Search Results (2,322)

X-band copper resonating cavities are key components of future pulsed GHz normal-conductive multi-TeV accelerators. High electric field gradients are required for emerging applications; however, as gradients increase, components’ lifetime decreases, primarily due to radiofrequency (RF) breakdown. Coating technologies are being investigated in several laboratories to improve RF structure, performance and lifetime. To this end, we investigated the feasibility of fabricating nanometer-periodic Cu/Mo metallic multilayers on three-dimensional (3D) aluminum mandrels designed to replicate X-band copper resonating cavities. These nanometer-period multilayers are proposed to mitigate surface degradation due to electric breakdown at high accelerating gradients by stabilizing inner cavity surfaces against dislocation evolution and roughening caused by thermo-mechanical fatigue. High-Power Impulse Magnetron Sputtering (HiPIMS) in a bias-controlled dual closed-field magnetron configuration was employed to deposit alternating Mo and Cu nano-layers onto the 3D geometries. Given the complexity of HiPIMS technology, plasma pulse evolution was studied by combining time-resolved optical emission spectroscopy with electrical measurements of the pulse discharge. The influence of the process parameters, particularly the applied DC bias, on film growth was studied using non-destructive microprobe α-particle elastic backscattering spectrometry (µEBS) and scanning transmission electron microscopy (STEM). STEM and µEBS analyses confirmed that Mo layers with thicknesses of approximately 5–35 nm were successfully deposited repeatedly on thicker Cu layers (30–150 nm), preserving individual layer properties with minimal interdiffusion and alloying. The layers were deposited inside trenches with an aspect ratio of 5:1 representative of X-band irises. This technology, coupled with the replica process, could be applied to highly engineered nanostructured coatings for X-band cavity treatment in compact particle accelerator prototypes, as it may improve electrical breakdown lifetime under high accelerating fields, at least for degradation processes driven by the high mobility of copper dislocations. Full article

Air pollution is a growing hazard to global health. Epidemiological studies have reported a potential role of air pollutant exposure in the development or aggravation of neurodegenerative diseases. However, the underlying mechanisms are ill-defined. Ferroptosis is an iron- and reactive oxygen species (ROS)-dependent form of cell death that drives neuronal loss in neurodegenerative diseases. Our previous studies reported the involvement of adenosine 3′,5′-cyclic monophosphate (cAMP) and EPAC (exchange protein directly activated by cAMP) in ferroptotic cell death. Here, we investigated the effects of diesel exhaust particles (DEP) in mouse hippocampal (HT22) neuronal cells. Our data showed that toxicity induced by RSL3 (50–75 nM), a ferroptosis inducer, was significantly increased by the addition of DEP (100 μg/mL). Pharmacological inhibition of EPAC1 (CE3F4 30 μM or AM-001 30 μM) and soluble adenylyl cyclase (sAC; TDI-10229 1 μM or TDI-11861 0.1 μM) prevented enhanced ferroptotic HT22 cell death caused by DEP, while pharmacological modulation of EPAC2, protein kinase A (PKA), phosphodiesterases (PDEs), or transmembrane AC did not. DEP in combination with RSL3 exposure increased intracellular calcium levels and induced lysosomal de-acidification. Furthermore, inhibition of EPAC1 prevented mitochondrial ROS (MitoSOX) and lipid peroxidation (BODIPY C11 and MDA levels) after DEP and RSL3 co-exposure. Collectively, EPAC1 may serve as a novel target for the treatment or prevention of neurodegenerative diseases accelerated by air pollution. Full article

Self-collision detection has become the dominant computational bottleneck in GPU-accelerated cloth simulation, as modern parallel solvers such as XPBD have drastically reduced the cost of position updates while leaving collision resolution largely unoptimized. Existing spatial partitioning methods treat all cloth regions uniformly, saturating GPU memory bandwidth despite the fact that the vast majority of the mesh surface remains geometrically flat and collision-free at any given frame. We propose a hierarchical self-collision culling framework built upon a resolution-independent discrete curvature metric derived from the $h^2$-normalized Laplace-Beltrami operator, integrated with a discrete Kirchhoff–Love shell model combining distance and dihedral bending constraints within XPBD. Unlike prior cache-dependent acceleration strategies, our method tightly couples curvature-driven geometric pruning with a fused GPU kernel design and shows that this stateless formulation is both faster and physically more reliable. Evaluated on meshes of $512\times 512$ and $1024\times 1024$ particles, our method achieves a $5.5\%$ and $9.7\%$ FPS improvement alongside a $34.9\%$ and $28.4\%$ reduction in active collision pairs, respectively, with qualitative validation via high-fidelity rendering confirming artifact-free self-contact and strict ground-plane non-penetration. Ablation results further reveal that temporal coherence, conventionally regarded as an optimization standard, strictly degrades both performance (FPS decrease of $1.4\%p$ to $1.9\%p$) and physical accuracy (penetration depth increase of $36.1\%$ to $100.0\%$ relative to the curvature-only stage) on RTX 3070 GPU, advocating for stateless per-frame geometric evaluation as the preferred design paradigm. Full article

