Search Results (24)

This research presents the development and management principles of mobile resonant electrical systems designed for high-voltage generation, intended for non-destructive diagnostics of insulation in high-power electrical equipment. The core of the system is a series inductive–capacitive (LC) circuit characterized by a high quality (Q) factor and operating at high frequencies, typically in the range of 40–50 kHz or higher. Practical implementations of the LC circuit with Q-factors exceeding 200 have been achieved using advanced materials and configurations. Specifically, ceramic capacitors with a capacitance of approximately 3.5 nF and Q-factors over 1000, in conjunction with custom-made coils possessing Q-factors above 280, have been employed. These coils are constructed using multi-core, insulated, and twisted copper wires of the Litzendraht type to minimize losses at high frequencies. Voltage amplification within the system is effectively controlled by adjusting the current frequency, thereby maximizing voltage across the load without increasing the system’s size or complexity. This frequency-tuning mechanism enables significant reductions in the weight and dimensional characteristics of the electrical system, facilitating the development of compact, mobile installations. These systems are particularly suitable for on-site testing and diagnostics of high-voltage insulation in power cables, large rotating machines such as turbogenerators, and other critical infrastructure components. Beyond insulation diagnostics, the proposed system architecture offers potential for broader applications, including the charging of capacitive energy storage units used in high-voltage pulse systems. Such applications extend to the synthesis of micro- and nanopowders with tailored properties and the electrohydropulse processing of materials and fluids. Overall, this research demonstrates a versatile, efficient, and portable solution for advanced electrical diagnostics and energy applications in the high-voltage domain. Full article

Optimizing stress distribution at the bone–implant interface is critical to enhancing the long-term biomechanical performance of dental implant systems. Vertical misalignment between splinted implants can result in elevated localized stresses, increasing the risk of material degradation and peri-implant bone resorption. This study employs three-dimensional finite element analysis (FEA) to evaluate the mechanical response of peri-implant bone under oblique loading, focusing on how variations in vertical implant platform alignment influence stress transmission. Four implant configurations with different vertical placements were modeled: (A) all crestal, (B) central subcrestal with lateral crestal, (C) lateral subcrestal with central crestal, and (D) all subcrestal. A 400 N oblique load was applied at 45° simulated masticatory forces. Von Mises stress distributions were analyzed in both cortical and trabecular bone, with a physiological threshold of 100 MPa considered for cortical bone. Among the models, configuration B exhibited the highest cortical stress, exceeding the physiological threshold. In contrast, configurations with uniform vertical positioning, particularly model D, demonstrated more favorable stress dispersion and lower peak values. Stress concentrations were consistently observed at the implant–abutment interface across all configurations, identifying this area as critical for design improvements. These findings underscore the importance of precise vertical alignment in implant-supported restorations to minimize stress concentrations and improve the mechanical reliability of dental implants. The results provide valuable insights for the development of next-generation implant systems with enhanced biomechanical integration and material performance under functional loading. Full article

This study proposes a data-driven optimization framework to enhance emission control performance in diesel engine selective catalytic reduction (SCR) systems under transient operating conditions. A one-dimensional SCR model was constructed in GT-Power, and simulation datasets were generated using experimentally measured inputs from the World Harmonized Transient Cycle (WHTC), with representative emission responses obtained by varying fixed ammonia-to-NOx (A/N) ratios. Building on these datasets, a hybrid prediction model combining Long Short-Term Memory (LSTM) networks and multi-head attention mechanisms was developed to accurately forecast SCR outlet NH₃ leakage and NOx emissions. The model exhibited high predictive accuracy, achieving R² values exceeding 0.977 and low RMSE across training, validation, and test sets. Based on the model predictions, a constrained dynamic multi-objective optimization strategy was implemented to adaptively adjust ammonia dosing, aiming to simultaneously minimize NH₃ leakage and NOx emissions. The optimized NH₃ injection profiles were validated through reapplication in the GT-Power simulation environment. Compared to the baseline fixed-ratio control strategy, the proposed approach reduced NH₃ leakage and NOx emissions by 34.40% and 11.15%, respectively, as determined for the transient segment of the WHTC cycle. These results demonstrate the effectiveness of integrating physics-based simulation, deep learning prediction, and dynamic optimization for improving aftertreatment adaptability and emission compliance in real-world diesel engine applications. All reported values are based on a single simulated WHTC cycle without statistical uncertainty analysis. Full article

