Search Results (86)

The aim of this study was to determine the connection between oscillations in operating pressure values and the appearance of various irregularities on machined surfaces. Such oscillations are a consequence of the high water pressure generated during abrasive water jet machining. Oscillations in the operating pressure values are periodic, namely due to the cyclic operation of the intensifier and the physical characteristics of water. One of the most common means of reducing this phenomenon is installing an attenuator in the hydraulic system or a phased intensifier system. The main hypothesis of this study was that the topography of a machined surface is directly influenced by the inability of the pressure accumulator to fully absorb water pressure oscillations. In this study, we monitored changes in hydraulic oil pressure values at the intensifier entrance and their connection with irregularities on the machined surface—such as waviness—when cutting aluminum AlMg3 of different thicknesses. Experimental research was conducted in order to establish this connection. Aluminum AlMg3 of different thicknesses—from 6 mm to 12 mm—was cut with different traverse speeds while hydraulic oil pressure values were monitored. The pressure signals thus obtained were analyzed by applying the fast Fourier transform (FFT) algorithm. We identified a single-sided pressure signal amplitude spectrum. The frequency axis can be transformed by multiplying inverse frequency data with traverse speed; in this way, a single-sided amplitude spectrum can be obtained, examined against the period in which striations are expected to appear (in millimeters). In the lower zone of the analyzed samples, striations are observed at intervals determined by the dominant hydraulic oil pressure harmonics, which are transferred to the operating pressure. In other words, we demonstrate how the machined surface topography is directly induced by water jet pressure frequency characteristics. Full article

M-edge X-ray absorption spectroscopy (XAS), which probes 3p→3d transitions in first-row transition metals, provides detailed insights into oxidation states, spin-states, and local electronic structure with high element and orbital specificity. Operating in the extreme ultraviolet (XUV) region, this technique provides sharp multiplet-resolved features with high sensitivity to ligand field and covalency effects. Compared to K- and L-edge XAS, M-edge spectra exhibit significantly narrower full widths at half maximum (typically 0.3–0.5 eV versus >1 eV at the L-edge and >1.5–2 eV at the K-edge), owing to longer 3p core-hole lifetimes. M-edge measurements are also more surface-sensitive due to the lower photon energy range, making them particularly well-suited for probing thin films, interfaces, and surface-bound species. The advent of tabletop high-harmonic generation (HHG) sources has enabled femtosecond time-resolved M-edge measurements, allowing direct observation of ultrafast photoinduced processes such as charge transfer and spin crossover dynamics. This review presents an overview of the fundamental principles, experimental advances, and current theoretical approaches for interpreting M-edge spectra. We further discuss a range of applications in catalysis, materials science, and coordination chemistry, highlighting the technique’s growing impact and potential for future studies. Full article

Silicon (Si) and silicon carbide (SiC) are second- and third-generation semiconductor materials with excellent properties that are particularly suitable for applications in scenarios such as high temperature, high voltage, and high frequency. Si/SiC wafers face warpage and bending problems during production, which can seriously affect subsequent processing. Fast, accurate, and comprehensive detection of thickness, thickness variation, and flatness (including bow and warpage) of SiC and Si wafers is an industry-recognized challenge. Frequency scanning interferometry (FSI) can synchronize the upper and lower surfaces and thickness information of transparent parallel thin wafers, but it is still affected by multiple interfacial harmonic reflections, reflectivity asymmetry, and phase modulation uncertainty when measuring SiC thin wafers, which leads to thickness calculation errors and face reconstruction deviations. To this end, this paper proposes a high-precision facet reconstruction method for SiC/Si structures, which combines harmonic spectral domain decomposition, refractive index gradient constraints, and partitioning optimization strategy, and introduces interferometric signal “oversampling” and weighted fusion of multiple sets of data to effectively suppress higher-order harmonic interferences, and to enhance the accuracy of phase resolution. The multi-layer iterative optimization model further enhances the measurement accuracy and robustness of the system. The flatness measurement system constructed based on this method can realize the simultaneous acquisition of three-dimensional top and bottom surfaces on 6-inch Si/SiC wafers, and accurately reconstruct the key parameters, such as flatness, warpage, and thickness variation (TTV). A comparison with the Corning Tropel FlatMaster commercial system shows that this method has high consistency and good applicability. Full article

