Search Results (235)

Thermal management is critical for maintaining the safety and performance of lithium-ion batteries. Phase change materials (PCMs) have been widely studied as passive cooling media due to their high latent heat capacity, but major technical challenges remain due to their relatively low thermal conductivity and nanoparticle sedimentation in composite systems. In this work, a composite phase change material (PCM) consisting of paraffin wax, a microencapsulated phase change material (MicroPCM 28D), and nano carbon black is developed to enhance thermal stability and suppress particle sedimentation through increased viscosity of the PCM matrix. Five capsule geometries fabricated by fused filament fabrication (FFF) 3D printing are experimentally investigated under airflow velocities ranging from 0 to 10 m s⁻¹. Wind tunnel experiments with infrared thermography are used to evaluate the thermal response of the PCM capsules. The results show that airflow velocity and capsule geometry strongly influence heat dissipation behavior. Compared with conventional wax composites, the MicroPCM 28D composite capsules reduce peak temperature by approximately 2–4 °C under airflow velocities of 0–10 m/s. These findings provide insights into geometry-regulated convection and stable composite PCM design for lithium-ion battery thermal management systems. Full article

Traditional road tunnel ventilation systems suffer from high energy consumption and limited effectiveness in fire smoke control. Thus, there is a pressing need to develop advanced air purification technologies that integrate low energy demand with efficient smoke mitigation capabilities. In this study, a self-developed negative ion purification system was implemented, and systematic full-scale experimental investigations were conducted in both a test tunnel and an operational road tunnel to evaluate its performance in air purification and smoke suppression under normal operation and fire conditions. Key parameters, including negative ion concentration, particulate matter concentration, carbon monoxide (CO) concentration, and smoke distribution characteristics, were measured to elucidate smoke evolution behavior and the underlying mechanisms influenced by negative ions. The results show that the negative ion purification system can rapidly establish a high-concentration negative ion field within the tunnel space. Under normal operating conditions, negative ions markedly reduce particulate matter concentrations and their fluctuations, thereby effectively improving tunnel air quality. Under fire conditions, the system maintains high purification efficiency, with significant reductions in particulate matter concentration observed in the test tunnel and clear suppression of longitudinal particulate transport in the real tunnel. In particular, PM10 exhibits a higher removal efficiency. In addition, negative ions promote particle agglomeration and gravitational settling, accelerate CO dilution and dispersion, and significantly improve tunnel visibility. The results demonstrate that the negative ion purification system exhibits strong applicability and considerable engineering potential across different spatial scales and fire scenarios. Full article

We report the design, epitaxial growth, and room-temperature operation of a high-gain AlInAsSb-based avalanche photodiode (APD) for short-wavelength infrared (SWIR) detection at 1.55 µm. The device employs SAGCM structure to confine the electric field within the multiplication region while suppressing dark current. High-quality AlInAsSb layers were grown on GaSb substrates by molecular beam epitaxy using a digital alloy approach, achieving excellent surface morphology (R_a < 0.2 nm) and uniform superlattice periodicity. Electrical characterization reveals a well-defined breakdown voltage near −17 V and a peak internal multiplication gain of 200 at 300 K under 0.2 mW illumination at 1550 nm—among the highest gains reported to date for antimonide-based APDs operating at room temperature. Variable-temperature dark current analysis indicates a transition from tunneling-dominated to thermally generated dark current as temperature increases from 100 K to 300 K. These results demonstrate the strong potential of AlInAsSb SAGCM APDs for eye-safe, high-sensitivity applications in LIDAR, free-space optical communication, and low-light SWIR imaging. Full article

