Search Results (1,623)

Accurate and high-efficiency film metrology remains a key challenge in High-Volume Manufacturing (HVM), where conventional spectroscopic reflectometry and white light interferometry (WLI) are either limited by model dependence or throughput. In this work, we extend the measurable film-thickness range of reflectometry to at least 50 µm through a new model-free algorithm, the Linearized Reflectance Zero-Crossing (LRZ) method. The approach builds upon the previously reported Linearized Reflectance Extrema (LRE) technique but eliminates the sensitivity to spectral sampling and fringe attenuation that degrade performance in the thick-film regime. By linearizing phase response and extracting Zero-Crossing positions in wavenumber space, LRZ provides robust and repeatable thickness estimation without iterative fitting, achieving comparable accuracy with much higher computational efficiency than conventional model-based methods. Validation using more than 80 measurements on alumina films over NiFe substrates shows excellent correlation with WLI (r = 0.97) and low gauge repeatability and reproducibility (GR&R < 3%). Moreover, LRZ achieves an average Move-Acquire-Measure (MAM) time of approximately 2 s, which is about 7 times faster than WLI. The proposed method enables fast, accurate, and model-independent optical metrology for thick films, offering a practical solution for advanced HVM process control. Full article

Addressing the technical bottlenecks of excessive surface density in traditional magnetic metal powder absorbers and excessive thickness in conventional foam-based absorbers, this study proposes a novel lightweight, ultra-wideband microwave-absorbing metamaterial. This metamaterial, through multi-layer and multi-dimensional structural design, has constructed a composite structure composed of a resistive film frequency-selective surface, a foam wave-absorbing medium layer and a reflective layer, achieving the controllable regulation of microwave absorption performance and the integration of structure and function. The research results show that the fabricated absorbing metamaterial achieves efficient electromagnetic wave absorption over a wide frequency band of 94 GHz under the ultra-light and ultra-thin conditions with a density as low as 0.078 g/cm³ and a thickness of only 4.9 mm. This study provides an effective design concept and solution for developing new lightweight, thin-layer, wide-band, and highly microwave-absorbing materials. Full article

Finding diabetic foot ulcers (DFUs) early and accurately is essential for improving patients’ quality of life and lowering the risk of amputation. RGB images, commonly used in automated DFU detection, have limitations such as lighting variations, color inconsistencies, and inability to directly reflect physiological information. Background/Objectives: Although thermal images can capture temperature anomalies associated with inflammation and circulatory disorders, they cannot provide consistent performance due to their low spatial resolution and limited availability in clinical datasets. Furthermore, the lack of paired RGB–thermal image pairs makes it difficult to develop effective multimodal deep learning models. Methods: This study proposes a two-stage multimodal deep learning approach to overcome these limitations. In the first stage, an RGB2T-cGAN (RGB to Thermal cGAN) model based on pix2pix was designed to generate synthetic thermal representations from RGB images that resemble clinical patterns, thereby addressing the missing modality problem. In the second stage, the Multimodal Dual-Stream Multi-Head Cross-Attention (MDS-MHCA) classifier model was developed, which processes DFU RGB and generated synthetic thermal images through separate streams, enabling the dynamic modeling of complementary information across modalities. Results: The proposed MDS-MHCA model achieved 99.06% accuracy, 99.09% recall, and 99.06% F1-score on the test set, demonstrating a clear advantage over models based solely on RGB (91.51% accuracy) or thermal (96.23% accuracy) modalities. Furthermore, patient-based 10-fold GroupKFold cross-validation results demonstrate that the model offers high generalization capability across different patient groups, with an average accuracy of 96.49 ± 1.04 and an AUC value of 0.9927 ± 0.0067. Conclusions: The findings reveal that the proposed approach, through the integration of synthetic thermal information and cross-attention-based multimodal fusion, overcomes the fundamental limitations of single-modality-based systems and offers a DFU detection system that is more robust and reliable and holds potential for integration into clinical decision support systems. Full article

