Search Results (4,010)

Single-crystal diamond (SCD) is an ideal substrate material for semiconductor devices due to its extremely wide bandgap and exceptionally high thermal conductivity. However, diamond’s extreme hardness and chemical inertness pose challenges for the fabrication of ultra-smooth surfaces. Traditional polishing processes are not only inefficient but also prone to introducing subsurface defects, which severely degrade device performance. To address the above issues, this study proposes a hybrid polishing process combining reactive ion etching (RIE) surface modification with chemical mechanical polishing (CMP), which enables low-loss atomic-level processing of SCD. The study found that RIE treatment induces lattice disorder on the diamond surface, forming a sp²-hybridized amorphous carbon-modified layer. Compared to the sp³ structure of native diamond, this modified layer has lower hardness and is easier to remove. We conducted the verification of the optimized process using high-quality single-crystalline diamond (SCD) samples with an initial surface roughness Ra of 0.68 nm. Under the optimized RIE parameters (substrate bias power: 200 W, etching time: 600 s, gas flow ratio of Ar:O₂:CF₄ = 40:50:10), the surface roughness Ra was reduced to as low as 0.35 nm after 2 h of CMP treatment. Furthermore, systematic characterization of the SCD’s as-received surface, RIE-modified surface, and CMP-treated surface was performed using Raman spectroscopy and X-ray photoelectron spectroscopy (XPS), elucidating the “etching modification–mechanical removal” polishing mechanism. Full article

A global, uniform two-variable analytic approximation for the modified Bessel function $I_{\nu }\left(x\right)$ is presented, valid for all real x and for orders $-1/2\le \nu \le 1/4$. The approximation is constructed using a two-variable multipoint quasi-rational approximation (MPQA) approach, in which the argument x and the order $\nu$ are treated simultaneously as independent variables. The method consistently incorporates the power-series expansion at small arguments and the asymptotic behavior at large arguments, leading to an explicit analytic representation that preserves the correct limiting behaviors. The resulting approximation remains suitable for analytical differentiation and integration, while all parameters are obtained from linear equations, avoiding numerical fitting procedures. A numerical analysis over the entire domain considered shows excellent agreement with the exact function. The largest relative error observed is ${\epsilon }_r=0.0213$, occurring at $\nu =-0.34$ and $x=2.56$. These results indicate that the proposed approximation provides an accurate and efficient analytic representation of $I_{\nu }\left(x\right)$ throughout the investigated domain. Full article

Electrostatic MEMS micromirrors provide a compact and low-power beam-steering solution for miniaturized laser communication terminals. However, when they are used for quasi-static beam pointing rather than resonant scanning, the nonlinear voltage–angle relationship, bidirectional actuation asymmetry, and terminal-level installation errors can significantly degrade pointing accuracy. In this paper, a nonlinear modeling and differential-voltage control method is investigated for a two-axis electrostatic MEMS micromirror used in a miniaturized laser communication terminal. The device under test is a bonded aluminum MEMS micromirror with a 5.0 mm aperture. Static and dynamic characterization results show that the micromirror achieves maximum mechanical deflection angles of 5.215° and 5.161° along the X and Y axes, respectively, with resonant frequencies of 317 Hz and 319 Hz. To improve the accuracy of quasi-static pointing, the differential-voltage actuation principle is analyzed, and a nonlinear voltage–angle model is established based on measured deflection data. Compared with a first-order linear model, the cubic nonlinear model reduces the root-mean-square fitting error from 0.142° to 0.0127° for the X axis and from 0.132° to 0.0109° for the Y axis. Furthermore, a terminal-level calibration architecture based on a quadrant detector is introduced to map the MEMS angular deflection to the received spot position. The proposed modeling and calibration approach provides an actuator-level basis for accurate beam pointing and closed-loop acquisition in miniaturized laser communication terminals. Full article

