In recent years, infrared polarization imaging has gradually become a research hotspot owing to its ability to simultaneously acquire multi-dimensional radiation as well as polarization information and thereby more comprehensively reflect the physical properties of targets. However, it is susceptible to complex environments, causing reduced image contrast and obscured details. Existing multi-scale fusion methods focus mainly on infrared–visible fusion, whereas the fusion of infrared intensity and infrared degree of linear polarization images, which provides complementary thermal-radiation contrast and polarization-sensitive surface detail, has received limited attention. Therefore, a multi-scale decomposition and feature adaptive weight fusion method for infrared intensity and polarization images is proposed. Unlike conventional pyramid-based methods that apply uniform fusion rules across all decomposition levels, the proposed method employs differentiated strategies tailored to distinct frequency components. The source images are first decomposed by Gaussian and Laplacian pyramids into base and detail layers. An adaptive region weight strategy with guided filtering is then applied to the base layers, while an absolute-maximum selection strategy is used for the detail layers. The adaptive weights are computed from local saliency, enabling each image to contribute proportionally to its local informational advantage. The fused layers are then reconstructed into the final fused image. Qualitative and quantitative experiments on two datasets, comparing seven state-of-the-art fusion methods, demonstrate that the proposed method better preserves infrared intensity and polarization information, yielding high contrast and rich detail. This work provides strong support for target detection and recognition in complex environments and demonstrates significant application potential.
Boron carbide (B4C) is widely used as a coating material for x-ray optics in X-ray Free Electron Laser (XFEL) beamlines. In this study, single-shot damage experiments were conducted on B4C/Si-sub and B4C/Cr/Si-sub mirrors at 517 eV using the Shanghai Soft x-ray free electron laser. The damage thresholds were determined to be 0.49 ± 0.13 and 0.32 ± 0.08 J/cm2 for B4C/Si-sub and B4C/Cr/Si-sub, respectively. Morphological and microstructural characterizations reveal that XFEL-induced damage in both samples is closely related to thermal melting of the Si substrate. Based on the silicon melting criterion, the theoretical damage threshold simulated by the finite element method for B4C/Si-sub is in good agreement with the experimental result. The bump damage morphology observed at a fluence of 0.66 J/cm2 for this sample is attributed to the volumetric expansion of the molten Si substrate. In contrast, the silicon melting criterion overestimates the damage threshold for the B4C mirror with a Cr adhesive layer. The lower experimental threshold of B4C/Cr/Si-sub is attributed to the interfacial diffusion reaction and the femtosecond XFEL-induced cavitation, which leads to a more readily observable damage morphology.
A novel shared-aperture reflectarray antenna (RA) based on structural multiplexing is proposed. Featuring mechanical reconfigurability, ultra-wideband performance is achieved, and manufacturing costs are significantly reduced. Through this design, the inherent bandwidth limitations of conventional shared-aperture reflectarrays are effectively overcome. RA2 and RA1 are passively reconfigured via a dual-layer structure to operate at 27.5–30.5 and 30.2–34.5 GHz, respectively. The reflection phase of each RA-unit is controlled by adjusting the dimensions of the square patches on the double-layer dielectric. Sidelobe levels are suppressed below −18.4 dB, with edge diffraction exerting minimal impact on the main radiation pattern. Experimental measurements confirm that a gain ranging from 27.2 to 28.0 dBi is achieved across the 27.5–34.5 GHz band, corresponding to a −1 dB gain bandwidth of 22.6%. An aperture efficiency exceeding 24% is maintained, reaching a peak of 39% at 28 GHz. The measured main beam remains relatively stable, with a 3 dB beamwidth of ∼5.3° in both the E- and H-planes.