Due to phenomena, such as refraction, reflection, and light scattering, the three-dimensional (3D) reconstruction of transparent objects with complex geometric symmetry or contours is confronted with the challenges of insufficient extraction of feature points and recognition of contour detail. To solve this challenge, a novel reconstruction method based on multi-cooperative Neural Radiance Fields (NeRF) is proposed in the paper. This method incorporates angular offset fields and local reconstruction fields, explicitly modeling the effects of refraction and reflection during light propagation. The angular offset field simulates the internal refractive deflection within transparent materials, while the localized reconstruction field performs secondary reconstruction in regions affected by specular reflection. This approach effectively captures surface contours of transparent objects and accurately reconstructs scene details. Experimental results demonstrate that our method achieves approximately 10% improvement in reconstruction accuracy compared to traditional neural radiance field techniques, with a PSNR of 25, an increased SSIM of 0.87, and a reduced LPIPS value of 0.365. The proposed method offers a new perspective for reconstructing transparent objects and scenes containing such materials, holding significant theoretical and practical value. Full article

Additive manufacturing is increasingly used in construction, yet reliable quality assurance for three-dimensional-printed concrete elements remains a major challenge. Existing digital defect-detection methods, particularly voxel-based and mesh-based approaches, are often evaluated separately, which limits understanding of their relative capabilities for construction-scale inspection. This study establishes a controlled comparison of the two representations using identical scan-to-design data, consistent preprocessing, and unified defect thresholding. A voxel pipeline employing signed distance fields and a three-dimensional convolutional neural network, and a mesh pipeline using triangular surface reconstruction, geometric surface descriptors, and MeshCNN, were applied to structured-light scans of printed clay wall segments containing intentional voids, material buildup, and layer-height inconsistencies. Across common performance metrics, the voxel-based method achieved a recall of 95% for spatially coherent, volumetric-consistent void-related anomalies inferred from surface geometry, reflecting improved aggregation of distributed deviations, while the mesh-based method attained a mean surface defect localization error of 0.32 mm with a substantially lower computational cost in runtime and memory. These results clarify representation-dependent trade-offs and provide guidance for selecting appropriate inspection pipelines in extrusion-based construction. The findings establish a controlled, construction-oriented comparative framework for digital defect detection and support more efficient, reliable, and scalable quality-assurance workflows for sustainable additive manufacturing. Full article

We present a Genetic Algorithm (GA)-based inverse design framework for creating a single-layer, fabrication-compatible dielectric nano-patterned surface that enables efficient color routing in both transmissive and reflective optical systems. Unlike traditional multilayer or absorption-based color filters, the proposed structure employs a fabrication-compatible architecture that spatially routes red, green, and blue light into designated output channels, significantly enhancing light utilization and color fidelity. The design process integrates a GA with full-wave finite-difference time-domain (FDTD) simulations to optimize the structural pillar height distribution, using a figure of merit that simultaneously maximizes optical efficiency and minimizes spectral crosstalk. For CMOS image sensor-scale designs, the nano-patterned surface achieved peak optical efficiencies of 76%, 72%, and 78% for blue, green, and red channels, respectively, with an average efficiency of 75.5%. Parametric studies further revealed the dependence of performance on pillar geometry, refractive index, and unit cell scaling, providing practical design insights for scalable fabrication using nanoimprint or grayscale lithography. Extending the approach to reflective displays, we demonstrate tunable-mirror-based architectures that emulate electrophoretic microcapsules, achieving efficient color reflection and an expanded color gamut beyond the sRGB standard. This single-layer, inverse-designed nano-patterned surface offers a high-performance and fabrication-ready solution for compact, energy-efficient imaging and display technologies. Full article

