, and the energy concentration exceeding 60% at 15 μm: the tolerance design meets the imaging requirements. Additionally, the system maintains stable image quality within the temperature range of −20 °C~60 °C. The design offers excellent imaging quality, high design flexibility, good real-time performance, compact size, and low economic cost, providing an effective optical structure and realization strategy for ultra-wide-field imaging systems. Full article

Long-wave infrared (LWIR) broadband absorption is of great significance in science and technology. The electromagnetic field energy is absorbed by the metamaterials material, leading to the enhanced light absorption, from which the Metal–Dielectric–Metal (MDM) structure is designed. FDTD simulation calculation indicate that the bandwidth within which the absorber absorption ratio greater than 90% is 11.04 μm, and the average absorption rate (9.10~20.14 μm) is 93.6%, which can be accounted for by the impedance matching theory. Upon the matching of the impedance of the metamaterial absorber with the impedance of the incident light, the light reflection is reduced to a minimum, and increase the absorption ratio. Meanwhile, the good incidence angle unsensitivity due to the metasurface structural symmetry and the characteristics of the electromagnetic field distribution at different incidence angles. Due to the form regularity of the nanoring–nanowire metasurface structure, the light acts similar in different polarization directions, and the surface plasmon resonance plays a key role. Using FDTD electromagnetic field analysis to visualize the electric field and magnetic field strength distribution within the absorber, the electromagnetic field at the interface in the nanoring–nanowire metasurface structure, promote the surface plasmon resonance and interaction with damaged materials, and improve the light absorption efficiency. Moreover, the different microstructures and the electrical and optical properties of different top materials affect the light absorption. Meanwhile, adjusting the absorption layer thickness and periodic geometry parameters will also change the absorption spectrum. The absorber has high practical value in thermal electronic devices, infrared imaging, and thermal detection. Full article

When objects are obscured by shadows or dim surroundings, image quality is improved by fusing near-infrared and visible-light images. At night, when visible and NIR lights are insufficient, long-wave infrared (LWIR) imaging can be utilized, necessitating the attachment of a visible-light sensor to an LWIR camera to simultaneously capture both LWIR and visible-light images. This camera configuration enables the acquisition of infrared images at various wavelengths depending on the time of day. To effectively fuse clear visible regions from the visible-light spectrum with those from the LWIR spectrum, a multi-band fusion method is proposed. The proposed fusion process subsequently combines detailed information from infrared and visible-light images, enhancing object visibility. Additionally, this process compensates for color differences in visible-light images, resulting in a natural and visually consistent output. The fused images are further enhanced using a night-to-day image translation module, which improves overall brightness and reduces noise. This night-to-day translation module is a trained CycleGAN-based module that adjusts object brightness in nighttime images to levels comparable to daytime images. The effectiveness and superiority of the proposed method are validated using image quality metrics. The proposed method significantly contributes to image enhancement, achieving the best average scores compared to other methods, with a BRISQUE of 30.426 and a PIQE of 22.186. This study improves the accuracy of human and object recognition in CCTV systems and provides a potential image-processing tool for autonomous vehicles. Full article

This study’s field observations of Light Source Efficiency (LSE) in the Taklamakan Desert have unveiled significant daily average variations across different wavelengths, with LSE values ranging from 0.827 at 9.1 μm to a peak of 0.969 at 12.1 μm, and notably, a substantial daily variation (DV) of Δε = 0.080 in the 14.3 μm band. These findings underscore the necessity for wavelength-specific analysis in LSE research, which is crucial for enhancing the precision of remote sensing applications and climate models. This study’s high-temporal-resolution FTIR field observations systematically reveal the diurnal dynamics of infrared surface emissivity in the desert for the first time, challenging existing satellite-based inversion products and highlighting the limitations of traditional temperature–emissivity separation algorithms in arid regions. The diurnal fluctuations are governed by three primary mechanisms: the amplification of lattice vibrations in quartz minerals under high daytime temperatures, changes in the surface topography due to thermal expansion and contraction, and nocturnal radiative cooling effects. The lack of a significant correlation between environmental parameters and the emissivity change rate suggests that microclimate factors play a dominant indirect regulatory role. Model comparisons indicate that sinusoidal functions outperform polynomial fits across most wavelengths, especially at 12.1 μm, confirming the significant influence of diurnal forcing. The high sensitivity of the 14.3 μm band makes it an ideal indicator for monitoring desert surface–atmosphere interactions. This study provides three key insights for remote sensing applications: the development of dynamic emissivity correction schemes, the prioritization of the long-wave infrared band for surface temperature inversion in arid regions, and the integration of ground-based observations with geostationary high-spectral data to construct spatiotemporally continuous emissivity models. Future research should focus on multi-angle observation experiments and the exploration of machine learning’s potential in cross-scale emissivity modeling. Full article