In this study, the Monte Carlo method was employed to simulate radiation damage in β-Ga2O3 induced by Si+ ion implantation. By optimizing implantation energy and fluence, a uniform Si concentration of ∼1 × 1018 cm−3 was achieved across a depth range of 0.1–0.5 μm. As implantation energy increased, the fraction of total energy deposited via ionization losses rose from 48.53% to 71.56%, while phonon-mediated and vacancy-related energy losses declined from 48.14% to 26.62% and from 3.33% to 1.83%, respectively. Concurrently, the maximum energy absorbed reached 40.86 eV/(Å ion) for Ga atoms and 34.89 eV/(Å ion) for O atoms. The peak values of total displacements per atom, gallium vacancies, and oxygen vacancies were 0.039 86, 1.6 × 1021 cm−3, and 1.8 × 1021 cm−3, respectively. Collectively, these results indicate that Si+ ion implantation inevitably introduces a high density of point defects in Ga2O3, which may severely degrade carrier mobility and impede electrical activation efficiency.
To establish a robust theoretical and physical foundation for the safe design and application of heterogeneous polymer-bonded explosives (PBXs), it is essential to elucidate their shock Hugoniot relationship and Jones–Wilkins–Lee (JWL) equation of state (EOS). Based on planar shock wave theory and the Rankine–Hugoniot relations, combined with the relationship between shock wave velocity and particle velocity, symmetric impact experiments were conducted to determine the EOS of the PBX under different shock front conditions. Interfacial particle velocity experiments were performed to characterize the reaction-zone parameters, including the Chapman–Jouguet pressure and the von Neumann spike pressure. Cross-comparison and validation of the results from the two experiments confirmed the reliability of the test method for deriving the JWL EOS parameters for unreacted PBX. For the reacted PBX, the EOS parameters were calibrated using 50 mm-diameter cylinder expansion tests. The reacted JWL EOS parameters were subsequently fitted via an optimization algorithm, providing a critical basis for predicting the internal pressure, density, and energy states of the PBX under higher-amplitude shock loading.
In order to create scientific, educational, and technical documents, the LATEX system is often used. The system has a mechanism of macros that automate repetitive tasks when called. In this article, the method for programming new macros was used in the LATEX2ɛ version of this system. The \NoP macro template and its modification \NoPm were created: they automate paragraph numbering when any of these macros is called. These macros can also automate the numbering of other elements of a document when any of these macros is called. These macros function without using any packages. The \matrfirst and \matrappar macro templates were created to automate matrix formatting when these two macros are called together. At the same time, a fixed-template workaround was introduced to bypass the limitation of the \newcommand command that itself does not allow creating macros that accept more than nine arguments. The results of the evaluation of the created \NoP and \NoPm macros confirmed their value as a convenient tool for automating paragraph numbering when any of these macros is called, and the results of the evaluation of the created \matrfirst and \matrappar macros confirmed their value as a convenient tool for automating formatting matrices with entries not limited to nine when these two macros are called together. When called, the created macros reduce the probability of making an error. They increase the readability of the source code by reducing the number of commands that are not related to the content of the document.
Compressed air energy storage (CAES) is a promising technology for large-scale energy storage; however, conventional CAES systems have problems such as mechanical losses and complex compression processes. In this study, a liquid piston compressor-based compressed air energy storage (CAES) system is proposed. A thermodynamic model is established, and a MATLAB/Simulink model is developed for dynamic simulation to evaluate the performance characteristics of the proposed system. By analyzing the effects of key operating parameters, including storage pressure, storage tank volume, initial pressure, and pump power, the optimal parameter combination is determined. Under the optimal operating conditions, the results show that the proposed system achieves storage duration (charging time) of 0.2611 h, specific compression work of 263.92 kJ/kg, an energy density of 4.01 kWh/m3, and a compression efficiency of 89.97%.