The operational reliability of gas-insulated switchgear/gas-insulated transmission lines (GIS/GIL) is critically threatened by internal metallic particles, which serve as primary triggers for insulation degradation. Conventional partial discharge (PD) detection methods often lack sensitivity during the early stages of particle movement. To overcome these limitations, this study aims to develop a novel non-intrusive defect diagnosis methodology based on the analysis of mechanical vibration signals. The coupled particle motion model integrating the electrostatic field, particle tracking, and multibody dynamics has been established. This model reveals the dynamic law that metallic particles migrate toward the conductor and undergo charge polarity reversal after collision, with a maximum speed of 2.7 m/s. Meanwhile, the peak vibration acceleration excited by the collision is calculated as 0.02 m/s². Accordingly, the high-voltage experimental platform with the full-scale prototype is built to simulate the actual operating conditions of the power grid. With the particle defects set inside the prototype, vibration signals are collected by using an accelerometer, and the measured peak vibration acceleration is 0.017 m/s². Finally, a defect diagnosis method based on the Hilbert–Huang Transform (HHT) and correlation coefficient analysis is proposed. This method uses Empirical Mode Decomposition (EMD) to extract the IMF4 component of the signal in the vicinity of the 1000 Hz frequency band. When particle defects occur, the correlation coefficient between the IMF4 component and the original signal exceeds 0.7668. This vibration-based monitoring technique provides an alternative for the condition-based maintenance of GIS/GIL, offering significant engineering value for enhancing the safety and reliability of power transmission infrastructure. Full article

As the power industry continues to advance rapidly, large-scale generators are evolving toward higher voltage levels and greater capacity. The heat accumulation associated with high voltage and large capacity accelerates the aging of the main insulation. It is necessary to enhance the thermal conductivity (λ) and dielectric properties of existing main insulation materials. This work focuses on investigating the effects of varying addition levels of two different-sized BN particles on the λ and dielectric properties of the mica tape composite dielectric. The experimental findings demonstrate a progressive enhancement in the λ of the mica tape corresponding to the incremental addition of h-BN concentration. When the doping concentration reaches 20 wt.%, the λ of the two h-BN-doped mica tape (h-BN/MT) reaches a maximum of 0.382 W/(m·K), 0.4 W/(m·K), respectively, which enhances the λ of the contrasting pure mica tape (0.199 W/(m·K)) by 91.95% and 101.01%, respectively. In terms of electrical insulation properties, both sizes of h-BN/MT perform well, with breakdown strength above 32 kV/mm. Furthermore, the second-order thermal conductivity model of mica tape doped with different sizes of h-BN was constructed by combining the Halpin–Tsai model with the Series model, which allows the calculation of λ of mica tape composites doped with different sizes of h-BN. This work provides a novel structural design approach for preparing mica tape composite dielectric that simultaneously exhibits high λ and high insulation properties. Full article

To qualify epoxy resin systems for use in superconducting magnets of future particle accelerators up to peak doses beyond 100 MGy, the effects of the irradiation source, the irradiation environment and the irradiation temperature have been assessed. Identical epoxy resin samples have been irradiated with ⁶⁰Co gamma rays, 24 GeV/c protons and by mixed neutron/gamma radiation in a reactor and at a spallation source up to a dose of 170 MGy. Irradiation-induced cross-linking and chain scission have been monitored by Dynamical Mechanical Analysis (DMA). When irradiations are performed with the same dose rate and in the same environment, the different radiation sources have a similar efficiency to produce radiation damage, and the total absorbed dose is a good scaling factor to compare irradiation effects in polymers. To distinguish between the influence of the irradiation temperature and of environmental oxygen, proton irradiations have been carried out in ambient air, inert gas at ambient temperature and in liquid helium. Compared to ambient air irradiation, in inert atmosphere more cross-linking is observed. Cross-linking rates are strongly reduced at 4.2 K. For some polymers the irradiation temperature has a strong influence on the chain scission rate. The most-radiation-hard epoxy resin systems maintain substantial mechanical strength up to doses beyond 100 MGy. Full article