Automotive reflectors used in headlamps and rear lamps are typically made of polycarbonate. However, this polymer has low light reflectivity. To enhance its reflective properties, it undergoes a metallization process, which significantly increases production costs. Therefore, it is of interest to develop polymers that do not require metallization for the manufacturing of automotive reflectors. In this regard, the use of polycarbonate reinforced with titanium dioxide nanoparticles may be an alternative. Studies indicate that incorporating these nanoparticles can improve the degradation temperature and mechanical properties of the composites. In the case of automotive reflectors, in addition to degradation due to temperature, it is crucial to assess the thermal diffusivity and reflectivity of these composites, thus ensuring the lighting performance of the component. Studies on such characteristics in polycarbonates with titanium dioxide nanoparticles are mostly limited to investigations of hardness and optical properties using Raman and UV–Vis spectroscopy tests. This article investigates the thermal and lighting performance of polycarbonate (PC) samples with 10 wt% titanium dioxide (TiO₂) nanoparticles and automotive reflectors with the same chemical composition. The thermal stability of PC and PC-10%TiO₂ was analyzed by thermogravimetry (TGA), whereas the reflectors were evaluated using active infrared thermography. Spectral thermographic analysis in the mid- and long-wave infrared range provided thermal diffusivity data for the polycarbonates and offered important insights into their optical behavior under operational conditions (up to 70 °C). Furthermore, illumination tests were conducted on PC-10%TiO₂, using metalized polymeric reflectors commonly employed in the automotive industry as a reference. The TGA results showed that incorporating 10 wt% TiO₂ into PC increased the degradation temperature from 167 °C to 495 °C. The long-wave infrared emissivity of PC-10%TiO₂ (averaging 0.96) was 3% lower than that of polycarbonate. PC-10%TiO₂ exhibited a thermal diffusivity of 0.20 mm²/s, which was 28.6% lower than that of PC, indicating greater thermal inertia due to the presence of nanoparticles. The lighting performance of the PC-10%TiO₂ reflector was on average 4% lower than that of a commercially available metallized polycarbonate reflector. However, for automotive reflectors, this value meets the sector’s regulatory criteria. These findings suggest that PC-10%TiO₂ has potential for use in the production of internal vehicle lighting reflectors, without significantly compromising light reflectivity, while offering the advantages of thermal stability and reduced heating around the reflector. Full article

The sea surface displays dynamic characteristics, such as waves and various formations. As a result, images of the sea surface usually have few stable feature points, with a background that is often complex and variable. Moreover, the sea surface undergoes significant changes due to variations in wind speed, lighting conditions, weather, and other environmental factors, resulting in considerable discrepancies between images. These variations present challenges for identification using traditional methods. This paper introduces an algorithm based on the phase-consistency model. We utilize image data collected from a specific maritime area with a high-frame-rate surface array infrared camera. By accurately detecting images with identical names, we focus on the subtle texture information of the sea surface and its rotational invariance, enhancing the accuracy and robustness of the matching algorithm. We begin by constructing a nonlinear scale space using a nonlinear diffusion method. Maximum and minimum moments are generated using an odd symmetric Log–Gabor filter within the two-dimensional phase-consistency model. Next, we identify extremum points in the anisotropic weighted moment space. We use the phase-consistency feature values as image gradient features and develop feature descriptors based on the Log–Gabor filter that are insensitive to scale and rotation. Finally, we employ Euclidean distance as the similarity measure for initial matching, align the feature descriptors, and remove false matches using the fast sample consensus (FSC) algorithm. Our findings indicate that the proposed algorithm significantly improves upon traditional feature-matching methods in overall efficacy. Specifically, the average number of matching points for long-wave infrared images is 1147, while for mid-wave infrared images, it increases to 8241. Additionally, the root mean square error (RMSE) fluctuations for both image types remain stable, averaging 1.5. The proposed algorithm also enhances the rotation invariance of image matching, achieving satisfactory results even at significant rotation angles. Full article

Division-of-focal-plane (DoFP) polarization imaging systems have demonstrated considerable promise in target detection and tracking in complex backgrounds. However, existing methods face challenges, including dependence on complex image preprocessing procedures and limited real-time performance. To address these issues, this study presents a novel histogram of polarization gradient (HPG) feature descriptor that enables efficient feature representation of polarization mosaic images. First, a polarization distance calculation model based on normalized cross-correlation (NCC) and local variance is constructed, which enhances the robustness of gradient feature extraction through dynamic weight adjustment. Second, a sparse Laplacian filter is introduced to achieve refined gradient feature representation. Subsequently, adaptive polarization channel correlation weights and the second-order gradient are utilized to reconstruct the degree of linear polarization (DoLP). Finally, the gradient and DoLP sign information are ingeniously integrated to enhance the capability of directional expression, thus providing a new theoretical perspective for polarization mosaic image structure analysis. The experimental results obtained using a self-developed long-wave infrared DoFP polarization thermal imaging system demonstrate that, within the same FBACF tracking framework, the proposed HPG feature descriptor significantly outperforms traditional grayscale {8.22%, 2.93%}, histogram of oriented gradient (HOG) {5.86%, 2.41%}, and mosaic gradient histogram (MGH) {27.19%, 18.11%} feature descriptors in terms of precision and success rate. The processing speed of approximately 20 fps meets the requirements for real-time tracking applications, providing a novel technical solution for polarization imaging applications. Full article