Leaf vein segmentation is a key technology supporting quality inspection and processing in the tobacco industry. However, factors such as wrinkles, occlusions, and complex secondary vein structures in acquired tobacco leaf images affect the accuracy of vein segmentation, making the reconstruction and restoration of veins after segmentation particularly important. Existing restoration methods suffer from inadequate accuracy in distinguishing pixels within fractured regions and coarse evaluation of local restoration, failing to meet the requirements for precise repair. To address this issue, this paper proposes an advanced leaf vein restoration algorithm named GDCA-Net. First, to tackle the difficulty in distinguishing between valid and invalid pixels inside and outside fractured areas, a multi-level generator network based on a U-Net structure is designed to expand the receptive field, capturing multi-scale contextual information and improving the quality and continuity of vein structure restoration. Second, to overcome the instability and lack of refinement in evaluating locally restored regions during adversarial training, a spectrally normalized Markov discriminator (SN-PatchGAN) is designed. Spectral normalization stabilizes the adversarial training process and refines the assessment of texture and structural consistency between restored regions and real images. Meanwhile, a multi-task composite objective loss function is constructed to enhance detail preservation and structural integrity. Experimental results show that GDCA-Net performs excellently in leaf vein breakage restoration, achieving a peak signal-to-noise ratio of 29.16 and a structural similarity index of 0.9962, outperforming other restoration methods and providing complete leaf vein data for accurate assessment of tobacco leaf stem content.
Effective gauge-normalization interfaces can leave two scalar inputs with ambiguous microscopic provenance: a projected light-sector response weight and a heavy-sector compliance. We examine a coherent-domain SU(2) construction with a light sector defined by a rank-2 projector and a matching relation containing these inputs. For fixed observable projector and light- and heavy-source covariances satisfying stated nondegeneracy conditions, a single positive quadratic light/heavy parent determines both quantities. Low-frequency Schur reduction fixes the reduced light susceptibility, while the inverse heavy block fixes scalar compliance; normalized response contractions produce the matching inputs. This establishes single-parent sufficiency and joint determination within a fixed realization. The parent-to-scalar map remains many-to-one, so microscopic uniqueness and kernel reconstruction do not follow. Under an explicit constitutive identification of scalar heavy compliance with the component-level dual-response coefficient, we derive the generator-trace and transverse-projection conversion from compliance to stiffness. In a one-heavy-mode completion, the ratio of the heavy-mediated off-diagonal light-Hessian contribution to heavy compliance is independent of the heavy gap for fixed light-heavy couplings. In a calibrated gap scan with the direct channel independently characterized, variation of this ratio excludes the static rank-one completion with gap-independent couplings. A three-resonator coupled-mode construction provides a concrete implementation: two light resonators coupled through a detuned auxiliary resonator realize the rank-one Schur map, and a representative microwave benchmark with 80 and 60 MHz couplings at 1 GHz detuning produces a 4.8 MHz-induced coupling. The result is a conditional provenance theorem and rank-sensitive diagnostic for the normalization interface.
A novel unsteady squeezing flow of a non-Newtonian ternary hybrid nanofluid is investigated by focusing Eyring–Powell fluid rheology in an infinite channel. The nanofluid consists of AA1072, AA1075, and ZrO2 nanoparticles suspended in blood; the analysis incorporates the effects of slip; and diffusion parameters motile micro-organisms and chemical reaction. High-fidelity solutions obtained by employing computational technique in MATLAB and solution is validated by machine learning (ML) technique. The artificial neural network demonstrates excellent agreement with numerical solutions, achieving consistently low MSE and MAE values and coefficients of determination R2≈1 across all flow regimes. From an ML standpoint, the network effectively learns the nonlinear physical scenario concerning governing parameters and flow responses, including strong magnetohydrodynamic damping, slip-induced mobility, and diffusion-dominated transport. Error analyses confirm stable learning without numerical oscillations, while architecture studies identify optimal neuron configurations for accuracy and efficiency. An increase in the magnetic parameter suppresses convection due to the Lorentz force reducing, whereas higher thermal radiation enhances heat diffusion and strengthens wall heat transfer. The entropy generation number increases with the Eckert number due to viscous dissipation converting kinetic energy into thermal energy, thereby enhancing irreversibility. Magnetic parameter intensifies Lorentz-force-induced resistance, further increasing entropy generation and thermodynamic losses in the system. The proposed ML-based framework offers a fast, reliable, and computationally economical surrogate for complex coupled boundary-value problems, ensuring rapid optimization and real-time prediction in investigated blood transport.