To tackle the degradation of sealing performance in nitrile butadiene rubber (NBR) seals due to material aging during long-term service, this study integrates experimental and molecular simulation methods to elucidate the aging mechanism. Experimental results reveal that the contents of C=C and C=O functional groups significantly decrease during aging, accompanied by enhanced hydrophobicity and increased crosslink density of NBR, indicating that crosslinking reactions dominate the aging process with the participation of C=C and C=O groups. Quantum mechanics (QM) and molecular dynamics (MD) simulations further demonstrate that α-H, C=C, and C≡N groups are preferentially oxidized due to their low bond energies. The oxidation of NBR generates unstable epoxy intermediates, which undergo chain scission to form ketones, aldehydes, and ultimately crosslinked structures. Using a multi-dimensional evaluation system based on bond dissociation energy (BDE), solubility parameter (Δδ), and migration coefficient (MSD), four antioxidants (4010NA, 4010, MC, and BHT) were screened. BHT emerges as the optimal choice, exhibiting superior free radical scavenging ability (BDE = 346.3 kJ/mol), good matrix compatibility (Δδ = 2.95), and anti-migration properties. The MD-based screening method established herein provides a theoretical basis for designing antioxidant systems in high-performance rubber materials, facilitating the development of advanced rubber products. Full article

Nanogenerators have garnered significant scholarly interest as a groundbreaking approach to energy harvesting, encompassing applications in self-sustaining electronics, biomedical devices, and environmental monitoring. The rise of additive manufacturing has fundamentally transformed the production processes of nanocomposites, allowing for the detailed design and refinement of materials aimed at optimizing energy generation. This review presents a comprehensive analysis of 3D-printed nanocomposites in the context of nanogenerator applications. By employing layer-by-layer deposition, multi-material integration, and custom microstructural architectures, 3D-printed nanocomposites exhibit improved mechanical properties, superior energy conversion efficiency, and increased structural complexity when compared to their conventionally manufactured counterparts. Polymers, particularly those with inherent dielectric, piezoelectric, or triboelectric characteristics, serve as critical functional matrices in these composites, offering mechanical flexibility, processability, and compatibility with diverse nanoparticles. In particular, the careful regulation of the nanoparticle distribution in 3D printing significantly enhances piezoelectric and triboelectric functionalities, resulting in a higher energy output and greater consistency. Recent investigations into three-dimensional-printed nanogenerators reveal extraordinary outputs, encompassing peak voltages of as much as 120 V for BaTiO₃-PVDF composites, energy densities surpassing 3.5 mJ/cm², and effective d₃₃ values attaining 35 pC/N, thereby emphasizing the transformative influence of additive manufacturing on the performance of energy harvesting. Furthermore, the scalability and cost-effectiveness inherent in additive manufacturing provide substantial benefits by reducing material waste and streamlining multi-phase processing. Nonetheless, despite these advantages, challenges such as environmental resilience, long-term durability, and the fine-tuning of printing parameters remain critical hurdles for widespread adoption. This assessment highlights the transformative potential of 3D printing in advancing nanogenerator technology and offers valuable insights into future research directions for developing high-efficiency, sustainable, and scalable energy-harvesting systems. Full article

Asymmetric deformation has been observed along the Altyn Tagh Fault (ATF), the northern boundary of the Tibetan Plateau. Several mechanisms have been proposed to explain this asymmetry, including contrasts in crustal strength, lower crust/upper mantle rheology, deep fault dislocation shifts, and dipping fault geometry; however, the real scenario remains debated. This study utilizes a time series Interferometric Synthetic Aperture Radar (InSAR) technique to investigate spatially variable asymmetries across the western section of the ATF (83–89°E). We generated a high-resolution three-dimensional (3D) crustal velocity field from Sentinel-1 data for the northwestern Tibetan Plateau (~82–92°E; 33–40°N). Our results confirm that pronounced greater deformations within the Tibetan Plateau occur only along the westernmost section of the ATF (83–85.5°E). We propose this asymmetry is primarily driven by a splay fault system within a transition zone, bounded by the ATF in the north and the Margai Caka Fault (MCF)–Kunlun Fault (KLF) in the south, which accommodates an east–west extension in the central Tibetan Plateau while transferring sinistral shear to the KLF. The concentrated strain observed along the ATF and MCF–KLF lends more support to a block-style eastward extrusion model, rather than a continuously deforming model, for Tibetan crustal kinematics. Full article