Surface-mounted permanent magnet synchronous generators (SPMSGs) are well suited for wind power applications mainly because of their high power density, low cogging torque, and effective thermal management. This study proposes an eccentric Halbach PM array pole shape to enhance the power generation capability of SPMSGs specifically designed for low-speed wind power generation. The topology of the proposed eccentric Halbach PM arrangement is optimized using a genetic algorithm. Two-dimensional finite element simulations indicate that the eccentric Halbach configuration significantly improves flux focusing and magnetic field distribution. Compared to the conventional design, the proposed structure exhibits a substantial increase in electromotive force with reduced total harmonic distortion. Cogging torque is reduced by 48.6%, supporting improved starting and low-speed operation. Under on-load, the proposed design delivers higher average torque with reduced ripple, contributing to smoother operation. At a rated speed, the output power increases by 25%, with consistently higher power generation capability across a wide range of load conditions. Additionally, the proposed generator achieves higher efficiency across all operating speeds. These findings confirm the effectiveness of the eccentric Halbach array configuration in improving the power generation capability of SPMSG, thereby reinforcing its applicability to low-speed wind energy systems aligned with long-term sustainability objectives. Full article

Modular multilevel converter (MMC) circulating current suppression is an effective method in improving power conversion quality. However, due to the complex composition of circulation under a three-phase imbalanced state, as well as the limitations of existing sliding mode circulation suppression methods that can easily cause high-frequency oscillation in the system, the circulation suppression effectiveness still needs to be further improved. Firstly, this article clarifies the phase sequence law and key control factors of the circulation by separating the MMC circulation phase sequence and decoupling the model. Secondly, the generalized proportional integral sliding surface and the hyperbolic tangent convergence law are introduced into sliding mode control to improve the system’s ability to flexibly suppress the circulating current. Then, the proposed method is evaluated using the system power quality and insulated-gate bipolar transistor (IGBT) junction temperature amplitude. The results show that the proposed method reduces the total harmonic distortion of the bridge arm current to 1.28% and 1.03%, respectively, under three-phase balanced and imbalanced states, and effectively smooths the IGBT junction temperature fluctuation of submodules. It also improves the stability and robustness of MMC system to circulation suppression gain variations, sudden load changes, and switching failures. This article provides an effective method for the synchronous implementation of MMC circulation suppression and IGBT junction temperature smoothing under complex and variable operating conditions. Full article

Environmental pollution from organic dyes such as malachite green and rhodamine B poses significant threats to ecosystems and human health due to their toxic properties. The rapid detection of these contaminants with high sensitivity and selectivity is crucial and can be effectively achieved using nonlinear optical methods. In this study, we combine the Simplified Bond Hyperpolarizability Model (SBHM) and molecular docking (MD) simulations to investigate the Second-Harmonic Generation (SHG) intensity of organic dyes on a silicon (Si(001)) substrate for nanoscale pollutant detection. Our simulations show good agreement with rotational anisotropy (RA) SHG intensity experimental data across all polarization angles, with a total error estimate of 3%. We find for the first time that the SBHM not only identifies the different organic pollutant dyes on the surface, as in conventional SHG detection, but can also determine their relative orientation and different concentrations on the surface. Meanwhile, MD simulations reveal that rhodamine B shows a strong adsorption affinity of $-10.4\mathrm{kcal}/\mathrm{mol}$ to a single-layer graphene oxide (GO) substrate, primarily through $\pi$-$\pi$ stacking interactions (36 instances) and by adopting a perpendicular molecular orientation. These characteristics significantly enhance SHG sensitivity. A nonlinear susceptibility analysis reveals good agreement between the SBHM and group theory. The susceptibility tensors confirm that the dominant contributions to the SHG signal arise from both the molecular structure and the surface interactions. This underscores the potential of GO-coated silicon substrates for detecting trace levels of organic pollutants with interaction distances ranging from $3.75\AA$ to $5.81\AA$. This approach offers valuable applications in environmental monitoring, combining the sensitivity of SHG with the adsorption properties of GO for nanoscale detection. Full article