To address the risk of pressure surges and explosions caused by internal short-circuit arcs in oil-immersed transformers, this paper first derives formulas for arc discharge energy and bubble pressure. A three-dimensional simulation model of an SFSZ-240000/220 transformer is then established. Pressure source parameters are defined, and the propagation of pressure waves within the insulating oil is analyzed through simulations to clarify the influence of oil properties on wave propagation. Multiple parameters of the simulation model are adjusted, and virtual probes are placed at specific locations on the tank wall. By varying the initial arc position, the number of arcs, and the density of the insulating oil, the system is analyzed from two perspectives: the transient pressure distribution across the tank wall and the resulting mechanical deformation. Based on these findings, suggestions for improving the structural design of the transformer tank are proposed. These results provide theoretical support for the explosion-proof structural design of transformer tanks and the prediction of fault-induced pressure.
Understanding physics governing alloy nanofilm formation with precisely controlled nanostructure and electronic functionality is central to developing next-generation nanoscale technologies. However, achieving simultaneous control of structural continuity and charge transport remains a fundamental challenge. To address this challenge, we have synthesized Pr–Ni–Co (PNC) alloy nanofilms by DC magnetron sputtering and uncovered how deposition time governs their growth pathway. At short deposition times, the film forms discontinuous islands, whereas extended deposition results in rapid coalescence into a continuous and increasingly ordered layer. This morphological transition produces a marked drop in electrical resistance, signaling the emergence of a fully percolated conduction network. Our findings identify deposition time as a decisive parameter coupling microstructural evolution with electronic transport in rare-earth metal alloys, establishing PNC nanofilms as a promising platform for advanced electronic and magnetic technologies, with potential relevance to catalytic systems.
The global minimum search on nanocluster potential energy surfaces remains a formidable challenge due to exponential scaling of local minima with cluster size and composition. Deep reinforcement learning (DRL) offers a promising alternative to traditional genetic algorithms and basin hopping, but prior DRL frameworks are restricted to seven noble metals [via effective medium theory (EMT) potentials] and lack systematic validation. Here, we integrate proximal policy optimization (PPO) with an embedded atom method (EAM) potential to create PPO–EAM–DRL for autonomous nanocluster optimization. The framework is applied to Ag1Ni12, Ag6Ni7, Ag7Ni6, Ag12Ni1, and Pt6Co7 nanoclusters. The agent learns stable exploration policies within 300–500 episodes and consistently identifies lower-energy global minima than those obtained using a Birmingham cluster genetic algorithm, with particularly significant improvements for Ag6Ni7 and Pt6Co7 systems. Machine learning atomic cluster expansion re-optimization further confirms that EAM-derived minima are energetically more stable or equivalent to EMT-derived minima across all investigated Ag–Ni compositions. By replacing EMT with EAM, the proposed framework extends DRL-driven nanocluster optimization from a limited set of metallic systems to a broader transition-metal chemical space. This work establishes a transferable and extensible platform for autonomous materials discovery and global minimum search in multimetallic nanoclusters.
