Search Results (210)

Lidar systems are of major importance for driver assistance systems and autonomous driving, but their obstacle detection range can be heavily impaired by adverse weather conditions like fog. To mitigate the effects of fog, the use of polarized light has been proposed. We simulated a polarized lidar system, taking Mie theory-based scattering functions for different fog types at several wavelengths into account, and investigated the possible increase in contrast between fog backscattering and target returns for different surface types, depending on the target orientation and the polarizer configuration. Fog is modeled as an infinite, homogeneous, scattering, and absorbing medium. The simulated detector registers the time-dependent radiance, resolved by scattering order. Our findings show that the suitable choice of illumination and detection polarization allows the amount of single-scattered light detected to be reduced by two to four orders of magnitude and the contrast between fog and target to be increased significantly. Crucially, this approach delivers robust contrast enhancement regardless of whether the target surface is depolarizing Lambertian or perfectly reflecting. Full article

Developing sustainable and scalable personal thermal management textiles that simultaneously provide radiative cooling, moisture comfort, and responsible end-of-life management remains challenging. Here, we report a sustainable, scalable, and recyclable bamboo dissolving pulp-derived cellulose/SiO₂ fiber (CSF), fabricated by a wet-spinning process involving the dissolution and regeneration of cellulose and nano-SiO₂. The resultant CSF exhibits a hierarchical interface-pore structure, which enhances solar scattering (up to 94.56% in 0.4–1.0 μm) by Mie scattering of nano-SiO₂ particles and multiple scattering at micro- and nanopore-induced air/cellulose/SiO₂ interfaces. By coupling high mid-infrared emissivity of 94.8% (8–13 μm), the CSF demonstrates average daytime sub-ambient cooling of 9.5 °C under hot and humid summer conditions. More importantly, the CSF presents a multiscale water-transport network that integrates molecular water capture (–OH groups), capillary infiltration (nanoscale interfaces between nano-SiO₂ and cellulose), and liquid spreading and evaporation (interconnected microchannels between fibers), which realizes larger liquid diffusion area and water-vapor transmission rate (7.55 cm² and 175.48 g m⁻² 24 h⁻¹), compared to commercial cotton and polyester. In addition, the CSF demonstrates desirable soil-biodegradation capability, while the feasibility of closed-loop reuse is demonstrated through a single recycling cycle, supporting environmentally friendly wearable cooling textiles. The wet-spinning strategy paves the way for the construction of sustainable, scalable and recyclable fiber for thermal- and moisture-comfort textiles. Full article

This paper deals with the use of the singular boundary method for analysis of time-harmonic acoustic scattering by penetrable obstacles. There are many formulations of boundary-type meshless methods, distinguished mainly by the manner in which the singularity of the fundamental solution at the source point is treated. The article presents the singular boundary method (SBM), a boundary-only, integration-free collocation technique in which the source points are placed directly on the physical boundary, so that no volume mesh, no auxiliary boundary and no element connectivity are required. The scattered field in the exterior and the transmitted field inside each obstacle are each represented by a single layer of fundamental solutions. The determination of the origin intensity factors (OIFs), which replace the singular self-interaction of the single-layer fundamental solution and of its normal derivative, is the crucial part of the method. A closed-form OIF is employed for the Dirichlet boundary condition and a purely geometric OIF based on the signed boundary curvature is employed for the Neumann boundary condition, so that only two boundary operators are required instead of the four operators used in the direct formulation. The accuracy of the method has been compared with the analytical Mie series and the third-order deltaBEM. Third-order convergence and reasonable accuracy, when compared to the exact solution, are obtained throughout. Full article