Resource allocation for cognitive Vehicle-to-Everything (V2X) networks is challenging due to dynamic spectrum sharing, strong interference coupling, and stringent latency constraints for safety-critical Vehicle-to-Vehicle (V2V) traffic. Although recent Multi-Agent Reinforcement Learning (MARL) approaches report promising gains, many evaluations are conducted at limited and fixed network scales, which restricts insights into scalability under dense spectrum reuse. This paper investigates cooperative multi-agent learning for interference-aware and deadline-constrained V2X resource management. We propose a Q-value Transformation (QTRAN)-based value decomposition framework under centralized training with decentralized execution (CTDE) for joint resource-block and power allocation among V2V agents. The proposed approach is implemented in a realistic V2V/V2I simulator incorporating Manhattan grid mobility, fast fading, explicit cross-tier and co-channel interference, and per-link payload/deadline dynamics. Beyond communication-level performance, improved timely delivery of V2V safety messages can support cooperative maneuvering, collision avoidance, platooning, and infrastructure-assisted traffic management. Extensive simulations across varying numbers of V2V agents benchmark QTRAN against independent learning baselines including MARL and centralized single-agent learning (SARL). Results show that QTRAN improves performance compared with the selected learning baselines and enhances the throughput–reliability trade-off under interference-coupled spectrum reuse. For instance, at $N_{\mathrm{V}2\mathrm{V}}=20$, QTRAN achieves a V2V rate of $0.194\pm 0.004$ and a V2I rate of $9.117\pm 0.213$, while reaching a V2V success rate of $0.812\pm 0.017$ with a low Deadline Miss Ratio of $0.001\pm 0.000$. At higher density ($N_{\mathrm{V}2\mathrm{V}}=50$), QTRAN sustains strong reliability (V2V success rate of $0.719\pm 0.006$ and Completion Ratio of $0.716\pm 0.006$) while maintaining competitive infrastructure throughput (V2I rate of $9.251\pm 0.114$). These results indicate that QTRAN effectively captures non-linear interference interactions, enabling coordinated decentralized spectrum and power decisions under the adopted density-based evaluation setting, thereby enhancing V2V reliability and throughput in cognitive Internet of Vehicles. Full article

The development of sustainable electrocatalysts for clean energy by modifying biomass-derived activated carbon with nitrogen and transition metals is presented. Activated carbon (AWC) material was obtained using alder wood char as a precursor, while nitrogen and cobalt or copper nanoparticles were incorporated with the aim of creating efficient materials for hydrazine oxidation (HzOR) and direct hydrazine–hydrogen peroxide fuel cells (DHHPFC, N₂H₄–H₂O₂). The composition, structure, and surface morphology of the created materials were examined using X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), energy-dispersive X-ray analysis (EDX), and inductively coupled plasma optical emission spectroscopy (ICP-OES). The activity of the AWC, AWC–Co–N, and AWC–Cu–N catalysts for HzOR was investigated using cyclic voltammetry (CV) and linear sweep voltammetry (LSV). N₂H₄–H₂O₂ fuel-cell tests were performed by applying the catalysts as both the anode and cathode. It was found that all materials retained a hierarchical porous carbon framework, while metal incorporation altered surface compactness. Cobalt doping produced well-dispersed Co nanoparticles and abundant Co–N–C coordination sites, whereas Cu introduction resulted in moderately compact structures with uniformly distributed Cu-based nanoparticles. Electrochemical measurements demonstrated that both metal dopants enhanced HzOR activity, with the catalytic performance following the order of AWC–Co–N > AWC–Cu–N > AWC. Fuel-cell testing further confirmed this trend: AWC–Co–N achieved the highest maximum power density (30.4 mW cm⁻²), outperforming AWC–Cu–N (17.7 mW cm⁻²). These results identify AWC–Co–N as a highly effective bifunctional electrocatalyst for DHHPFCs. Full article

Portable industrial X-ray flaw detectors operating in outdoor environments predominantly rely on small diesel generators for power supply. However, the inherent grid frequency drift of such weak grids induces critical phase-shift mismatches in conventional fixed-delay controllers, leading to voltage loss-of-control. This study aims to develop a robust, frequency-adaptive power drive system to overcome these operational challenges. A dynamic zero-crossing capture mechanism is proposed to extract real-time grid frequency variations, enabling instantaneous phase-shift feedforward compensation. This mechanism is integrated with an adaptive incremental proportional–integral–derivative (PID) controller that utilizes grid-condition recognition to dynamically schedule gains and neutralize frequency disturbances. Furthermore, a linear voltage soft-start strategy is incorporated to coordinate downstream constant-current regulation, preventing inrush currents. Concurrently, an offline downtime perception mechanism executes autonomous stepped-voltage conditioning to prevent cold high-voltage breakdowns. Simulation and hardware experimental results demonstrate that under continuous generator frequency drift, the adaptive control maintains a steady-state voltage error below 1%, suppresses the voltage ripple factor to 1.11%, and limits tube current fluctuations to 4.2%. The proposed system effectively mitigates weak-grid instability, ensuring reliable high-voltage generation and extending component lifespan for demanding non-destructive testing (NDT) applications. Full article