Servo valves are critical components in hydraulic control systems; their performance directly affects the accuracy and reliability of systems used in aerospace and construction machinery. In service, micron-scale solid contaminants in hydraulic oil tend to deposit within the narrow clearances between spool and sleeve, causing spool sticking and accelerated wear that degrade system stability and lifetime. This study combines fluid–particle coupling analysis, numerical simulation, and experiments to examine particle motion and migration in representative valve-like flow fields. A force model for particles in viscous hydraulic oil is derived from fluid- and particle-dynamics principles, and two-dimensional CFD–DPM models are constructed for laminar, jet-like, and swirling flow conditions. Parametric simulations explore the influence of flow velocity, particle size, and particle density on particle trajectories and displacement. Results indicate that particle size has the strongest effect on migration behavior, with particle displacement increasing from 0.35% to 30.65% in laminar flow, from 2.31% to 67.08% in jet-like flow, and from 1.93% to 145.09% in swirling flow. Fluid velocity also significantly affects particle displacement, while particle density has a relatively minor influence. Swirling flow produces the largest displacement, followed by jet-like and laminar flow. Finally, a Particle Image Velocimetry (PIV)–style experimental platform on scaled models is used to validate key simulation trends. Findings clarify dominant mechanisms of particle contamination in servo valves and offer guidance for gap optimization and anti-contamination design. Full article

Surrogate-assisted evolutionary algorithms have become the mainstream approach for solving expensive constrained multi-objective optimization problems (ECMOPs). However, existing methods suffer from blind search issues, and their selection strategies fail to adapt to changes in evolutionary stages. To overcome these limitations, this paper proposes a Multi-directional Guided Dual-mode Kriging-assisted Competitive Particle Swarm Optimization (MGD-KCSO) algorithm. MGD-KCSO integrates three synergistic strategies: a multi-directional guided solution strategy that constructs four complementary search paths based on non-dominated solutions to effectively enhance convergence and diversity; a dual-population data selection strategy that separates unconstrained and constrained populations to perform objective-oriented and constraint-oriented optimization, respectively; and an adaptive infill sampling strategy that dynamically switches sampling modes by monitoring the change rate of the objective function of the ideal point. If this rate exceeds a predefined threshold, the algorithm executes unconstrained sampling to accelerate convergence; otherwise, it switches to constrained sampling to prioritize the exploration of feasible boundaries. To verify the effectiveness of MGD-KCSO, comprehensive experiments were conducted on 33 benchmark problems and two real-world engineering design problems (pressure vessel and disc brake design). MGD-KCSO was compared against eight classic algorithms and three state-of-the-art methods published in the past two years. Experimental results evaluated by inverted generational distance (IGD) and hypervolume (HV) metrics demonstrate that MGD-KCSO outperforms the comparative algorithms on most test instances, achieving superior performance in terms of convergence, diversity, and practical applicability. Full article

Background/Objectives: RNA interference (RNAi) is a promising strategy for mitigating diseases at the molecular level. However, RNAi is limited by its instability in biological fluids and impermeability to cellular membranes. In response, our lab has previously patented a non-ionizable lipid nanoparticle (LNP) platform (R8-PLP) for RNAi therapeutic delivery. This formulation incorporates 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[methoxy(polyethylene glycol)-2000] (DSPE-PEG) to improve particle stability and drug retention. However, long-anchored PEGylated lipids like DSPE-PEG may impair internalization and stimulate immune responses. The literature suggests substituting short-anchored PEGylated-lipids like 1,2-dimyristoyl-rac-glycero-3-[methoxy(polyethylene glycol)-2000] (DMG-PEG) to attenuate these effects. Here, we evaluated whether substituting DMG-PEG for DSPE-PEG in our R8-PLP would improve in vitro cellular delivery and gene transfection without compromising in vitro critical quality attributes (CQAs) or increasing cytotoxicity. Methods: CQAs [encapsulation efficiency (EE%), particle size (nm), homogeneity (polydispersity index; PDI), and membrane zeta-potential] were assessed at assembly and after storage for up to 28 days at 4 °C. Additionally, in-serum stability at 4 °C and serum release kinetics at 37 °C were assessed. Human aortic smooth muscle cells (HASMCs) were treated with R8-PLPs and analyzed for cellular uptake (fluorometry), cytotoxicity (LIVE/DEAD stain), and gene modulation (qPCR). Results: DMG-PEG incorporation at variable mol% did not alter R8-PLP size, homogeneity, or siRNA EE% at assembly or after long-term storage, but did accelerate siRNA release kinetic profiles compared to DSPE-PEG controls. DMG-PEG substitution enhanced cellular uptake compared to DSPE-PEG R8-PLPs without increasing cytotoxicity. DMG-PEG incorporation also achieved significant silencing versus non-treated controls but did not improve gene silencing compared to DSPE-PEG R8-PLPs. Conclusions: Thus, DMG-PEG substitution did not enhance R8-PLP in vitro gene modulation efficacy despite improving cellular uptake and maintaining CQAs. Full article