The efficient fabrication of high-quality Ni60-WC composite coatings with low dilution and defect density remains a challenge for wear-critical tunneling cutters. In this study, a plasma–laser hybrid cladding (PLHC) strategy was developed to fabricate Ni60-40 wt% WC composite coatings, and their microstructures and properties were systematically compared with those produced by plasma cladding (PC) and laser cladding (LC). The PLHC coatings exhibit a low dilution rate of 10.7% and an ultra-low porosity of 0.2%, indicating improved metallurgical integrity. Microstructural analysis reveals that the hybrid energy input effectively suppresses WC dissolution and promotes a refined, uniformly distributed hard-phase network within the Ni-based matrix. As a result, the PLHC coatings achieve a high average microhardness of 1187.83 HV_1.0 and superior wear resistance, with a wear volume of 24.69 × 10⁻³ mm³ under a 200 N load, representing reductions of 53.6% and 20.9% compared with PC and LC coatings, respectively. These results demonstrate the effectiveness of plasma–laser hybrid cladding in tailoring the microstructure–property relationship of WC-reinforced composite coatings. Full article

Electron correlation and quantum interference are pivotal in mesoscopic transport. We theoretically study the nonequilibrium transport dynamics of a triangular triple-quantum-dot (TTQD) molecule connected to fermionic reservoirs using the exact hierarchical equations of motion (HEOM) formalism. We demonstrate a counterintuitive transport signature in which the stationary current is significantly enhanced by increasing U, a behavior distinct from the suppression typically observed in linear quantum dot arrays. By analyzing the evolution of spectral functions, we attribute this enhancement to the interplay between Coulomb-interaction-induced energy shifts and quantum interference effects specific to the triangular topology. We also explore how the circulation of chiral currents and electrode coupling strength modulate these interaction effects. Finally, we present a three-dimensional map of the transport current as a function of inter-dot tunneling (t) and Coulomb interaction (U), illustrating their combined effect on the current magnitude and its applications. Full article

With the rapid development of underground space, structural crack monitoring has become increasingly critical. This study proposes a unified framework integrating image preprocessing, feature extraction, model training, and safety assessment for crack analysis. An improved OTSU threshold segmentation algorithm based on sliding windows and local statistical analysis is developed to enhance noise suppression and detail preservation under complex backgrounds and varying resolutions. For crack identification and orientation classification, SVM, CNN, ResNet-18, and K-means clustering are systematically compared. The results show that the improved OTSU method outperforms the classical approach in both high- and low-resolution images. In classification tasks, SVM achieves the best performance under limited data conditions, with accuracy exceeding 96% and reaching 97% after outlier removal, outperforming CNN, K-means, and ResNet-18. Although ResNet-18 demonstrates strong overall performance with high prediction confidence across crack categories, it remains slightly inferior to SVM when training data are limited. Experimental validation using full-scale loading tests of metro shield tunnel segments further confirms the robustness of the proposed approach, with SVM achieving an accuracy of 95.45% in real-world conditions. This study provides an efficient and reliable solution for automated crack detection and classification in metro tunnel infrastructure and similar underground segment-based systems. Full article

Large-span bridges with bluff body girders are susceptible to vortex-induced vibration (VIV) due to their low frequency, light mass, and relatively low damping ratio, affecting fatigue life and serviceability. While research progress has been made on VIV mechanisms and control measures, systematic investigations on the application of vortex generators (VGs) to narrow Π-shaped railway girders remain scarce, and the potential synergistic effect of combining VGs with conventional aerodynamic measures has not been explored. To address this gap, wind tunnel tests were conducted on a 1:50 scale sectional model of a narrow Π-shaped steel girder for a railway cable-stayed bridge. The experimental program systematically investigated the VIV response of the original girder and evaluated the suppression effectiveness of conventional aerodynamic measures (vertical stabilizers, deflectors, modified fairings) and spanwise control using VGs. Parametric optimization of VG height (0.1 H–0.2 H, where H is the girder height), spacing (2/3 L₀ and L₀, where L₀ = 12.5 m is the standard segment length), and installation position (upper fairing, lower fairing, girder bottom) was performed. Results show that under wind angles of attack from −5° to +5° and a damping ratio of 0.36%, the original girder exhibits pronounced vertical VIV with a maximum RMS amplitude of 0.025 m, approximately 3.15 times the code limit. Conventional measures alone fail to adequately suppress VIV. However, the optimal combination of VGs (height 0.2 H, spacing L₀, installed on the lower fairing) with a 0.5 m wide, 15° inclined deflector effectively suppresses VIV under wind AOAs of 0°, ±3°, and –5°, achieving suppression below the measurable threshold. This study contributes the first comprehensive parametric investigation of VGs for narrow Π-shaped railway girders, reveals a synergistic effect when combining VGs with deflectors, and incorporates practical engineering constraints (such as aesthetic requirements) into the optimization process. Full article

