Quantitative Effects of Porous Obstruction Number on Explosion Dynamics of CH/H Mixtures.

This study investigates the effects of porous obstruction quantity on the explosion dynamics of CH/H hybrid fuel mixtures in semiconfined pipelines through integrated experimental and numerical approaches. High-frequency pressure transducers and ultrahigh-speed cameras were employed to record overpressure evolution and flame morphology, while numerical simulations incorporating the Charlette flame wrinkling model elucidated turbulence-flame interaction mechanisms. The study compared configurations with sequential porous obstructions to single-obstruction setups, revealing that obstruction number and blockage ratio critically govern flame speed, peak overpressure, and turbulent intensity.

A Turn-on Fluorescent Chemical Sensor Based on Imidazole-Schiff Base Structure for Al Detection as Well as Applications.

In this study, a novel imidazole-Schiff base fluorescent probe, EBI, was designed and synthesized. The molecular structure of EBI was systematically characterized by FT-IR, H NMR, C NMR and HR-MS. This study found that this probe could exhibit highly sensitive and selective fluorescence responses to Al in an EtOH/HO (1:1 v/v) mixed solvent.

Experimental Investigation of Obstruction Effects on CH/H Hybrid Fuel Explosion Dynamics in Semiconfined Pipelines.

This study systematically investigates the effects of porous obstacle blockage ratios on the explosion characteristics of CH/H mixtures in semiconfined pipelines through experimental methods. High-speed imaging and high-frequency pressure sensors were employed to simultaneously capture flame propagation dynamics and pressure field evolution. The results demonstrate that porous obstacles significantly alter flame propagation mechanisms.

DGS-Yolov7-Tiny: a lightweight pest and disease target detection model suitable for edge computing environments.

Pest detection is vital for maintaining crop health in modern agriculture. However, traditional object detection models are often computationally intensive and complex, rendering them unsuitable for real-time applications in edge computing. To overcome this limitation, we proposed DGS-YOLOv7-Tiny, a lightweight pest detection model based on YOLOv7-Tiny that was specifically optimized for edge computing environments.

Exogenous Melatonin Application Improves Shade Tolerance and Growth Performance of Soybean Under Maize-Soybean Intercropping Systems.

Maize-soybean intercropping is widely practised to improve land use efficiency, but shading from maize often limits soybean growth and productivity. Melatonin, a plant signaling molecule with antioxidant and growth-regulating properties, has shown potential in mitigating various abiotic stresses, including low light. This study investigated the efficacy of applying foliar melatonin (MT) to enhance shade tolerance and yield performance of soybean under intercropping.

Alternating Multilayered TiCT/Co Sandwich with Co Frosting for Superior Electromagnetic Wave Absorption Performance and Infrared Stealth Ability.

MXene-based wave-absorbing materials face challenges in practical applications such as severe sheet stacking and low dielectric loss. Herein, we used two-dimensional (2D) layered TiCT MXene as the backbone and stereoscopic magnetic cobalt (Co) crystals as the buttress and coating to design a connected three-dimensional layered sandwich heterostructure. By adjustment of the ratio of raw materials, Co crystals were anchored both within the interlayer gaps of the adjacent 2D sheets and on their surfaces through electrostatic and ion-dipole interactions with the functional groups of TiCT.

Titanate-Coupled Aluminum as an Interfacial Modifier for Enhanced Thermal and Mechanical Performance in Hybrid Epoxy Composites.

Thermally conductive polymer composites are essential for effective heat dissipation in electronic packaging, where both thermal management and mechanical reliability are critical. Although diglycidyl ether of bisphenol-A (DGEBA)-based epoxies exhibit favorable properties, their intrinsically low thermal conductivity limits broader applications. Incorporating conductive fillers, such as expanded graphite (EG) and metal powders, enhances heat transport but often compromises mechanical strength due to poor filler-matrix compatibility.

A Highly Selective Turn-On Fluorescence Sensor for Detecting Hg Based on Flavonol and Its Applications in Fluorescence Imaging.

Hg has harmful toxicity to both ecosystems and biological systems, so accurate monitoring of Hg is essential. Herein, a novel turn-on fluorescence sensor (HTZ) cooperating flavonol with thiocarbonate group was prepared. It exhibited a wider linear range (0-1 μM) and an ultra-low detection limit (8.

Pyrrole-Modified Two-Dimensional Carbon Nitride Nanoparticles Realize Super-Resolution Imaging.

Graphitic carbon nitride (g-CN), as an excellent optoelectronic material, has potential applications in bioimaging. However, the original g-CN has an excessively large size and poor water solubility and is difficult to modify, making it unsuitable for direct use in bioimaging. Here, we propose an efficient modification scheme.

A novel transcendental metaphor metaheuristic algorithm based on power method.