Colloidal quantum dots (QDs) have emerged as promising materials for the development of infrared photodetectors owing to their tunable band gaps, cost-effective manufacturing, and ease of processing. This paper provides a comprehensive overview of the fundamental properties of quantum dots and the operating principles of various infrared detectors. We review the latest advancements in short-wave infrared (SWIR), mid-wave infrared (MWIR), and long-wave infrared (LWIR) detectors employing colloidal quantum dots. Despite their potential, these detectors face significant challenges compared to conventional infrared technologies. Current commercial applications are predominantly limited to the near-infrared and short-wave bands, with medium- and long-wave applications still under development. The focus has largely been on lead and mercury-based quantum dots, which pose environmental concerns, underscoring the need for high-performance, non-toxic materials. Looking forward, the development of large array and small pixel detectors and improving compatibility with readout circuits are critical for future progress. This paper discusses these hurdles and offers insight into potential strategies to overcome them, paving the way for next-generation infrared sensing technologies. Full article

This review explores two main topics: the state-of-the-art and emerging capabilities of high-peak-power, ultrafast (picosecond and femtosecond) long-wave infrared (LWIR) laser technology based on CO₂ gas laser amplifiers, and the current and advanced scientific applications of this laser class. The discussion is grounded in expertise gained at the Accelerator Test Facility (ATF) of Brookhaven National Laboratory (BNL), a leading center for ultrafast, high-power CO₂ laser development and a National User Facility with a strong track record in high-intensity physics experiments. We begin by reviewing the status of 9–10 μm CO₂ laser technology and its applications, before exploring potential breakthroughs, including the realization of 100 terawatt femtosecond pulses. These advancements will drive ongoing research in electron and ion acceleration in plasma, along with applications in secondary radiation sources and atmospheric energy transport. Throughout the review, we highlight how wavelength scaling of physical effects enhances the capabilities of ultra-intense lasers in the LWIR spectrum, expanding the frontiers of both fundamental and applied science. Full article

Infrared (IR) sensors are widely used in various applications due to their ability to detect infrared radiation. Currently, infrared detector technology is in its third generation and faces enormous challenges. IR radiation propagation is categorized into distinct transmission windows with the most intriguing aspects of thermal imaging being mid-wave infrared (MWIR) and long-wave infrared (LWIR). Infrared detectors for thermal imaging have many uses in industrial applications, security, search and rescue, surveillance, medical, research, meteorology, climatology, and astronomy. Presently, high-performance infrared imaging technology mostly relies on epitaxially grown structures of the small-bandgap bulk alloy mercury–cadmium–telluride (MCT), indium antimonide (InSb), and GaAs-based quantum well infrared photodetectors (QWIPs), contingent upon the application and wavelength range. Nanostructures and nanomaterials exhibiting appropriate electrical and mechanical properties including two-dimensional materials, graphene, quantum dots (QDs), quantum dot in well (DWELL), and colloidal quantum dot (CQD) will significantly enhance the electronic characteristics of infrared photodetectors, transition metal dichalcogenides, and metal oxides, which are garnering heightened interest. The present manuscript gives an overview of IR sensors, their types, materials commonly used in them, and examples of related applications. Finally, a summary of the manuscript and an outlook on prospects are given. Full article

The Yixingzhai gold deposit is the largest gold deposit in Shanxi Province and develops three types of mineralization: porphyry, quartz vein, and breccia. Spectral characteristic parameters of muscovite are studied by short-wave infrared (SWIR) spectral, and the exploration significance is discussed. The Al-OH wavelength of muscovite associated with porphyry mineralization gradually becomes shorter from the periphery (>2206 nm) to the center (2201–2205 nm), and the crystallinity (>2.6) gradually increases. In quartz vein mineralization, the wavelength gradually increases from the periphery (<2203 nm) to the center (2210–2211 nm), while the crystallinity does not change significantly and in a small value (<1.5). The wavelength variation range of breccia mineralization is 2198~2214 nm and is concentrated in 2201~2204 nm near the center, while the overall crystallinity is lesser than 5.5 and concentrated around 1–2.2 near the center. The wavelength and crystallinity of muscovite are mainly affected by Tschermak substitution and temperature. When the contents of Si, Fe, and Mg are low and Al^VI is high, the wavelength tends toward the short-wave (SW) direction, while the opposite tends toward the long-wave (LW) direction. The high crystallinity (4.1–8.4) of muscovite can be used as an indicator of porphyry gold mineralization and also provides an important indicator to explore similar types of gold deposits. Full article