The development of filled photopolymer composites for Digital Light Processing (DLP) additive manufacturing requires optimizing processing parameters to achieve the desired mechanical properties. Traditional experimental approaches are time-intensive, while physics-based models often struggle to capture the complex interactions among parameters. This study presents a physics-informed machine learning framework that combines Random Forest with Bayesian optimization (RF-BO) to predict the ultimate tensile strength in recycled thermoset resin composites manufactured via DLP. A validation dataset of 19 systematically varied formulations (each with n = 5 measurement replicates for reliability) was generated and augmented with 1500 physics-informed synthetic samples to enable robust model training. The limited experimental dataset, while insufficient for traditional statistical inference, provided critical validation of physical trends, including non-monotonic particle-size effects and optimal processing windows. Six machine learning algorithms were evaluated, with RF-BO achieving superior performance (R² = 0.9125, MSE = 1.07 MPa). The framework identified optimal processing conditions of 59–64 μm particle size, 5.0 ± 0.5 wt.% concentration, and 60 min cure time, predicting a maximum UTS of 43.84 MPa with a prediction error of less than 1.0 MPa. Feature importance analysis revealed that cure time was the dominant parameter (40%), followed by particle size (30%), validating the physical interpretability. This approach demonstrates significant potential for accelerating materials design in composite additive manufacturing while maintaining physically meaningful predictions. Full article

The study explores the potential of thermoplastic biocomposites made from cellulose acetate, modified hemp seed hull particulate fillers and environmentally friendly plasticizer triacetin. Emphasizing the environmental advantages of utilizing natural materials, the research demonstrates the impact of different hemp hull chemical modification, such as alkali treatment or acetylation, on the mechanical properties of the resultant composites. Hemp seed hulls treated with 4–16% NaOH solution were studied using SEM imaging, FT-IR, XRD and chemical composition analyses. The study showed that alkaline treatment of hemp seed hull particles improved the mechanical properties of biocomposites, and the optimum concentration of NaOH solution ranged from 8 to 12%. The tensile modulus increased by 17–24%, and the tensile strength improved by 21–23% in biocomposites containing HH8 and HH12 fillers, while hardness increased by approximately 11–13%. It was also demonstrated that alkaline treatment of hemp seed hull fillers accelerated the biodegradation of biocomposite extrudates under aerobic conditions in a standard aqueous medium. Overall, the results demonstrated the potential of alkaline-treated hemp seed hulls as fillers in composite bioplastics. Full article

In deep geothermal engineering, concrete slabs are prone to thermal cracking. The aggregates and pores are the core influencing factors for this failure behavior. However, existing research methods are unable to accurately capture the microscopic evolution process of thermal cracking and cannot clarify the intrinsic mechanism of how the characteristics of aggregates and pores affect the initiation and propagation of cracks. This limitation restricts the in-depth understanding of the laws of concrete thermal cracking. To address this deficiency, this study employs the discrete element method (DEM) and combines the particle flow program PFC2D to construct a microscopic model of concrete disks. By setting reasonable temperature parameters and thermal load boundaries, a numerical simulation system matching the actual deep geothermal high-temperature environment is established. Three sets of quantitative variables were designed: aggregate particle size (0.003, 0.004, 0.005, 0.006), aggregate volume fraction (0.35, 0.40, 0.45, 0.50), and porosity (0.11, 0.12, 0.13, 0.14). Through controlled variable simulations, the influence laws of each variable on the formation, propagation path, and time evolution of concrete thermal cracks were explored. The quantitative research results show that an increase in aggregate particle size significantly accelerates the generation and propagation of cracks. When the particle size is 0.006, the number of cracks is the highest and the propagation rate is the fastest. The aggregate volume fraction is negatively correlated with the final number of cracks, and 0.50 is the optimal fraction, at which the number of cracks is the smallest. A decrease in the fraction will lead to intensified stress concentration in the cement paste and a sudden increase in the number of cracks. An increase in porosity significantly disrupts the material continuity. When the porosity is 0.14, the bifurcation and connection of cracks are the most significant, while a low porosity of 0.11 can effectively inhibit the overall development process of thermal cracks. In addition, compared with traditional experimental methods and continuous medium numerical simulation techniques, the discrete element method has unique advantages in revealing the internal mechanism of concrete thermal cracking at the microscopic level. It can achieve real-time tracking of the evolution of discrete micro-cracks and the internal stress distribution characteristics. This study enriches the microscopic theoretical system of concrete thermal cracking and provides reliable quantitative references and technical support for the design of thermal crack resistance of concrete in deep geothermal engineering and the optimization of material composition. Full article