The use of advanced brittle composites in engineering systems has necessitated robotic rotary ultrasonic machining to attain high precision with minimal machining defects such as delamination, burrs, and cracks. Longitudinal–torsional coupled (LTC) vibrations are created by introducing helical slots to a horn’s profile to enhance the quality of ultrasonic machining. In this investigative research, modified ultrasonic horns were designed for a giant magnetostrictive transducer by generating helical slots in catenoidal and cubic polynomial profiles to attain a high amplitude ratio ($T_A/L_A$) and low stress concentrations. Novel ultrasonic horns with a giant magnetostrictive transducer were modelled to compute impedances and harmonic excitation responses. A structural dynamic analysis was conducted to investigate the effect of the location, width, depth and angle of helical slots on the Eigenfrequencies, torsional vibration amplitude, longitudinal vibration amplitude, stresses and amplitude ratio in novel LTC ultrasonic horns for different materials using the finite element method (FEM) based on the block Lanczos and full-solution methods. The newly designed horns achieved a higher amplitude ratio and lower stresses in comparison to the Bezier and industrial stepped LTC horns with the same length, end diameters and operating conditions. The novel cubic polynomial LTC ultrasonic horn was found superior to its catenoidal counterpart as a result of an $8.45\%$ higher amplitude ratio. However, the catenoidal LTC ultrasonic horn exhibited 1.87% lower stress levels. The position of the helical slots was found to have the most significant influence on the vibration characteristics of LTC ultrasonic horns followed by the width, depth and angle. This high amplitude ratio will contribute to the improved vibration characteristics that will help realize good surface morphology when machining advanced materials. Full article

External-rotor dual-armature flux-switching PM (ER-DA-FSPM) machines have high torque density and decent fault tolerance, making them promising candidates for in-wheel machine applications in electric vehicles. The torque output and optimal design parameters of ER-DA-FSPM machines are affected by the stator/rotor torque ratio, which is the focus of this paper. Firstly, this paper analyzes airgap flux density harmonics of ER-DA-FSPM to provide a clear insight into the torque-generation mechanism. Then, this paper investigates the influence of torque ratio on average torque under the same copper loss. It is found that the average torque decreases with torque ratio increasing due to the reduction of the positive torque component generated by the sixth airgap field harmonics and the rise in the negative torque component from the eighth harmonics. Moreover, this paper also provides the optimal parameter recommendation to guide the machine design. The split ratio should increase, and the arc of PMs should decrease for a larger torque ratio, whilst the other parameters are hardly influenced. Next, this paper makes a comparison among the ER-DA-FSPM machine, external rotor flux-switching PM (ER-FSPM) machine, and surface-mounted PM (ER-SPM) machines. It shows that the ER-DA-FSPM machine, with the torque ratio being 2, can lead to a much larger total torque. In addition, in the event of rotor winding failure, which is more possible due to the existence of slip rings than stator winding failure, the stator can still provide an average torque larger than that of ER-SPM machine and 92.0% that of the ER-FSPM machine, respectively. Finally, the theoretical analysis is verified by the experiments. Full article

Accurately generating high-resolution surface grid datasets often involves merging multiple weather observation networks and addressing the challenge of network heterogeneity. This study aims to tackle the problem of accurately interpolating temperature data in regions with a complex topography. To achieve this, we introduce a deterministic interpolation method that incorporates elevation to enhance the accuracy of temperature datasets. This method is particularly valuable for areas with intricate terrains. Our robust methodology integrates a network harmonization method with radial basis function (RBF) interpolation for complex topographical regions. The method was tested on 10 min average temperature data from Jeju Island, South Korea, over 2 years that had a spatial resolution of 100 m. The results show a significant reduction of 5.5% in error rates, from an average of 0.73 °C to 0.69 °C, by incorporating all adjusted data. Integrating a parameterized nonlinear temperature profile further enhances accuracy, yielding an average reduction of 4.4% in error compared to the linear model. The spatial interpolation method, based on regression-based radial basis functions, demonstrates a 6.7% improvement over regression-based kriging for the same temperature profile. This research offers a valuable approach for precise temperature interpolation, especially in regions with a complex topography. Full article