This paper proposes a novel metaheuristic algorithm-the Power Method Algorithm (PMA), which is inspired by the power iteration method to solve complex optimization problems. PMA simulates the process of computing dominant eigenvalues and eigenvectors, incorporating strategies such as stochastic angle generation and adjustment factors, effectively addressing eigenvalue problems in large sparse matrices. The algorithm is rigorously evaluated on 49 benchmark functions from the CEC 2017 and CEC 2022 test suites.

Dung beetle optimizer based on mean fitness distance balance and multi-strategy fusion for solving practical engineering problems.

As a swarm intelligence algorithm, Dung beetle optimizer (DBO) was inspired by the behavior pattern of dung beetles for survival. This paper presents a dung beetle optimizer based on mean fitness distance balance and multi-strategy fusion (MMDBO), which addresses the slow convergence and weak global search of the original DBO. MMDBO improves performance by incorporating a cosine similarity strategy for position updates, enhancing convergence speed and diversity.

Reconstruction of cobalt magnesium aluminum hydrotalcite loaded ruthenium using the memory effect for selective oxidation of 5-hydroxymethylfurfural under alkali-free conditions.

The hydrotalcite CoMgAl-LDH was prepared using a hydrothermal method. The calcined hydrotalcite was rehydrated utilizing its "memory effect", and the catalyst Ru/CoMgAl-RLDH was prepared by loading ruthenium nanoparticles through the impregnation reduction method. The pristine hydrotalcite CoMgAl-LDH exhibited a specific surface area of 9.

Short-term traffic flow prediction research based on ICEEMDAN-MPE-PSO-DELM model.

Based on historical data, a new short-term traffic flow prediction model (ICEEMDAN-MPE-PSO-DELM-ARIMA) for intersections is proposed. In order to improve prediction accuracy, ICEEMDAN decomposition algorithm is applied on traffic flow time series to obtain multiple Intrinsic Mode Function (IMF) components. Then PSO-MPE algorithm is introduced to obtain the multi-scale permutation entropy values of each IMF component, to judge the randomness.

Bearing remaining useful life prediction based on optimized VMD and BiLSTM-CBAM.

To address the issue of low accuracy in existing remaining useful life (RUL) prediction algorithms for rolling bearings, this paper proposes a novel RUL prediction method based on the Beluga Whale Optimization (BWO) algorithm, Variational Mode Decomposition (VMD), an improved Convolutional Block Attention Module (CBAM*), and a Bidirectional Long Short-Term Memory (BiLSTM) network. First, BWO is utilized to optimize the parameters of VMD, which is then applied to decompose and reconstruct the original vibration signals. Subsequently, time-domain and frequency-domain features are extracted from the reconstructed data to construct a degradation feature set.

The MnO/biochar composite prepared from straw biochar and divalent manganese: investigation of synthetic conditions and malachite green degradation.

In this study, the goal was to recycle and reuse manganese in wastewater by use of a cheap material biochar, ammonia, and hydrogen peroxide to produce a MnO/biochar composite, which could be used for the degradation of dye in wastewater (MG has been selected as a candidate dye mode here). The experiment condition of was optimized, and MnO/biochar composite has been characterized by TEM, XRD, XPS and N adsorption-desorption. The kinetics and isotherm of malachite green (MG) degradation were well described by the pseudo-second-order and pseudo-first-order kinetic modes, indicating that as prepared MBC both have good adsorption and photocatalytic capacity due to its component of biochar and MnO.

Research Progress in and Defect Improvement Measures for Laser Cladding.

Laser cladding, a cutting-edge surface modification technique for metals, offers a novel approach to enhancing the wear and corrosion resistance of substrates due to its rapid heating and cooling capabilities, precise control over coating thickness and dilution rates, and non-contact processing characteristics. However, disparities in the physical properties between the coating material and the substrate, coupled with the improper utilization of process parameters, can lead to coating defects, thereby compromising the quality of the coating. This paper examines the effects of material systems and process parameters on laser cladding composite coatings and shows that cracking is mainly caused by thermal and residual stresses.

Exploring the Gas Permeability of Type IV Hydrogen Storage Cylinder Liners: Research and Applications.

As hydrogen fuel cell vehicles gain momentum as crucial zero-emission transportation solutions, the urgency to address hydrogen permeability through the polymer liner becomes paramount for ensuring the safety, efficiency, and longevity of Type IV hydrogen storage tanks. This paper synthesizes existing research findings, analyzes the influence of different materials and structures on gas permeability, elucidates the dissolution and diffusion mechanisms of hydrogen in plastic liners, and discusses their engineering applications. We focus on measurement methods, influencing factors, and improvement strategies for liner gas permeability.

Influence of Cr- and Co-Doped CaO on Adsorption Properties: DFT Study.