Conventional fixed phase-shift strategies for parallel PV converters fail to minimize output ripple under heterogeneous input conditions, while communication-based synchronous methods incur high costs and reliability risks. Furthermore, standard global optimization algorithms like conventional Particle Swarm Optimization (PSO) suffer from slow convergence, hindering real-time application. To address these limitations, this paper proposes a communication-free distributed ripple suppression method based on an enhanced PSO with randomized phase shifting. Unlike traditional approaches, our method enables autonomous convergence without inter-unit communication. Crucially, a randomized pre-scanning mechanism narrows the search space, accelerating convergence significantly. Simulation results demonstrate that the proposed method reaches a steady state in merely 5 ms, which is 50% faster than conventional PSO (~10 ms) and eliminates communication latency. Under severe heterogeneous conditions, the technique reduces output voltage ripple to 0.66 V (a 53% reduction) compared to the unoptimized 1.21 V, vastly outperforming fixed interleaving strategies that show negligible improvement. The approach also ensures robust stability during load steps and plug-and-play operations, offering a superior low-cost and high-speed solution for distributed PV systems. Full article

The global construction sector, a major consumer of virgin raw materials, is under increasing pressure to transition from a linear to a circular economy model. Marble waste, generated in large quantities during quarrying, cutting, and polishing operations, represents a promising secondary resource for sustainable construction applications. This systematic review was conducted in accordance with the PRISMA 2020 reporting guidelines to critically evaluate the utilization of marble waste in concrete and other building materials. A comprehensive literature search was performed using major scientific databases, and relevant studies published between 2000 and 2025 were analyzed. The findings consistently indicate that marble waste performs most effectively as a fine aggregate replacement at 10–20%, resulting in improved compressive strength, pore refinement, and durability. As a cement substitute, the optimum replacement level is generally 5–10%, beyond which dilution effects may adversely affect strength development. The performance is primarily attributed to improved particle packing and microstructural refinement. This review further highlights future pathways for industrial-scale implementation, mix optimization, standardisation, and policy integration to accelerate circular construction practices. These findings support the potential of marble waste as a sustainable material in advancing circular economy principles in the construction industry. Full article

Pt–transition metal intermetallic compounds have been recognized as promising catalysts for oxygen reduction reaction (ORR). However, further enhancing the activity and durability of this kind of catalyst is still necessary. Herein, we report a novel L1₀-type PtFe intermetallic nanoalloy with the partial substitution of Fe sites by La as a highly active and stable catalyst towards ORR. This new intermetallic nanoalloy retains an ordered structure after the incorporation of La confirmed by XRD, XPS and TEM results and the ordered PtFe_0.5La_0.5 nanoparticles are embedded in porous carbon (L1₀-PtFe_0.5La_0.5@C) in very uniform particle size of around 2 nm. This L1₀-PtFe_0.5La_0.5@C catalyst exhibits a half-wave potential of 933 mV, which is about 12 mV and 70 mV higher than those of L1₀-PtFe@C and commercial Pt/C catalysts, respectively. Moreover, it also achieves an enhanced mass activity of 0.79 A mg_Pt⁻¹ at 0.90 V, which outperforms the performance of commercial Pt/C (0.10 A mg_Pt⁻¹). In addition, it also shows excellent stability with only 3 mV negative shift in half-wave potential after 20k CV cycles of accelerated durability testing. This high activity and stability may be attributed to the incorporation of La in the PtFe lattice, which induces the formation of a compressively strained Pt overlayer in acidic media which not only tunes the surface strain of Pt sites but also possesses robust resistance to the dissolution of Fe and La. This work also provides a new direction for the development of Pt-based intermetallic catalysts for efficient catalysis applications. Full article