Surfactant-enhanced soil washing is a promising strategy for the remediation of organochlorine pesticide (OCPs) contaminated sites. In this study, we constructed a comprehensive evaluation framework integrating efficient parameter optimization, effluent recovery and ecological restoration assessment. Among the 14 evaluated washing agents, the non-ionic surfactant Triton X-100 exhibited superior solubilization capacity for highly hydrophobic OCPs. Under an optimal dosage of 2.0%, Triton X-100 achieved near-complete extraction of γ-chlordane and over 75% removal of mirex in both moderately and severely contaminated soils. Powdered activated carbon (PAC) demonstrated exceptional selective adsorption performance, significantly outperforming activated carbon fiber (ACF). The optimal PAC dosages (20 g/L) could extract over 90% of OCPs from the soil washing effluents, facilitating potential washing agent recycling. Furthermore, community-level physiological profiling (BIOLOG-AWCD) revealed distinct ecological trajectories post-washing. While nitrogen and phosphorus (N/P) bio-stimulation successfully restored and even surpassed the microbial diversity in moderately contaminated soils, it only partially alleviated the ecological vulnerability in severely contaminated soils (Simpson index < 0.45). These findings underscore that while surfactant-enhanced soil washing combined with selective adsorption constitutes a powerful physicochemical remediation cycle, restoring heavily degraded microhabitats necessitates an integrated approach coupling bio-stimulation with phytoremediation. Full article

Background/Objectives: Higher energy and carbohydrate intakes have been hypothesized to enhance resistance training adaptations, yet empirical evidence remains mixed. The purpose of this study was to investigate whether supplemental carbohydrate–energy intake improves muscle hypertrophy and strength. Methods: Twenty resistance-trained men (26.7 ± 4.9 years old, 9.7 ± 6.1 years training experience) completed a quasi-randomized, double-blinded, counterbalanced crossover trial. Participants consumed either a daily protein-only supplement (30 g protein, 4 g carbohydrate) or a daily protein-plus-carbohydrate supplement (30 g protein, 54 g carbohydrate) for 8 weeks each, followed by crossover, while continuing their habitual training and nutrition. Primary outcomes included lean mass obtained using dual-energy X-ray absorptiometry, muscle thickness and cross-sectional area obtained via ultrasound, back squat one-repetition maximum, fatigue index, and knee extensor peak torque. Differences in estimated marginal means, controlling for order and phase effects, were analyzed via linear mixed models, with first-phase-only ANCOVAs as sensitivity analyses. Results: The carbohydrate–protein condition resulted in significantly higher daily energy (+485 kcal/d; p = 0.017) and carbohydrate intake (+33 g/d; p = 0.043) than the protein-only condition, with no differences in protein or fat intake or training volume. No significant differences between conditions were observed for any outcome, including in the sensitivity analyses. Conclusions: Modest supplemental carbohydrate–energy intake did not significantly augment muscle hypertrophy, fatigue resistance or strength in trained men within our study context. More high-powered research is needed to determine how much and under which circumstances carbohydrate–energy intake affects resistance training adaptations. Full article