With the rapid increase in cyber-attacks, intrusion detection systems (IDS) have become essential for network security. However, traditional IDS methods often struggle with class imbalance, leading to asymmetric data distributions that adversely affect detection performance and model generalization. To address this issue and enhance detection accuracy, this paper proposes SE-DWNet, a residual network model incorporating an attention mechanism and one-dimensional depthwise separable convolution, trained on a symmetrically preprocessed dataset using SMOTETomek sampling. First, the feature distributions of the training and test datasets are analyzed using box plots, highlighting the impact of feature difference. To mitigate this difference and restore a more symmetric data distribution, we employ the SMOTETomek integrated sampling method in conjunction with a Focal Loss function. Subsequently, a lightweight residual network, incorporating the SE module and the Res-DWNet module, is designed to improve detection accuracy while maintaining computational efficiency. Extensive experiments on the NSL-KDD, CICIDS2018, and ToN-IoT datasets demonstrate that SE-DWNet outperforms existing neural network-based IDS models, achieving accuracy, precision, recall, and F1-score improvements ranging from 0.17% to 5.33%. The results confirm the effectiveness and superiority of the proposed approach in intrusion detection tasks. Full article

In the present contribution, a preliminary analysis of the effects of the Generalized Uncertainty Principle (GUP) with a minimum length, in the context of compact stars, is performed. On basis of a deformed Poisson canonical algebra with a parametrized minimum length scale that induces deviations from conventional Quantum Mechanics, fundamental questions involving the consistence, evidences and proofs of this approach as a possible cure for unbounded energy divergence are outlined. The incorporation of GUP effects into semiclassical 2N-dimensional systems is made by means of a time-invariant distortion transformation applied to their non-deformed counterparts. Assuming the quantum hadrodynamics $\sigma -\omega$ approach as a toy-model, due to its simplicity and structured description of neutron stars, we perform a preliminary analysis of GUP effects with a minimum spacetime length on these compact objects. The corresponding results for the equation of state and the mass-radius relation for neutron stars are in tune with recent observations with a maximum mass around 2.5 M_⊙ and radius close to 12 km. Our results also indicate the smallness of the noncommutative scale. Full article

For metal-free low-dimensional ferromagnetic materials, a hopeful candidate for next-generation spintronic devices, investigating their magnetic mechanisms and exploring effective ways to regulate their magnetic properties are crucial for advancing their applications. Our work systematically investigated the origin of magnetism of a graphitic carbon nitride (Pca21 C₄N₃) monolayer based on the analysis on the partial electronic density of states. The magnetic moment of the Pca21 C₄N₃ originates from the spin-split of the 2p_z orbit from special carbon (C) atoms and 2p orbit from N atoms around the Fermi energy, which was caused by the lone pair electrons in nitrogen (N) atoms. Notably, the magnetic moment of the Pca21 C₄N₃ monolayer could be effectively adjusted by adsorbing nitric oxide (NO) or oxygen (O₂) gas molecules. The single magnetic electron from the adsorbed NO pairs with the unpaired electron in the N atom from the substrate, forming a N_sub-N_ad bond, which reduces the system’s magnetic moment from 4.00 μ_B to 2.99 μ_B. Moreover, the NO adsorption decreases the both spin-down and spin-up bandgaps, causing an increase in photoelectrical response efficiency. As for the case of O₂ physisorption, it greatly enhances the magnetic moment of the Pca21 C₄N₃ monolayer from 4.00 μ_B to 6.00 μ_B through ferromagnetic coupling. This method of gas adsorption for tuning magnetic moments is reversible, simple, and cost-effective. Our findings reveal the magnetic mechanism of Pca21 C₄N₃ and its tunable magnetic performance realized by chemisorbing or physisorbing magnetic gas molecules, providing crucial theoretical foundations for the development and utilization of low-dimensional magnetic materials. Full article

We present an analysis of α-helix folding in the coarse-grained coordinate of number of formed helical hydrogen bonds (NHBs) for four alanine peptides (ALA)n, with n = 5, 8, 15, and 21 residues. Starting with multi-microsecond all-atom molecular dynamics trajectories in aqueous solution, we represent the system dynamics in a space of between four (for ALA5) and twenty (for ALA21) hydrogen-bonding microstates. In all cases, transitions changing the hydrogen bond count by 1–2 dominate and the coil formation, NHB 1 → 0, is the fastest process. The calculation of global maximum weight paths shows that, when analyzed at a sufficiently long lag time, folding in the NHB coordinate is consecutive, with direct folding, 0 → 3, for ALA5 and bottlenecks at transitions 4 → 6 for ALA8, 0 → 5 for ALA15, and 0 → 9 for ALA21. Further coarse-graining to 2–4 dimensions was performed with the optimal dimensionality reduction method, allowing the identification of crucial folding intermediates and time scales of their formation in ALA8, ALA15, and ALA21. The detailed analysis of hydrogen bonding patterns revealed that folding is initiated preferentially at both peptide termini. The kinetic model was also used to estimate diffusion and friction coefficients for helix propagation. The description of the helix formation process in the hydrogen bonding coordinate NHB was in good general agreement with the experimental data and qualitatively similar to previous kinetic models of higher dimensions based on structural clustering. Use of the low-dimensional hydrogen bonding picture thus provides a different, complementary way of describing the complex and fascinating mechanism of helix formation. Full article