Aiming at the problems of microseismic signals from rock mass fracture in deep-buried tunnels with low signal-to-noise ratio (SNR) suffering from coupled interference of multi-source noise, and traditional filtering methods having fixed parameters and poor processing effects on spectral aliasing, this study proposes a ternary coupled adaptive filtering method integrating the Sparrow Search Algorithm, Variational Mode Decomposition and Wavelet Threshold Denoising (SSA-VMD-DWT). First, the noise intrusion characteristics of low-SNR microseismic signals in deep-buried tunnels were analyzed, and the filtering difficulties of white noise, low-frequency noise, high-frequency noise and non-stationary noise were clarified. Subsequently, a parameter optimization framework with the Sparrow Search Algorithm (SSA) as the core was constructed to optimize the key parameters, including the penalty factor α and modal number K of Variational Mode Decomposition (VMD), as well as the wavelet basis and decomposition layers of Wavelet Threshold Denoising (DWT), respectively. A dual-index threshold decision function based on kurtosis and correlation coefficient, and a wavelet packet entropy weighted reconstruction algorithm were designed to realize the collaborative adaptive adjustment of decomposition depth and threshold rules. Finally, the performance of the algorithm was verified through simulation signal experiments and an engineering case of a deep-buried tunnel in Southwest China. The results show that for the simulated signal with a low SNR of 2 dB, the SNR is increased to 12.43 dB, and the root mean square error is reduced to 2.36 × 10⁻⁷ after denoising by this algorithm, which is significantly superior to the Empirical Mode Decomposition (EMD) and traditional DWT methods. In the engineering case, the information entropy of the filtered signal is the lowest among all methods, which can effectively suppress multi-band noise and retain the core characteristics of microseismic signals from rock mass fracture, solving the problems of spectral aliasing, detail loss and empirical parameter setting of traditional methods. This method provides a new technical paradigm for the processing of low-quality microseismic signals in deep tunnel engineering and can improve the accuracy of monitoring and early warning for rock mass dynamic disasters. Full article

With the increasing use of reinforced concrete segments in large-scale tunnels, engineering projects have placed higher mechanical demands on concrete, and the choice of concrete materials significantly influences these mechanical properties. This study is based on the preliminary mix design for the concrete used in the Second Undersea Tunnel Project, with the mass content of nano-SiO₂ (NS) (1–3%), the volume content of steel fibers (SF) (0.5–1.5%) and the volume content of polypropylene fibers (PPF) (0.05–0.25%) as independent variables and using compressive strength (Y₁), splitting tensile strength (Y₂), and toughness index (Y₃) as response variables. Using the Box–Behnken response surface design method, response surface models for each parameter were established and analyzed. The effects of NS, SF, and PPF on the mechanical properties of the concrete were investigated. Combining the MOPSO algorithm and the entropy-weighted TOPSIS method, a multi-objective cooperative optimization study was conducted. Finally, a microstructural analysis of the optimal NSDHFRC was performed. The results indicate that Y₁, Y₂, and Y₃ all initially increase and then decrease with increasing NS content; Y₁ and Y₃ increase with increasing SF content. However, when the SF content exceeds a certain level, the fiber spacing becomes too dense, weakening the effective bridging effect between fibers, resulting in a decrease in Y₂ at excessively high SF contents; PPF can suppress crack formation within a certain content range, but its effect on Y₁ is relatively weak. Due to agglomeration and water absorption, both Y₂ and Y₃ decrease when the PPF content is too high. It was determined that the optimal solution occurs when the mass fraction of NS is 2.15%, and the volume fractions of SF and PPF are 1.37% and 0.063%, respectively, with Y₁, Y₂, and Y₃ being 69.94 MPa, 5.49 MPa, and 1.99, respectively. Experimental verification confirmed that the relative error is within 5%. A microscopic analysis of the optimal solution revealed that an appropriate amount of NS refines the concrete structure through physical and chemical reactions, improves the interface transition zone, and enhances the bond strength between the fibers and the matrix. Meanwhile, PPF and SF distribute stress, respectively delaying the propagation of microcracks and macrocracks during different loading stages. These findings provide a reference for practical engineering applications. Full article