This paper introduces and investigates a novel two-parameter sequence, termed the biparametric Appell extension (B-App-Ex) and denoted by ${\mathcal{B}}_n(x;\lambda ,\alpha )$. Standard classical Appell sequences often lack sufficient structural parameters, which can limit their operational flexibility in certain advanced spectral schemes. To address this limitation, we construct an enhanced operational framework by integrating a binomial structural kernel ${(1+w)}^{\lambda }$ with a linear exponential scaling $e^{\alpha xw}$ entirely within the Appell class. We provide a rigorous logical deduction of the fundamental properties of this sequence, including its explicit power series representation, a characteristic three-term recurrence relation, and a governing second-order differential equation (DEq.). A significant contribution of this work is the establishment of analytically exact connection and inverse connection formulas between the B-App-Ex basis and various classical orthogonal polynomial (COP) families. Numerical verification via a collocation-based projection framework demonstrates that these algebraic kernels achieve near-machine epsilon precision (≈${10}^{-15}$), remaining stable even for high-order approximations. Furthermore, by isolating the dilation factor $\alpha$, we establish an $O\left(N\right)$ computational complexity that offers a reduction in latency by approximately two orders of magnitude compared to classical matrix-based transformations. The results demonstrate that the proposed biparametric (Bip.) extension offers a versatile and highly optimized analytical template for modeling complex dynamic systems where structural shifting and spatial scaling must be tuned simultaneously. Full article

Permalloy (Py) is a crucial component in spin nano-oscillators due to its excellent soft magnetic properties. Due to orbital angular momentum quenching, Py exhibits very low magnetic damping. It reduces intrinsic energy dissipation during precession, which is beneficial for lowering operational power consumption and enhancing the thermal stability of certain memory devices. But lower magnetic damping limits its application in fast-switching spintronic devices. Thus, in this work, the rare earth element Gd is introduced into Py to further enhance the spintronic performance of Py_100−xGd_x alloys. Through spin-torque ferromagnetic resonance measurements (ST-FMRs), the maximum spin Hall angle of the system was calculated to be 0.149 when x = 20, significantly exceeding that of 0.042 in the pure Py sample. Additionally, Gd doping significantly enhances the ability to modulate the magnitude of the linewidth. Also, as the Gd content in the alloy increased, the magnetic damping coefficient of the device gradually rose, reaching a peak in the sample with 17% Gd content. The maximum magnetic damping coefficient of the Py-Gd alloy was 0.051, representing an approximate 2.4-fold increase compared to that of pure Py. The findings of this study confirm that the use of rare-earth elements is highly effective in tuning the performance of spintronic devices and provide support for the development of highly efficient SOT devices. It is noted that the regulation of magnetic damping by Py-Gd holds significant implications for enhancing the magnetization switching speed of SOT devices and reducing the drive current density for microwave emission in spin nano-oscillators. Full article

The adhesive bonding of aluminum with other materials is widely used in the aerospace, marine, automotive and railroad industries that require lightweight materials. Adhesive bonding has the advantages of reduced corrosion, stress concentration, and cost effectiveness. To improve bonding strength and performance, we examined the use of ascorbic acid (vitamin C), which is a water-soluble compound and a natural reducing agent. Owing to its reducing power and acidity, ascorbic acid allows the Al etching process to proceed efficiently to increase the surface roughness and prevent Al oxidation. In addition, this study used an eco-friendly technique of simply immersing aluminum substrates in an ascorbic acid solution with sodium chloride. The surface free energy was evaluated using the sessile drop method and calculated using the Owens–Wendt–Rabel and Kaelble method. Confocal microscope was used to investigate the roughness of the surface, and the functional groups of Al surface were analyzed by X-ray photoelectron spectroscopy. The bonding strength was measured using the single-lap joint shear test. Compared to aluminum without treatment, the bonding strength of a treated AA 6061 was enhanced by 58.6%. Full article

Self-powered integrated electrochemical systems require electrode materials that can simultaneously provide energy storage and sensing functions. Boron-doped diamond (BDD) electrodes have good chemical stability and a wide potential window, but their small specific surface area and slow interfacial charge transfer limit their use in such bifunctional applications. In this work, we prepared a three-dimensional porous BDD scaffold on titanium foam by hot-filament chemical vapor deposition, and then grew polypyrrole (PPy) layers on the scaffold by in situ oxidative polymerization. The polymerization time was varied from 8 to 20 h. The BDD/PPy composite obtained after 12 h showed an areal capacitance of 398.6 ± 15.2 mF/cm² at 1 mA/cm², which is about 5.8 times that of the porous BDD alone (67.9 mF/cm²). Its charge transfer resistance (R_ct) was as low as 1.3 ± 0.1 Ω, among the lowest reported for BDD-based electrodes. The porous BDD framework provides ion diffusion pathways, while the PPy layer introduces pseudocapacitance. X-ray photoelectron spectroscopy reveals that the PPy layer contains pyrrolic –NH– groups, which are known to chelate various water pollutants (e.g., heavy metal ions and organic molecules). Based on these surface properties and the low R_ct, we suggest that this composite may have theoretical potential for preconcentrating and detecting multiple pollutants. This work demonstrates a way to improve the capacitance of BDD-based electrodes and may serve as a starting point for future exploration in integrated energy-sensing devices after experimental validation. Full article