A (3+1)-dimensional generalized Yu–Toda–Sasa–Fukuyama equation is considered systematically. N-soliton solutions are obtained using Hirota’s bilinear method. The employment of the complex conjugate condition of parameters of N-soliton solutions leads to the construction of breather solutions. Then, the lump solution is obtained with the aid of the long-wave limit method. Based on the transformation mechanism of nonlinear waves, a series of nonlinear localized waves can be transformed from breathers, which include the quasi-kink soliton, M-shaped kink soliton, oscillation M-shaped kink soliton, multi-peak kink soliton, and quasi-periodic wave by analyzing the characteristic lines. Furthermore, the molecular state of the transformed two-breather is studied using velocity resonance, which is divided into three aspects, namely the modes of non-, semi-, and full transformation. The analytical method discussed in this paper can be further applied to the investigation of other complex high-dimensional nonlinear integrable systems. Full article

MXene is a type of two-dimensional (2D) transition metal carbide and nitride, and its promising energy storage materials highlight its characteristics of high density, high metal-like conductivity, tunable terminals, and charge storage mechanisms known as pseudo-alternative capacitance. MXenes are a class of 2D materials synthesized by chemical etching of the A element in MAX phases. Since they were first discovered more than 10 years ago, the number of distinct MXenes has grown substantially to include numerous M_nX_n−1 (n = 1, 2, 3, 4, or 5), solid solutions (ordered and disordered), and vacancy solids. To date, MXenes used in energy storage system applications have been broadly synthesized, and this paper summarizes the current developments, successes, and challenges of using MXenes in supercapacitors. This paper also reports the synthesis approaches, various compositional issues, material and electrode topology, chemistry, and hybridization of MXene with other active materials. The present study also summarizes MXene’s electrochemical properties, applicability in pliant-structured electrodes, and energy storage capabilities when using aqueous/non-aqueous electrolytes. Finally, we conclude by discussing how to reshape the face of the latest MXene and what to consider when designing the next generation of MXene-based capacitors and supercapacitors. Full article

For the free vibrations of multi-degree mechanical structures appeared in structural dynamics, we solve the quadratic eigenvalue problem either by linearizing it to a generalized eigenvalue problem or directly treating it by developing the iterative detection methods for the real and complex eigenvalues. To solve the generalized eigenvalue problem, we impose a nonzero exciting vector into the eigen-equation, and solve a nonhomogeneous linear system to obtain a response curve, which consists of the magnitudes of the n-vectors with respect to the eigen-parameters in a range. The n-dimensional eigenvector is supposed to be a superposition of a constant exciting vector and an m-vector, which can be obtained in terms of eigen-parameter by solving the projected eigen-equation. In doing so, we can save computational cost because the response curve is generated from the data acquired in a lower dimensional subspace. We develop a fast iterative detection method by maximizing the magnitude to locate the eigenvalue, which appears as a peak in the response curve. Through zoom-in sequentially, very accurate eigenvalue can be obtained. We reduce the number of eigen-equation to $n-1$ to find the eigen-mode with its certain component being normalized to the unit. The real and complex eigenvalues and eigen-modes can be determined simultaneously, quickly and accurately by the proposed methods. Full article

Hydrogels consist of three-dimensionally crosslinked polymeric chains, are hydrophilic, have the ability to absorb other molecules in their structure and are relatively easy to obtain. However, in order to improve some of their properties, usually mechanical, or to provide them with some physical, chemical or biological characteristics, hydrogels have been synthesized combined with other synthetic or natural polymers, filled with inorganic nanoparticles, metals, and even polymeric nanoparticles, giving rise to composite hydrogels. In general, different types of hydrogels have been synthesized; however, in this review, we refer to those obtained from the thermosensitive polymer poly(N-vinylcaprolactam) (PNVCL) and we focus on the definition, properties, synthesis techniques, nanomaterials used as fillers in composites and mainly applications of PNVCL-based hydrogels in the biomedical area. This type of material has great potential in biomedical applications such as drug delivery systems, tissue engineering, as antimicrobials and in diagnostic and bioimaging. Full article

In this paper, we introduce the notions of the almost anti-periodic discrete process of the N-dimensional vector-valued and $N\times N$ matrix-valued functions. Some basic properties of the almost anti-periodic discrete functions are established. Based on this, the conditions of the stability and instability of the almost anti-periodic solutions to the general N-dimensional mechanical system and the underactuated Euler–Lagrange system have been considered. Moreover, some examples are provided to support our obtained results. Full article