In deep-space exploration and remote sensing, characterizing radiative transfer in complex planetary atmospheres is fundamental for robust target detection and optical navigation. On the Martian surface, intense scattering and attenuation by dust aerosols pose severe environmental interference, challenging star sensors used for high-precision navigation. To address this, this study develops a spectral radiative transfer model based on the Null Collision Monte Carlo Method to characterize the optical background of the dusty Martian atmosphere. Mie scattering theory is employed for dust particles, while gas molecular absorption is modeled via line-by-line integration. The simulated sky radiance is validated against Mars rover Navcam observations, yielding an average relative error of 7.83% between the modeled and observed radiance values across scattering angles greater than 5°. Building on this, an imaging link model evaluates surface-based detection performance, including signal-to-noise ratio, detection success probability, and star count. Optical parameters—aperture, field of view, and integration time—are optimized for nighttime and dawn-dusk modes. Spatio-temporal assessments are conducted globally across Martian years, focusing on the Zhurong landing site and Tianwen-3 candidates. Finally, an Earth-environment equivalence experiment using a 60% transmittance filter verifies the design’s robustness. This work confirms the feasibility of star-sensor-based attitude determination on Mars. Full article

Biological aerosols represent a significant challenge for modern CBRN defense due to their potential for long-range dispersion and the need for rapid threat assessment. Current stand-off detection systems are effective in recognizing anomalous aerosol clouds but often lack the molecular specificity required for reliable agent identification. This review examines the role of mid-infrared (MIR) spectroscopy as an emerging approach for chemically resolved stand-off bioaerosol sensing. The physical principles of MIR detection are discussed, including molecular vibrational fingerprints, differential scattering (DISC), and circular intensity differential scattering (CIDS), together with their relationship to aerosol optical properties and Mie resonance effects. Existing and emerging sensing architectures are reviewed, ranging from operational CO₂ laser-based DISC systems to semiconductor-based platforms utilizing tunable differential absorption lidar (DIAL), Quantum Cascade Lasers (QCLs), and dual-comb spectroscopy. The analysis highlights the ability of MIR sensing to access biomolecular signatures associated with proteins, lipids, nucleic acids, and bacterial spores, while also addressing challenges related to atmospheric attenuation, biological variability, and signal interpretation. The reviewed literature indicates that MIR spectroscopy offers a promising pathway toward improved stand-off identification of hazardous bioaerosols, supporting early threat detection and enhanced situational awareness in applications including CBRN defense, critical infrastructure protection, environmental monitoring, public health surveillance, and emergency response. Full article

Based on generalized Lorenz–Mie theory (GLMT) and the Maxwell stress tensor (MST) method, this study investigates the modulation mechanism of the axial optical torque N_z exerted on Cs₂AgBiBr₆ (CABB) perovskite-coated gold nanospheres under vector Bessel-beam illumination. The results show that the CABB shell reconstructs the torque-resonance channels of the coated particle by modifying both the dispersive dielectric environment around the gold core and the core–shell interfacial response. As the shell thickness increases, the dominant response undergoes a continuous redshift. The polarization state, half-cone angle α₀, and order l of the incident vector Bessel beam serve as external optical-field degrees of freedom that regulate the incident angular-momentum channels, thereby enabling coordinated control over the torque peak magnitude, spectral line shape, and torque direction. Analyses of the near-field distributions, Poynting-vector distributions, and Mie-order decomposition reveal that the strong torque response arises from selective coupling between the intrinsic Mie channels of the core–shell particle and the vectorial structure of the incident light, rather than simply from local field-intensity enhancement. This study provides a theoretical basis for tunable N_z responses in perovskite–plasmonic hybrid nanostructures and for structured-light-driven rotational manipulation at the nanoscale. Full article