Using the combination of Concentrated solar power (CSP) and calcium looping (CaL) technology is an effective way to solve the problems of intermittent solar energy, but calcium-based materials are prone to sintering due to the densification of the surface structure during high-temperature cycling. In this study, the enhancement mechanism of Co and Cr doping in terms of the adsorption properties of CaO was investigated by Density Functional Theory (DFT) calculations. The results indicate that Co and Cr doping shortens the bond length between metal and oxygen atoms, enhances covalent bonding interactions, and reduces the oxygen vacancy formation energy.

Micro-Galvanic-Driven Scalable Synthesis of Heterostructured Nanoarrays for Durable Anion Exchange Membrane Water Electrolysis.

The scalable synthesis of alkaline hydrogen evolution (HER) electrocatalysts that integrate high activity with operational durability is essential for advancing practical anion exchange membrane water electrolysis (AEMWE). Herein, vertical Cu-MoNi heterostructures are fabricated via a self-driven galvanic-corrosion-coupled low-temperature reduction strategy, circumventing hydrothermal protocols for scalable electrode fabrication. The catalyst achieves a low overpotential of 276 mV and exceptional stability for up to 2000 h at an ampere-level current density of 1 A cm in 1 m KOH.

Workpiece surface defect detection based on YOLOv11 and edge computing.

The rapid development of modern industry has significantly raised the demand for workpieces. To ensure the quality of workpieces, workpiece surface defect detection has become an indispensable part of industrial production. Most workpiece surface defect detection technologies rely on cloud computing.

The preparation of ratio-fluorescent/T weight dual mode imaging material PAA/manganese dioxide/graphene quantum dots composites and its application on quantitative analysis of HPO.

Fluorescence/magnetic resonance dual-mode imaging combines the high spatial and temporal resolution of magnetic resonance with the real-time imaging performance of fluorescence, which has high sensitivity and deep tissue penetration, and has become one of research focus in late years. In this paper, PAA/manganese dioxide/graphene quantum dots composites (AMQ) with dual fluorescence emission wavelengths and short T-weight imaging time (about 1 min) has been synthesized by polyol method with PAA, ascorbic acid and divalent manganese ions as main raw materials. As prepared fluorescence/T weight image material AMQ was used for quantitative analysis of HPO, of which LOD are 0.

Curtailing Non-Radiative Recombination and Tailoring Interfacial Energetics via Bimolecular Passivation toward Efficient Inverted Perovskite Solar Cells.

Despite significant development of perovskite solar cells (PSCs) in recent years, presence of nonradiative recombination centers at the perovskite surface, grain boundaries, and interfaces remain a major bottleneck in achieving the desired device performance. Also, energy levels offset among perovskite and neighboring functional layers leads to poor charge extraction, thereby further limiting the device capability. Therefore, it is essential to carefully understand the underlying defects and develop a suitable passivation technique to suppress such detrimental imperfections.

C nanofibers dotted with metal-organic framework (MOF)-derived square Fe@C crystals for enhanced electromagnetic wave absorption performance.

C nanofibers dotted with square Fe@C crystals derived from metal-organic frameworks (MOFs) with a novel 3D hierarchical architecture were successfully prepared through electrospinning, hydrothermal processing, and high-temperature pyrolysis. The introduction of carbon nanofibers endowed the particles with directional action and mechanical support, inhibiting local agglomeration and the collapse of the Fe@C crystals. The unique overall 3D porous structure with micro-concavities on its surface provided sufficient paths for electromagnetic wave transmission, abundant heterostructured interfaces for interfacial polarization and a connected network for conductive loss.

MDCFVit-YOLO: A model for nighttime infrared small target vehicle and pedestrian detection.

An MDCFVit-YOLO model based on the YOLOv8 algorithm is proposed to address issues in nighttime infrared object detection such as low visibility, high interference, and low precision in detecting small objects. The backbone network uses the lightweight Repvit model, improving detection performance and reducing model weight through transfer learning. The proposed MPA module integrates multi-scale contextual information, capturing complex dependencies between spatial and channel dimensions, thereby enhancing the representation capability of the neural network.

Performance optimization of Co/Zn-ZIF-8/PDMS mixed-matrix membranes based on tubular ceramic carriers for ethanol recovery pervaporation.

In the present investigation, highly hydrophobic Zn-ZIF-8 nanoparticle-filled polydimethylsiloxane (PDMS)-based mixed-matrix membranes (MMMs) were prepared from tubular ceramic carriers to meet the requirements of industrial applications, which were better than ZIF-67/PDMS (Co-ZIF-8/PDMS) MMMs in overall performance for ethanol recovery from aqueous solutions. Their separation factor for pervaporation was greatly enhanced compared with the pristine PDMS membrane; however, the flux reduction was slightly larger (flux-separation factor trade-off effect). Furthermore, CoZn-ZIF-8/PDMS MMM was prepared through the substitution of Zn with Co in the Zn-ZIF-8 framework filler.