As a class of self-organized soft matter systems merging fluidic mobility with long-range molecular order, cholesteric liquid crystals (CLCs) possess immense potential for the development of high-sensitivity, visually tractable flexible sensors. Leveraging their unique helical superstructures and stimuli-responsive photonic bandgaps, CLCs can transduce subtle physical or chemical perturbations into discernible optical signatures, such as Bragg reflection shifts or mesomorphic textural transitions. Nonetheless, the intrinsic fluidity of CLCs often compromises their structural integrity, while conventional one-dimensional (1D) or two-dimensional (2D) confinement geometries exhibit pronounced angular dependence, significantly constraining their detection precision in complex environments. Recently, microfluidic technology has emerged as a pivotal paradigm for achieving sophisticated three-dimensional (3D) spatial confinement of CLCs through the precise manipulation of microscale fluid volumes. This review systematically delineates recent advancements in microfluidics-enabled CLC sensors. Initially, the fundamental self-assembly principles and optical properties of CLCs are introduced, emphasizing the unique advantages of 3D spherical confinement in mitigating angular sensitivity and intensifying interfacial interactions. Subsequently, the primary sensing mechanisms are bifurcated into bulk-driven sensing via pitch modulation and interface-driven sensing via topological configuration transitions. We then detail the microfluidic-based fabrication strategies and engineering protocols for diverse 3D architectures, including monodisperse/multiphase droplets, microcapsules, shells, and Janus structures. Building upon these structural frameworks, current sensing applications in physical (temperature, strain/stress), chemical (volatile organic compounds, ions, pH), and biological (biomarkers, pathogens) detection are evaluated. Lastly, in light of persistent challenges, such as intricate signal interpretation and limited robustness in complex matrices, we propose future research trajectories, encompassing the co-optimization of geometric parameters (size and curvature), artificial intelligence-enhanced automated diagnostics, and multi-field-coupled intelligent integration. This work seeks to provide a comprehensive roadmap for the design of next-generation, high-performance, and portable liquid-state photonic sensing platforms. Full article

Ultraviolet radiation, particularly in the UVC sub-band 200–280 nm, is a non-thermal disinfection technology capable of inactivating a broad spectrum of microorganisms primarily through nucleic acid damage and protein oxidation. Its effectiveness depends on wavelength, irradiance, exposure time, environmental conditions, and microbial characteristics, such as species and repair capacity. In food processing environments, where equipment surfaces and packaging materials are critical control points for microbial contamination, UVC offers several advantages, including the absence of chemical residues, and compatibility with sustainable sanitization strategies. However, efficacy is strongly influenced by surface properties. Smooth, non-porous, reflective materials (stainless steel, glass), and photocatalytic metal coatings, enhance UVC performance, whereas rough, porous, or fibrous surfaces reduce penetration and create shadowing effects that limit microbial inactivation. This review synthesizes current evidence on UV-based decontamination in the food industry, highlighting both its potential and limitations. The findings emphasize that, although UVC radiation is effective in microbial control, its implementation must consider the complex interactions between surface properties, microorganisms and irradiation parameters, requiring optimization for each environment and application. Further research is therefore needed into: (i) wavelength-tuned systems, (ii) hybrid technologies (UV–plasma or UV-photocatalysis), (iii) material integrity and durability of materials under repeated exposure, and (iv) emerging alternative light sources. Full article

Particle size and size distribution are critical parameters that strongly influence the performance, reproducibility, and applicability of nanoparticles. In this work, we systematically investigated the effect of oscillation mode on the particle size and dispersion of SiO₂ nanoparticles synthesized via the Stöber method. Multiple commonly used laboratory mixing and oscillation modes—including stirring, horizontal shaking, vertical shaking, rotating, vertical shaking combined with rotating, water bath sonication, probe sonication, and static conditions—were comparatively evaluated. Particle size and size distribution were characterized by transmission electron microscopy and dynamic light scattering, and the polydispersity index (PDI) was quantitatively analyzed. The results demonstrate that stirring, horizontal shaking, vertical shaking, and rotating produce silica nanoparticles with comparable average sizes and consistently low PDI values within the investigated parameter range, indicating similar performance among these moderate and continuous oscillation modes under the studied conditions. In contrast, vertical shaking combined with rotating, water bath sonication, and probe sonication lead to larger particle sizes and broader size distributions, accompanied by elevated PDI values. Although static conditions yield smaller average particle sizes, the resulting particles exhibit the highest PDI, reflecting poor size uniformity. These findings provide practical process-level guidance for selecting appropriate oscillation modes to achieve reproducible and uniform silica nanoparticle synthesis in general laboratory settings. Full article