The radial fine structure of lightning channels is crucial for understanding the physical mechanisms of lightning discharge, energy transmission, and lightning protection effects. Traditional theoretical models suggest that lightning channels consist of a high-temperature and high-conductivity core carrying axial current and a corona sheath layer storing charges. In recent years, with the development of high-speed optical imaging, slitless spectroscopy, and near-field electrical measurements, researchers have directly observed the visible channel core in natural lightning for the first time and obtained key parameters such as the radial temperature and conductivity distribution of the channel. This paper systematically reviews the research progress in the radial structure of lightning channels in terms of theoretical models, observational diagnostics, and parameter characteristics, confirming the rationality of the corona sheath model and revealing significant differences in physical properties between the channel core and the corona sheath. Current research is moving from macroscopic models to direct diagnosis of microscopic physical parameters, but key issues such as the formation and evolution mechanism of the channel core, the precise quantification of sheath currents, and the dynamic changes in radial structure at different discharge stages remain unsolved. Future research opportunities lie in multi-platform collaborative observations, the application of high-resolution diagnostic techniques, and the construction of multi-physics field coupling models, while challenges include the extreme difficulty of observations, the uncertainty in parameter inversion, and the deep integration of theoretical models with experimental data.
Magnetic Liquid Double Suspension Bearing (MLDSB) combines electromagnetic suspension with hydrostatic support to improve load-carrying capacity and operational stability. However, failure of an individual hydrostatic support element can destroy the original force balance and induce strongly coupled electromagnetic–hydrostatic transient responses and rotor–stator rub-impact. Existing studies provide limited understanding of this coupled fault behavior, particularly for different hydrostatic failure locations with experimental validation. To address this issue, a three-degree-of-freedom rotor dynamic model incorporating electromagnetic force, hydrostatic supporting force, and nonlinear rub-impact force is established. Three representative failure modes, namely, lower-, upper-, and right-element failures, are investigated, and the effects of liquid-film thickness, coating thickness, bias current, and supply pressure on the rotor dynamic response are analyzed. The results show that the failure location strongly affects the transient response, with lower-element failure producing the most severe rub-impact behavior, followed by upper- and right-element failures. Increasing the liquid-film thickness, coating thickness, and supply pressure intensifies the rub-impact response, whereas increasing the bias current suppresses it. Experimental comparisons of rotor trajectory, electromagnetic force, and hydrostatic force show trends consistent with the simulations, supporting the capability of the proposed model to capture the principal transient characteristics of MLDSB under hydrostatic failure. The results provide a basis for fault diagnosis, parameter optimization, and safe operation of MLDSB systems.
A mid-infrared InP-based quantum cascade laser (QCL) structure is directly grown by molecular beam epitaxy on an 8-in. Ge-coated Si template. The semiconductor structure employs a metamorphic (GaAs/AlInAs) buffer and a strain-compensated active region comprising 26 stages based on an Al0.68In0.32As/Ga0.32In0.68As composition to achieve a record-high wall plug efficiency of 11% for a mid-infrared QCL-on-Si and a peak optical output power exceeding 10 W from a 10 mm × 30.3 μm ridge waveguide device. The device emission wavelength is centered at λ = 4.4 μm. Characterization by cathodoluminescence and transmission electron microscopy reveals a threading dislocation density of 1.0 × 107 cm−2 in the upper cladding and 3.7 × 107 cm−2 in the active region. These results present an advancement in the integration of high performance QCLs on silicon photonic platforms, further paving the way for scalable, low cost mid-infrared photonic integration.
A recent article [R. O. Ocaya and F. Yakuphanoğlu, Measurement 186, 110105 (2021)] presented the Ocaya–Yakuphanoglu (OY) method of device parameter extraction, wherein the current–voltage (I–V) equation of metal–oxide–semiconductor and metal–semiconductor devices in the thermionic emission (TE) model was reformulated as a differential equation. The solution revealed a fundamental but previously hidden symmetry in the device characteristics and rigorously proved that series resistance, Rs, is not constant but rather the instantaneous slope (dV/dI) of the I–V curve. The application of Rs reduced the TE equation and restored the true junction voltage, effectively removing bias-induced distortions in the extracted parameters. Consequently, the calculated barrier height, ΦB, is effectively invariant across bias, consistent with its intrinsic physical origin. Here, we extend the OY method by revealing a previously unrecognized relationship between Rs, ΦB, and applied bias, showing that it is intrinsic to Schottky transport and naturally explains the exponential decay with bias frequently observed in empirical studies; this enables reliable extraction of the diode parameters at their intrinsic limits, free from field induced distortions. Measurements on an Al/p-Si/2OD-TIFDKT/Al Schottky diode under 100 mW/cm2 illumination demonstrate that the OY method reproduces the expected trends in Rs and outperforms the Cheung and Norde methods.