The fading of painted relics is a widespread deterioration phenomenon in ancient painted cultural relics, yet its underlying mechanism has long been attributed solely to pigment oxidation. Directed at colored drawings with complex surface microstructures, such as pottery paintings, wall murals and architectural paintings, here we challenge this view by demonstrating that light scattering induced by sub-micron pores within the paint layer plays a dominant role, especially Mie scattering when pore sizes approach visible light wavelengths (400–700 nm). In order to minimize the damage to the genuine painted relics, a large number of simulated experiments were conducted first. Using porous polyacrylamide (PAM) membranes and nylon 6 filter membranes as model systems, we show that pore-induced scattering reduces the optical path length for light absorption, leading to a significant decrease in color saturation and brightness. By filling the pores with non-volatile colorless ionic liquids ([BMIM]PF₆) (n = 1.41) or glycerol (n = 1.47)—both possessing refractive indices close to those of the pigments—the scattering is effectively suppressed, and the original color is restored. The filling treatment reduces the color difference (ΔE*ab) by 30%–50% and the surface reflectivity by 20%–40%. Mercury intrusion porosimetry and fluorescence spectroscopy confirm that pore elimination and optical path lengthening are responsible for the color recovery. The proposed mechanism and restoration strategy were successfully validated on authentic painted brick fragments from the Western Qing Tombs (Hebei, China), where severely faded green and red patterns reappeared after ionic liquid treatment. This study provides a new interface-regulation paradigm for the conservation of painted cultural heritage, shifting the focus from irreversible chemical remediation to reversible physical restoration and offers a generalizable platform for controlling light scattering in porous optical materials. Full article

Particle size distribution (PSD) is a key determinant of aerosol optical properties and plays an important role in optical sensing and environmental monitoring. However, estimating PSD from light scattering measurements remains a challenging inverse problem due to its ill-posed nature and sensitivity to noise. To achieve the objective, this study proposed a physics-informed, data-driven inversion framework for PSD reconstruction using multi-angle light scattering signals generated from Mie scattering simulations. Synthetic datasets were generated using Johnson–SB, lognormal, and bimodal lognormal PSDs under various optical conditions, and the resulting scattering intensities were used to train machine learning models, including Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Support Vector Regression (SVR). The proposed framework was evaluated using both point-wise error metrics and distribution-based metrics, including Kullback–Leibler divergence and Wasserstein distance. The results showed that RF and XGBoost consistently achieved the highest reconstruction accuracy, with R² values exceeding 0.98 across different PSDs, and significantly outperformed conventional linear baseline methods, including Ridge regression (representing Tikhonov regularization) and Non-negative Least Squares (NNLS). Additional experiments using lognormal and bimodal lognormal PSDs further confirmed the distributional generalization capability of the proposed model. The reconstructed PSDs also showed strong agreement with the reference distributions and remained robust under Gaussian, lognormal, and combined noise perturbations of up to 20%. Therefore, integrating physics-based scattering simulations with machine learning provided an accurate and robust solution for the inverse Mie scattering problem in optical particle characterization. Full article

An experimental setup has been developed that enables the conversion of a complex stream of polydisperse droplets generated by an ultrasonic dispenser into a stream of nearly identical droplets falling through a vertical channel. The fall of droplets of an aqueous NaCl solution in this channel, filled with heated dry air, is studied. Water from the droplets evaporates quickly, and crystals of a solid salt crust form on their surface. At a later stage of the process, the remaining solution is removed from the droplet using a jet of water vapor that passes through the pores of the polycrystalline crust. It was first observed that some of the drying droplets suddenly shifted to one side under the influence of the reactive force generated by the vapor jet. Images obtained using a scanning electron microscope show that the salt particles formed have a diameter of around 25 µm, are slightly porous, and consist of numerous crystals. It has been proven that these particles do not have a central cavity. The use of seawater and the role of salt particles in protecting against thermal radiation from fires are briefly discussed. Calculations based on Mie theory have shown that the contribution of light scattering by thin-walled hollow sea salt particles formed above the ocean surface during relatively slow evaporation of seawater droplets can be significant to the ocean’s heat balance. Full article