Material nonlinearity is explored for the assessment of structural integrity. Crack–wave interactions are of particular interest. The major focus is on higher-order harmonics, generated in propagating shear horizontal (SH) waves. These harmonics are generated due to global material nonlinearity and local effects such as fatigue cracks. The theoretical background of the proposed method is explained. The method is examined using numerical simulations and experimental tests. The former involves the Local Interaction Simulation Approach (LISA), implemented for the nonlinear shear horizontal wavefield. The latter is based on a high-frequency shear excitation approach. Experimental tests are conducted using a series of beam specimens with fatigue cracks. Low-profile, surface-bonded piezoceramic shear actuators are used for excitation. The excitation frequency is selected to minimize the number of generated modes in the examined specimens. Nonlinear ultrasonic responses are collected using a non-contact laser vibrometer. The results show that higher-order harmonic generation—based on shear horizontal wave propagation—can be used for crack detection in the presence of global material nonlinearity. Full article

The generation of ozone by dielectric barrier discharge (DBD) is widely used for water and wastewater treatment, the control of catalytic reactions, and surface treatment. Recently, a need for compact, effective, and economical ozone and reactive oxygen–nitrogen species (RONS) generators for medical, biological, and agricultural applications has been observed. In this study, a novel hybrid DBD (HDBD) reactor fulfilling such requirements is presented. Its structured high-voltage (HV) electrode allows for the ignition of both the surface and volume microdischarges contributing to plasma generation. A Peltier module cooling of the dielectric barrier, made of alumina, allows for the efficient control of plasma chemistry. The typical electrical power consumption of this device is below 30 W. The operation frequency of the DBD driver oscillating in the auto-resonance mode is from 20 to 40 kHz. The specific energy input (SEI) of the reactor was controlled by the DBD driver input voltage in the range from 10.5 to 18.0 V, the Peltier current from 0 to 4.5 A, the duty cycle of the pulse-width modulated (PWM) power varied from 0 to 100%, and the gas flow from 0.5 to 10 SLM. The operation with oxygen, synthetic air, and compressed dry air (CDA) was characterized. The ultraviolet light (UV) absorption technique was implemented for the measurement of the ozone concentration. The higher harmonics of the discharge current observed in the frequency range of 5 to 50 MHz were used for monitoring the discharge net power. Full article

Continuous and dense time series of satellite remote sensing data are needed for several land monitoring applications, including vegetation phenology, in-season crop assessments, and improving land use and land cover classification. Supporting such applications at medium to high spatial resolution may be challenging with a single optical satellite sensor, as the frequency of good-quality observations can be low. To optimize good-quality data availability, some studies propose harmonized databases. This work aims at developing an ‘all-in-one’ Google Earth Engine (GEE) web-based workflow to produce harmonized surface reflectance data from Landsat-7 (L7) ETM+, Landsat-8 (L8) OLI, and Sentinel-2 (S2) MSI top of atmosphere (TOA) reflectance data. Six major processing steps to generate a new source of near-daily Harmonized Landsat and Sentinel (HLS) reflectance observations at 30 m spatial resolution are proposed and described: band adjustment, atmospheric correction, cloud and cloud shadow masking, view and illumination angle adjustment, co-registration, and reprojection and resampling. The HLS is applied to six equivalent spectral bands, resulting in a surface nadir BRDF-adjusted reflectance (NBAR) time series gridded to a common pixel resolution, map projection, and spatial extent. The spectrally corresponding bands and derived Normalized Difference Vegetation Index (NDVI) were compared, and their sensor differences were quantified by regression analyses. Examples of HLS time series are presented for two potential applications: agricultural and forest phenology. The HLS product is also validated against ground measurements of NDVI, achieving very similar temporal trajectories and magnitude of values (R² = 0.98). The workflow and script presented in this work may be useful for the scientific community aiming at taking advantage of multi-sensor harmonized time series of optical data. Full article