In this work, a high-performance mid-wave infrared (MWIR) photodetector (PD) utilizing an InAs/GaSb Type-II superlattice absorber and a quaternary AlGaAsSb barrier is designed and analyzed based on numerical simulations aimed at determining an optimized detector structure. Through these simulations, the composition of the AlGaAsSb barrier is carefully designed to achieve lattice matching, high conduction band offset and zero valence band offset. By optimizing the barrier thickness and doping concentration, the depletion region is effectively shifted from the narrow-bandgap absorber to the wide-bandgap barrier; additionally, at 150 K and a reversed bias of 0.05 V, the dark current density in the PD with the barrier (pBn) is reduced to 1.83 × 10⁻⁵ A/cm², about two orders of magnitude lower than that of the PD without the barrier. Furthermore, the effect of the barrier on the generation–recombination (G-R) and the trap-assisted tunneling (TAT) currents are analyzed and compared in detail, and it is found that the barrier structure is much more effective in suppressing the TAT current at low reversed bias when the electric field is low in the absorber layer. These results demonstrate the efficacy of the proposed AlGaAsSb barrier design for realizing high-operating-temperature MWIR PDs. It also provides an insight into the physical mechanism that leads to the performance enhancement of InAs/GaSb PDs. Full article

Polypropylene fibers provide an innovative solution for enhancing the crack resistance of tunnel lining segments. However, existing macro-models obscure the distinct effects of fibers on the mortar and ITZ, while explicit meso-modeling remains computationally prohibitive. This study develops a multi-scale modeling framework to investigate PFRC segment fracture under bending. The framework integrates a 3D meso-scale module for calibrating fracture-related material properties, a 3D macro-scale module for predicting global displacements, and a 2D meso-scale module for resolving local fracture processes. A full-scale bending test was performed to validate the framework and to examine the effects of fiber content at both scales. Both the full-scale test and numerical simulations show that the segment response exhibits three stages: elastic, damage development, and cracking at the design load. Numerical simulations further reveal that an optimal fiber content of 0.4% reduces the vertical displacement at the load point by 9.8% and the horizontal displacement at the edge point by 2.9% relative to the fiber-free case. Meso-scale simulations show that 0.4% fibers decrease the bottom crack width from 0.0868 to 0.0770 mm (−11.29%) and limit internal crack connectivity. Although fibers may locally promote ITZ cracking due to reduced mortar–aggregate bonding, a strengthened mortar matrix suppresses crack penetration and connected crack networks. A pronounced high-damage peak in the ITZ near the failure threshold confirms the ITZ as the governing weak link; therefore, further improvements may require ITZ-strengthening strategies. Full article

Reliable positioning and mapping in roadway tunnels are crucial for vehicle-based monitoring and inspection, especially considering the challenging environmental conditions such as rapidly changing illumination, low-texture environments, and repetitive structural elements. While general LiDAR-inertial odometry (LIO) frameworks and loop-closure detection methods are effective in general scenarios, they often suffer from severe drift or incorrect loop constraints under these specific conditions. These challenges are further exacerbated by the inherent uncertainties associated with low-cost sensors. This paper introduces a narrow field-of-view LiDAR-centric RTK-visual-inertial SLAM system enhanced by three key modules: semantic-assisted loop detection and matching, two-stage RTK quality control, and adaptive factor graph optimization (FGO). In the first module, the proposed semantic loop descriptor (SLD) matching is used to determine the potential loop closure locations and then integrates the corresponding constraint as graph nodes. The quality control module addresses RTK outlier rejection during tunnel entry and exit, employing an event-driven stochastic model to characterize the uncertainty between RTK and the other sensors, effectively suppressing RTK-induced errors. FGO module performs optimization by incorporating LIO, RTK, and loop closure factors, employing a keyframe-based strategy to produce globally optimized poses while continuously updating the map. The proposed Tunnel-SLAM was evaluated against state-of-the-art SLAM algorithms in four extended roadway tunnels, ranging in traveling distance approximately from 5 to 10 km. Experimental results demonstrate that the proposed SLAM achieved a final drift of less than 2 m with loop closure, demonstrating significantly reducing the drift, while other existing SLAM frameworks fail catastrophically or have large drift. Full article