The interaction of electromagnetic waves with atmospheric aerosols plays a significant role in communication systems and multimedia information transmission. Understanding the interaction of vortex light beams with an aerosol-laden atmosphere is indispensable for establishing a framework of the environmental channel. During the interaction, different optical effects such as absorption and scattering will result in energy attenuation, and this yields the deterioration of the transmission feature of the vortex beam signal. In this study, we present a theoretical analysis of Gaussian vortex beams (GVBs) scattering by diverse aerosol (unformed carbon, dust, sulphate, silicate, soot, and nitrate) particles in the atmosphere on the basis of the well-established generalized Lorenz–Mie theory (GLMT). Combined with the lognormal distribution model for aerosol particles, the attenuation and transmission characteristics of GVBs for different aerosol particles are analyzed. The extinction efficiency $\left(Q_{ext}\right)$ factor of GVB, caused by the absorption and scattering of various aerosols, becomes smaller compared to that of a basic Gaussian beam (GB). Increasing the OAM mode index, the energy attenuation and transmission caused by aerosol absorption and scattering further decrease. Moreover, this research provides a basis to analyze the optical characteristics of the twisted beams in different atmospheric channels, such as wireless communication networks over aerosol-laden systems and material interactions. Full article

To address the limited constraints of ground-based lidar with few channels in retrieving aerosol microphysical parameters in urban atmospheres, this study developed a method to retrieve aerosol volume size distribution and effective radius from a 355/532/1064 nm triple-wavelength elastic-scattering, single-polarization lidar system. The method uses 3β + 2α optical quantities as input constraints, applies Mie scattering theory as the forward model, parameterizes the volume size distribution with B-spline functions, and achieves stable solutions through Tikhonov regularization and cross-validation. To reduce uncertainties in prior parameters, including the complex refractive index, particle size range, and lidar ratio, an optimization strategy based on parameter search, retrieval reconstruction, and error minimization was introduced. Numerical simulations showed that the method reproduced the main features of a bimodal lognormal aerosol volume size distribution with good feasibility and stability. Two case studies further showed fine-mode dominance and decreasing extinction coefficient, depolarization ratio, and effective radius with height under good air quality conditions, but enhanced coarse-mode contribution and effective radius in the upper cloud-influenced layer under lightly polluted conditions, as inferred from the combined variations in RSCS, extinction coefficient, depolarization ratio, and effective radius. Full article

Baltic amber exhibits a wide range of colors and has attracted considerable attention in materials science. Previous studies have mainly focused on the origin and formation characteristics of beeswax-amber, while the relationship between beeswax-amber color and the microstructural characteristics of internal bubbles remains poorly understood. Ten beeswax-amber specimens exhibiting a color gradient from yellow to white were selected. Scanning electron microscopy (SEM) was used to examine and analyze their internal structures, with a focus on documenting bubble size, number, and density characteristics. Ultraviolet (UV) illumination was employed for qualitative optical observation, and Fourier-transform infrared (FTIR) spectroscopy was conducted to identify component phase and spectra. The correlation between bubbles and color was analyzed to infer the origin of white beeswax-amber’s coloration and explore the mechanisms underlying beeswax-amber’s color variation. Results indicate that beeswax-amber coloration is closely linked to its microscopic bubble characteristics. The microstructure satisfies conditions for Mie scattering, some white beeswax-amber samples contain abundant nanoscale bubbles, triggering a combined effect of Rayleigh and Mie scattering. These results demonstrate that the color of Baltic amber is governed not only by its intrinsic body color but also by the synergistic optical effects arising from internal bubble microstructures, providing a physically grounded explanation for its diverse appearances. Full article

Using an in situ method of time-resolved Mie scattering indicatrix registration, the dynamics of micro- and nanoparticle formation during the explosive boiling of a solution of ibuprofen in subcritical carbon dioxide (T₀ = 302 K, P₀ = 71 bar) were investigated. The process is found to exhibit multistage behavior. At the jet front, ibuprofen microaggregates with a mean radius of 1.4 ± 0.2 μm are formed, maintaining a stable size over the initial ~100 ms. Subsequent reduction in boiling intensity results in a decrease in the particle radius to 650 ± 100 nm. In the following stage, nanoscale CO₂ clusters (20–50 nm) are detected by the Mie scattering technique. The findings indicate that the final size of the resulting ibuprofen particles is governed not only by the initial thermodynamic conditions but also by the boiling dynamics of the ibuprofen-saturated CO₂ solution during the pulsed ejection process. Full article