Premixed hydrogen–air deflagration in a half-open channel can produce local compression and flame-induced flow redistribution even when downstream pressure relief is available. Three-dimensional compressible reacting-flow simulations are used to examine the flame-head morphology, center-ahead pressure loading, and recessed-center wake motion in a straight channel with one closed end and one open end. Four diagnostics are extracted with a common post-processing framework: flame-head splitting, local center-ahead overpressure, tip–center velocity separation, and wake backflow. The stoichiometric mixture is used as the reference case, and neighboring leaner and richer mixtures test how mixture strength shifts the same response sequence. Under the present half-open confinement, the initially compact flame develops a center-plane-dominant split front. Local compression then appears ahead of the recessed center while branch-tip dominance and negative wake velocity strengthen together. Across the tested mixtures, the richer case enters the coupled response earlier in absolute time, whereas the stoichiometric case retains the strongest late-stage structural response at matched normalized stages. The analysis emphasizes large-scale flame topology, response timing, and inter-case trends under a common numerical closure. The resulting framework links split morphology, local pressure loading, and flow redistribution in half-open premixed reacting-flow configurations.
The speed and system reliability of magnetic reluctance-launched projectiles have been theoretically and experimentally verified. However, there is little research on the flight stability of such low-speed, non-spinning, and fin-stabilized projectiles, which affects the law enforcement application of this technology. This article establishes an analysis framework that couples steady-state computational fluid dynamics, unsteady forced oscillation transient computational fluid dynamics, and a rigid body trajectory model. Utilizing a linear least-squares fitting method based on the first-harmonic assumption, a static and dynamic aerodynamic database is constructed within the range of velocity of 20 to 60 m/s and an angle of attack range of −6° to +6°. The results show the following: (1) Under the studied operating conditions, the static stability margin of the projectile is 10%–22%, showing good static recovery ability, and the change in drag coefficient is relatively small. (2) The absolute value of the pitch combination dynamic derivative increases with the increase in speed, indicating that the increase in flight speed helps to enhance the dynamic damping capability. (3) The external ballistic simulation shows that under the selected typical initial angle of attack disturbance operating conditions, the projectile attitude can quickly converge in a short period of time, and the amplitude of angle of attack change during flight is small, exhibiting good attitude stability. The research can provide methodological support for the aerodynamic parameter analysis, external trajectory modeling, and flight stability evaluation of low-speed, non-spinning, and fin-stabilized, less-lethal projectiles and provides a reference for the design optimization and engineering application of related less-lethal projectiles.
Flexible triboelectric sensors are promising for wearable physiological and motion monitoring by converting body-induced mechanical stimuli into electrical signals. However, stable sensing across different signal scales, from subtle physiological fluctuations to large-amplitude body motions, remains challenging. Here, a flexible silver–aluminum conductive silicone-based triboelectric sensor, named SACS-sensor, is developed for wearable physiological and motion sensing. The device adopts a single-electrode structure, in which the silver–aluminum conductive silicone serves as the flexible electrode and the outer silicone rubber functions as both the encapsulation layer and triboelectric contact interface. The sensor exhibits repeatable force-dependent outputs over 20–200 N, with segmented linear sensitivities of 0.130 V N−1 below 100 N and 0.040 V N−1 above 100 N. It also maintains stable electrical output after 10 000 loading cycles. When attached to the wrist, the sensor captures coupled pulse–respiration signals, which can be separated by frequency-domain filtering. It further enables monitoring of throat-related activities and multi-joint motions. This study provides a simple and flexible triboelectric sensing strategy for wearable physiological and motion monitoring.