Camera calibration is an essential research direction in photonics and computer vision. It achieves the standardization of camera data by using intrinsic and extrinsic parameters. Recently, RGB-D cameras have been an important device by supplementing deep information, and they are commonly divided into three kinds of mechanisms: binocular, structured light, and Time of Flight (ToF). However, the different mechanisms cause calibration methods to be complex and hardly uniform. Lens distortion, parameter loss, and sensor degradation et al. even fail calibration. To address the issues, we propose a camera calibration method based on the Expectation–Maximization (EM) algorithm. A unified model of latent variables is established for the different kinds of cameras. In the EM algorithm, the E-step estimates the hidden intrinsic parameters of cameras, while the M-step learns the distortion parameters of the lens. In addition, the depth values are calculated by the spatial geometric method, and they are calibrated using the least squares method under an optical motion capture system. Experimental results demonstrate that our method can be directly employed in the calibration of monocular and binocular RGB-D cameras, reducing image calibration errors between 0.6 and 1.2% less than least squares, Levenberg–Marquardt, Direct Linear Transform, and Trust Region Reflection. The deep error is reduced by 16 to 19.3 mm. Therefore, our method can effectively improve the performance of different RGB-D cameras. Full article

A reflective baffle for the optical system of a satellite camera based on the carbon fiber composite materials is designed and validated. Firstly, two typical reflective baffles including elliptical type and Stavroudis type are studied. High modulus carbon fiber composite materials are selected to achieve lightweight and high rigidity. The aluminum film is coated on the surface of vanes to enhance the surface spectral reflectivity. Then, temperature field under typical external heat flow is calculated and stray light suppression characteristics are analyzed. Finally, the finite element simulation and mechanical vibration experiment are performed to verify the reliability of the baffle structure. The results show that the reflective baffle meets the requirements of mechanical environment during the launch phase of satellite camera. It provides a reference for the design of the satellite camera baffles structure. Full article

Most existing reactive agility assessments rely on screen-based or light-based stimuli that are spatially separated from the movement execution plane, thereby limiting ecological validity. The purpose of this study was to develop and validate a novel projection-based, ground level reactive agility test (RAT) designed to better reflect the perceptual motor demands of soccer. A total of 57 male soccer players (24 professional and 33 amateur) participated in the study. The system projects sport-specific visual stimuli onto the ground and uses a three-dimensional depth camera to track foot–stimulus interactions in real time. Two reactive agility protocols—a randomized simple reaction test and a randomized selective reaction test—were implemented. Construct validity was examined by comparing reactive agility and planned change-of-direction (PCOD) performance between professional and amateur players, as well as by analyzing relationships between PCOD and RAT outcomes. Professional players demonstrated significantly faster performance than amateurs across all tests (p < 0.01), with larger between-group differences observed in reactive agility compared with PCOD measures. Correlations between PCOD and reactive agility outcomes were low to moderate (r = 0.34–0.61), indicating that reactive agility captures performance components beyond planned movement ability. The reactive agility protocols showed excellent test–retest reliability (ICC = 0.92–0.99) with low measurement error (CV = 0.96–3.47%). In conclusion, the proposed projection-based, ground-level RAT provides a valid and reliable assessment of reactive agility in soccer. By integrating sport-specific stimuli and movement execution within the same spatial plane, the system enhances ecological validity and offers a scalable framework for both performance assessment and perceptual cognitive training in open-skill sports. Full article

We present an optical deformation sensor additively manufactured via an embedded printing process that enables the direct integration of colloidal quantum dots into multimode silicone (PDMS) waveguides. The sensor consists of two parallel waveguide strands, one of which is locally functionalized with CdSe/CdS quantum dots serving as fluorescent emitters. When narrow-band UV light at 405 nm is coupled into the non-functionalized strand, structural deformation alters the conditions of total internal reflection, thereby changing the optical interaction between both strands. This leads to a deformation-dependent variation in the fluorescence shift-affected intensity ratio, which serves as a self-referenced signal for angle determination. Using ratiometric evaluation, angular deflections of up to 9.5° are detected with a resolution below 1° ($2\sigma$ confidence), representing the performance of an initial functional prototype. The embedded printing process allows the voxel-wise adjustment of the material composition within a viscoplastic support medium and thus the spatially resolved integration of quantum dot-functionalized silicone. Attenuation losses of $0.81\pm 0.02\mathrm{dB}/\mathrm{cm}$ at 625 nm confirm the optical suitability of the printed waveguides. This approach combines optical sensing and structural flexibility within a single manufacturing step and establishes a pathway toward fully integratable deformation-sensing elements for soft robotic and wearable systems. Full article