In this study, a low-cost AS7265x-based multispectral electronic tongue system was developed for estimating milk composition and adulteration indicators and supported with an explainable artificial intelligence (XAI) framework. Experimental analyses were conducted on 190 augmented commercial milk samples, where fat, protein, solids-not-fat (SNF), density, freezing point, and added water ratio were treated as target variables. Sensor data were modeled as RAW, DERIVED, and FUSION feature sets, and regression performance was compared using Random Forest, Gradient Boosting, AdaBoost, KNN, and XGBoost. Model validation was carried out with both five-fold cross-validation and Leave-One-Out (LOO) strategies to assess field-level generalizability. Results showed that a narrow-band, low-cost optical sensor platform can estimate not only fat and protein but also SNF, density, and freezing point with high accuracy. Within the XAI framework, permutation-based importance analysis and SHAP were used to identify critical spectral bands for each target parameter, enabling data-driven recommendations for band-oriented sensor design optimization. The study presents a scalable methodology that integrates low-cost sensor design, multi-parameter quality estimation, and explainable modeling beyond traditional fat–protein-focused approaches. Across all six targets, the XAI analysis consistently identified the near-infrared channel at 860 nm (asIR_3) as the most informative band, reflecting the combined effect of water absorption and Mie scattering by fat globules; the visible channel at 680 nm (asVIS_4) emerged as a secondary band, reflecting dissolved-matter scattering. These bands are therefore the natural starting point for cost-reduced versions of the sensor. Among the compared feature sets (RAW, DERIVED, FUSION), the 18-band RAW configuration provided the most balanced performance across all six targets. Full article

Reliable detection of personnel is critical for situational awareness and life-saving interventions during indoor fire rescue operations, where dense smoke rapidly obscures visibility and compromises conventional vision systems. Visible-light cameras fail under such conditions due to severe Mie scattering, while thermal infrared (TIR) imaging—though capable of penetrating smoke—often lacks the fine-grained texture needed to distinguish human forms from background clutter. Furthermore, practical deployment of multimodal sensors is hindered by spatial misalignment between modalities, which degrades fusion efficacy and detection accuracy. To address these challenges, this paper proposes GLAFC-YOLO (Global-Local Alignment and Frequency-aware Cross-attention Fusion), a dual-stream multimodal detection framework specifically designed for personnel localization in smoke-obscured indoor fires. GLAFC-YOLO fuses near-infrared (NIR) and TIR imagery through three novel components: (1) a Global-Local Feature Alignment Subnet (GL-FAS) that rectifies geometric misalignment across modalities; (2) a Modality-Adaptive Frequency Channel Attention (MA-FCA) module that enhances complementary smoke-penetrating thermal signatures and NIR texture cues in the frequency domain; and (3) a Confidence-Aware Transposed Cross-Attention (CA-TCA) mechanism that suppresses smoke-induced artifacts and restores weakened human-centric features. Evaluated on a newly collected multimodal dataset of indoor fire scenarios with annotated personnel, GLAFC-YOLO achieves substantial improvements over the baseline YOLOv11 architecture. Specifically, it achieves Recall improvements of 43.2% and 0.5% compared to unimodal NIR and TIR baselines, respectively. In addition, it achieves improvements of 37.4% and 3.9% in $mA{P}_{50}$ and 17.3% and 17.0% in $mA{P}_{50–95}$. Experimental results indicate that GLAFC-YOLO outperforms competitive models and reduces personnel miss rates, demonstrating its robustness and readiness for real-world fire-rescue assistance. Full article