Acute and chronic liver failure are clinically significant conditions, and the artificial liver support system (ALSS) is emerging as a novel and effective approach for the clinical management of liver failure. Within this framework, scaffold materials occupy a pivotal position as integral components of the bioreactor. Elevating the performance capabilities of these scaffolds not only augments the therapeutic efficacy of the artificial liver but also lays the groundwork for refining and selecting large-scale hepatocyte culture models. In this study, we introduced a novel hepatocyte scaffold material designated as PET-COL, crafted by coating polyethylene terephthalate (PET) with collagen. This involved a sequence of modifications, including alkaline hydrolysis, EDC/NHS activation and crosslinking, as well as collagen conjugation. The physicochemical attributes of the scaffold were thoroughly characterized by Fourier-transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), second harmonic generation (SHG), water contact angle measurements, and high-performance liquid chromatography–mass spectrometry (HPLC-MS). Furthermore, an investigation into the material’s biological properties was conducted that encompassed SEM (HepaRG growth), fluorescence staining (assessment of cell viability), staining by trypan blue (HepaRG counting), CCK-8 (proliferation of cells), biochemical testing, and immunosorbent assay. Our findings revealed that collagen was covalently bonded to the PET surface, leading to a substantial enhancement in the material’s hydrophilicity (p < 0.001). The quantity of collagen coating was determined to be precisely 33.30 μg per scaffold. Human liver progenitor HepaRG cells thrived on the PET-COL material. Compared with the untreated group, cell viability, albumin secretion, urea synthesis, and the expression levels of CYP3A4 and CPS1 increased significantly (p < 0.001), demonstrating remarkable biological vitality. The PET-COL scaffold, as developed in this study, holds immense potential for application in bioartificial livers. Full article

Wetlands are integral components of agricultural landscapes, providing a wide range of ecological, economic, and social benefits essential for sustainable development and rural livelihoods. Globally, they are vulnerable ecological assets facing several significant threats including water extraction and regulation, land clearing and reclamation, and climate change. Classification and mapping of wetlands in agricultural landscapes is crucial for conserving these ecosystems to maintain their ecological integrity amidst ongoing land-use changes and environmental pressures. This study aims to establish a robust framework for wetland classification and mapping in intensive agricultural landscapes using time series of Sentinel-2 imagery, with a focus on the Gwydir Wetland Complex situated in the northern Murray–Darling Basin—Australia’s largest river system. Using the Google Earth Engine (GEE) platform, we extracted two groups of predictors based on six vegetation indices time series calculated from multi-temporal Sentinel-2 surface reflectance (SR) imagery: the first is statistical features summarizing the time series and the second is phenological features based on harmonic analysis of time series data (HANTS). We developed and evaluated random forest (RF) models for each level of classification with combination of different groups of predictors. Our results show that RF models involving both HANTS and statistical features perform strongly with significantly high overall accuracy and class-weighted F1 scores (p < 0.05) when comparing with models with either statistical or HANTS variables. While the models have excellent performance (F-score greater than 0.9) in distinguishing wetlands from other landcovers (croplands, terrestrial uplands, and open waters), the inter-class discriminating power among wetlands is class-specific: wetlands that are frequently inundated (including river red gum forests and wetlands dominated by common reed, water couch, and marsh club-rush) are generally better identified than the ones that are flooded less frequently, such as sedgelands and woodlands dominated by black box and coolabah. This study demonstrates that HANTS features extracted from time series Sentinel data can significantly improve the accuracy of wetland mapping in highly fragmentated agricultural landscapes. Thus, this framework enables wetland classification and mapping to be updated on a regular basis to better understand the dynamic nature of these complex ecosystems and improve long-term wetland monitoring. Full article

This work investigates a metasurface design to achieve remarkable second harmonic generation (SHG) conversion efficiency and enhance effective nonlinear susceptibility using the finite element method. The elements of the designed structure are composed of a rectangular split-ring resonator Ag film, a bowtie-shaped Ag nanoantenna, and a pair of Bi bars that induce nonlinear optical phenomena due to the nonuniform distribution of the electric and magnetic fields within the device surface. The simulation results agree perfectly with the theory and demonstrate outstanding achievements in terms of SHG conversion efficiency (η) and effective nonlinear susceptibility ($\left|{\chi }_{eff}^{\left(2\right)}\right|$). Specifically, the metasurface reaches a peak η value of $4.544\times {10}^{-8}$ and an effective nonlinear susceptibility of $3.4\times {10}^4$ pm/V. This work presents a novel and versatile design to achieve high η and $\left|{\chi }_{eff}^{\left(2\right)}\right|$in an SHG metasurface. Full article