The microstructure of as-cast Al-xSi (x = 4, 7, 10) alloys solidified under various cooling rates was characterized using scanning electron microscopy (SEM). To overcome the multicollinearity among eutectic silicon parameters, Principal Component Regression (PCR) analysis was employed to quantitatively evaluate the effects of silicon morphology, scale, and content on the electrical conductivity of the alloys. The results demonstrate that rapid solidification significantly refines the plate-like eutectic silicon and reduces its volume fraction, leading to improved electrical conductivity. The PCR model shows that a hierarchical mechanism: volume fraction (PC1) acts as the principal determinant, increasing baseline resistance primarily by truncating the electron mean free path (MFP); meanwhile, within identical alloy systems, morphological parameters (PC2) play a dominant regulatory role. A semi-quantitative electron drift path model was established, confirming that the morphological deviation of eutectic silicon from a spherical shape (i.e., increased aspect ratio) causes a non-linear increase in the amplitude of electron detours. This geometric elongation significantly degrades electrical conductivity, providing theoretical guidance for the microstructural design of high-conductivity Al-Si alloys, which can be practically applied to the manufacturing and optimization of lightweight, heat-dissipating enclosures for new energy vehicle (NEV) motors and power distribution systems. Full article

This paper presents the design and implementation of an X-band voltage-controlled oscillator (VCO) fabricated in a standard 180-nm CMOS process. To sustain stable oscillation under a constrained power budget, a gm-boosted topology is employed, integrating vertically stacked cross-coupled transistors with a center-tapped transformer to enhance the equivalent negative conductance. The boosting is achieved through two complementary mechanisms: the center-tapped transformer performs an impedance transformation that repurposes the layout parasitic capacitances into transconductance-enhancing elements, while the stacked cross-coupled pair reuses the DC current and suppresses the source-degeneration of a conventional pair, jointly sustaining a robust start-up margin at a low 0.75 V supply. On-wafer measurement results demonstrate a frequency tuning range from 8.78 GHz to 9.13 GHz as the control voltage is swept from 0 V to 1.8 V, with an average VCO gain K_VCO of 447.5 MHz/V. Under a total DC power consumption of 6.9 mW, the oscillator delivers an output power of 4.54 dBm and exhibits a measured phase noise of −103 dBc/Hz at a 1-MHz offset. Full article

Skin aging is a central focus of skin health. Supramolecular chemistry has emerged as a powerful strategy for enhancing the performance of cosmetic active ingredients. Adenosine is a promising anti-aging ingredient in skincare products, but its cosmetic application is limited by poor water solubility and low skin penetration. This study developed a supramolecular complex combining adenosine with ectoine through cocrystallization. The supramolecular assembly was characterized by differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA). Powder X-ray diffraction (PXRD), Fourier-transform infrared spectroscopy (FTIR) and density functional theory (DFT) calculations revealed extensive hydrogen-bonding networks between the components. The optimal supramolecular composition (1:1.5 molar ratio) achieved a 5.5-fold increase in water solubility. The supramolecular organization enhanced skin permeability by 3.1-fold in ex vivo porcine skin models. In fibroblast cell models, the supramolecular system exhibited superior antioxidant activity with 30.3% greater reactive oxygen species (ROS) reduction and restored cellular adenosine triphosphate (ATP) levels by 2.1-fold under H₂O₂-induced oxidative stress compared to individual components. These findings demonstrate that the adenosine–ectoine supramolecular complex represents an innovative multifunctional ingredient for basic anti-aging cosmetics, offering enhanced delivery, improved safety, and superior biological efficacy through supramolecular engineering. Full article