Wildland fire behaviour is strongly governed by the coupled effects of wind and terrain slope, yet the literature remains fragmented across experimental, empirical, mathematical, and physics-based modelling traditions. A systematic scoping review with narrative synthesis was performed (Web of Science, Scopus, and Google Scholar plus citation chaining), screening studies for explicit wind–slope treatment with reported forcings and outcomes. Across more than 150 studies, slope benches, wind tunnels, trenches/canyons, and field burns show that upslope–wind alignment promotes flame attachment and a shift from radiation-led to convection-led preheating (often near 20–30° slopes and moderate winds), whereas opposing or downslope forcing lifts flames and suppresses spread; confined geometries can trigger eruptive acceleration. Mathematical analogues and empirical models provide fast predictions using compact wind/slope modifiers and enable scenario and burn-probability mapping but typically prescribe coupling and miss regime transitions. Physics-based LES/CFD and coupled atmosphere–fire systems resolve terrain–flow feedback sand can yield reduced-order laws suitable for embedding into operational tools, albeit at higher computational cost and with validation gaps. Benchmarks are consolidated, approaches are compared using a common rubric (fidelity, validation, applicability, cost, and operational utility), and priorities are identified for cross-scale datasets, firebrand transport in complex terrain, and real-time coupled prediction. Full article

As nanofabrication advances toward atom-by-atom control of surface morphology, plasmonic electrodes and nanogap devices are being pushed into a regime where atomic-scale protrusions and sub-nanometer separations become accessible. In this extreme limit, classical electrodynamics becomes unreliable because it cannot capture quantum effects. To this end, we compute the optical response of metallic sub-nanometer nanogaps containing atomic-scale protrusions by employing quantum hydrodynamic theory (QHT), and benchmark the predictions against the classical local-response approximation (LRA). We revealed that atomic-scale variations in protrusion can leave the far-field scattering spectrum nearly unchanged while profoundly reshaping tnear-field nanofocusing. Upon a continuous decrease in the nanogap, QHT successfully predicts non-monotonic spectral evolution with a redshift-to-blueshift deflection point accompanied via a suppression of field enhancement, whereas LRA yields a continuous redshift and a monotonic increase in field enhancement. We further demonstrated that such an inflection point is tunable, as determined by the atomic morphology of the electrodes, which provide a theoretical foundation for the experimental observation of varied inflection points. These results provide a practical route to optically diagnose and engineer tunneling-enabled charge exchange and quantum-regulated nanofocusing in extreme plasmonic nanogaps, and offer design guidance for molecular-scale optoelectronic and nanophotonic devices. Full article

Hidradenitis suppurativa (HS) is a chronic, recurrent inflammatory skin disease characterized by painful nodules, abscesses, and epithelialized tunnels, predominantly affecting flexural regions. With a global prevalence of approximately 1%, HS has a significant negative impact on quality of life. Multi-omics and histopathology studies have revealed a complex interplay between innate and adaptive immunity in HS, with neutrophils emerging as important drivers of inflammation. While therapies targeting TNF-α and IL-17 isoforms offer a degree of benefit, significant unmet need remains. Neutrophil signatures in HS lesions and the circulation underscore the rationale for selective modulation of neutrophil function. Strategies advancing through clinical trials include inhibition of chemokine-mediated trafficking, neutrophil serine protease inactivation and suppression of neutrophil extracellular traps (NETs), which amplify inflammatory and autoimmune responses. These emerging therapies mark a significant shift toward targeted neutrophil modulation, offering new opportunities to improve outcomes for patients with HS. Full article