Metal–organic frameworks (MOFs), particularly Zeolitic Imidazolate Framework-8 (ZIF-8), are promising photocatalysts; however, their practical application is limited by a wide band gap (~3.85 eV), which restricts light absorption mainly to the ultraviolet region. This limitation was addressed by synthesizing a series of cobalt-doped ZIF-8 materials, Co(x)ZIF-8 (x = 0, 2.5, 5, 7.5, and 10 wt%), using a cost-effective aqueous synthesis route. Structural and compositional analyses using X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), and energy-dispersive X-ray spectroscopy (EDS) confirmed the formation of phase-pure ZIF-8 topology, with no significant change in nanoparticle morphology upon the partial substitution of Zn²⁺ by Co²⁺ ions within the framework. UV–Vis diffuse reflectance and Tauc plot analysis revealed a systematic and substantial reduction in the optical band gap (Eg) with increasing Co content, indicating enhanced visible-light absorption capability. All Co(x)ZIF-8 samples exhibited superior photocatalytic activity compared to pristine ZIF-8 under light irradiation. Among them, Co(2.5)ZIF-8 displayed the highest apparent reaction rate constant for pollutant degradation, while Co(5)ZIF-8 achieved the highest overall degradation efficiency (~87%) after 40 min. The enhanced photocatalytic performance is attributed to the synergistic effects of band-gap narrowing and the presence of Co²⁺ ions, which act as effective charge-trapping centers and suppress electron–hole recombination. Electrochemical measurements further demonstrated that Co(5)ZIF-8 exhibits the highest current density (most negative J) at large negative potentials (e.g., J ≈ −0.105 A cm⁻² at E = −2.0 V), indicating superior intrinsic catalytic activity. These findings highlight cobalt-doped ZIF-8 as a highly tunable and efficient photocatalyst with strong potential for environmental remediation applications. Full article

In the fabrication of ultrathin multilayer ceramic capacitors (MLCCs), the long-term stability of ceramic slurries is a critical yet often overlooked factor that can significantly influence coating uniformity, interfacial adhesion, and process reproducibility. Despite its industrial importance, the time-dependent evolution of slurry dispersion structures during storage and its direct impact on green sheet properties remain insufficiently understood. This study examined the time-dependent physicochemical evolution of barium titanate (BaTiO₃)-based green sheet slurries, which behave as colloidal gel-like dispersion systems, and their influence on the structural, optical, and interfacial properties of the resulting sheets. Dynamic light scattering revealed progressive yet uniform particle aggregation, while viscosity measurements indicated a gradual ~10% decrease over 960 h, reflecting reduced dispersion stability and progressive weakening of the slurry gel network during extended storage. The slurry, consisting of BaTiO₃ particles, polymeric binders, and plasticizers, forms a three-dimensional transient gel network, in which particle–particle and particle–binder interactions govern rheological behavior. The observed viscosity decrease and turbidity reduction indicate gel network relaxation and partial gel–sol–like transition behavior driven by aggregation. Cross-sectional scanning electron microscopy demonstrated that these changes produced a measurable reduction in final green sheet thickness, despite identical processing conditions. Furthermore, peel tests revealed that interfacial adhesion strength increased with storage time, attributable to localized solid enrichment within the slurry gel matrix and enhanced bonding at the release film interface. The reduced coating thickness also contributed to lower optical haze, reflecting a shortened light-transmission path. Collectively, these findings demonstrate that even moderate aggregation in a ceramic network-forming dispersion system substantially alters coating behavior, adhesion, and optical performance. The results underscore the importance of managing gel-network stability and rheology to ensure reliable green sheet fabrication and storage in MLCC manufacturing. Full article