Search Results (2,006)

Electrochemical CO₂ reduction reaction (CO₂RR) is a key technology for achieving carbon neutrality and efficient utilization of renewable energy, capable of converting CO₂ into high-value-added carbon-based fuels and chemicals. Copper (Cu)-based catalysts have attracted significant attention due to their unique performance in generating multi-carbon (C₂₊) products such as ethylene and ethanol; however, there are still many controversies regarding their complex reaction mechanisms, active sites, and the dynamic evolution of intermediates. In situ Raman spectroscopy, with its high surface sensitivity, applicability in aqueous environments, and precise detection of molecular vibration modes, has become a powerful tool for studying the structural evolution of Cu catalysts and key reaction intermediates during CO₂RR. This article reviews the principles of electrochemical in situ Raman spectroscopy and its latest developments in the study of CO₂RR on Cu-based catalysts, focusing on its applications in monitoring the dynamic structural changes of the catalyst surface (such as Cu⁺, Cu⁰, and Cu²⁺ oxide species) and identifying key reaction intermediates (such as *CO, *OCCO(*O=C-C=O), *COOH, etc.). Numerous studies have shown that Cu-based oxide precursors undergo rapid reduction and surface reconstruction under CO₂RR conditions, resulting in metallic Cu nanoclusters with unique crystal facets and particle size distributions. These oxide-derived active sites are considered crucial for achieving high selectivity toward C₂₊ products. Time-resolved Raman spectroscopy and surface-enhanced Raman scattering (SERS) techniques have further revealed the dynamic characteristics of local pH changes at the electrode/electrolyte interface and the adsorption behavior of intermediates, providing molecular-level insights into the mechanisms of selectivity control in CO₂RR. However, technical challenges such as weak signal intensity, laser-induced damage, and background fluorescence interference, and opportunities such as coupling high-precision confocal Raman technology with in situ X-ray absorption spectroscopy or synchrotron radiation Fourier transform infrared spectroscopy in researching the mechanisms of CO₂RR are also put forward. Full article

Environmental vibrations may affect the functional use of engineering structures and even lead to disastrous consequences. Vibration suppression and energy harvesting based on Nonlinear Energy Sink (NES) and the piezoelectric effect have gained significant attention in recent years. The harvested electrical energy can supply power to the structural health monitoring sensor device. In this work, the electromechanical-coupled governing equations of the primary structure coupled with the series-connected 2-degree-of-freedom NES (2-DOF NES) integrated by a piezoelectric energy harvester are derived. The absorption and dissipation performances of the system under varying transient excitation intensities are investigated. Additionally, the targeted energy transfer mechanism between the primary structure and the two NESs oscillators is investigated using the wavelet analysis. The reduced slow flow of the dynamical system is explored through the complex-variable averaging method, and the primary factors for triggering the target energy transfer phenomenon are revealed. Furthermore, a comparison is made between the vibration suppression performance of the single-degree-of-freedom NES (S-DOF NES) system and the 2-DOF NES system as a function of external excitation velocity. The results indicate that the vibration suppression performance of the first-level NES (NES1) oscillator is first stimulated. As the external excitation intensity gradually increases, the vibration suppression performance of the second-level NES (NES2) oscillator is also triggered. The 1:1:1, high-frequency, and low-frequency transient resonance captures are observed between the primary structure and NES1 and NES2 oscillators over a wide frequency range. The 2-DOF NES demonstrates superior efficiency in suppressing vibrations of the primary structure and exhibits enhanced robustness to varying external excitation intensities. This provides a new strategy for structural vibration suppression and online power supply for health monitoring devices. Full article

Ball joints are components of the vehicle axle, and their friction characteristics must be considered when evaluating vibration behavior and ride comfort in driving simulator-based simulations. To model the three-dimensional friction behavior of ball joints, real-time capability and intuitive parameterization using data from standardized component test benches are essential. These requirements favor phenomenological modeling approaches. This paper applies a spherical, three-dimensional friction model based on the LuGre model, compares it with alternative approaches, and introduces a universal parameter estimation framework using machine learning. Furthermore, the kinematic operating ranges of ball joints are derived from vehicle measurements, and component-level measurements are conducted accordingly. The collected measurement data are used to estimate model parameters through gradient-based optimization for all considered models. The results of the model fitting are presented, and the model characteristics are discussed in the context of their suitability for online simulation in a driving simulator environment. We demonstrate that the proposed parameter estimation framework is capable of learning all the applied models. Moreover, the three-dimensional LuGre-based approach proves to be well suited for capturing the dynamic friction behavior of ball joints in real-time applications. Full article

Selecting optimal measurement points to capture maximum vertical vibration levels induced by metro systems on adjacent buildings is a crucial yet often overlooked task. In this study, an on-site vibration test and simulation analysis of a building near the Nanjing metro line were conducted. A vibration wave screening method based on machine learning algorithms was introduced, with decision trees used to filter anomalous data and supervised learning models to identify data damaged by environmental vibration and to obtain representative vibration inputs. Subsequently, vertical vibration analysis was used to examine the influence of structural components, span lengths, and vertical height on vibration propagation and to quickly determine peak vibration locations. The results showed a positive correlation between span length and maximum vibration levels. Slabs are more sensitive to vibration than columns, with higher levels at the center of slabs than at the edges. Additionally, the vibration amplitude increases and then decreases as the vertical height increases. These findings were confirmed by on-site vibration tests and offer insights for sustainable vibration management in metro-adjacent buildings, supporting resilient infrastructure development. The study also provides guidance for selecting vibration measurement points, enhancing human discomfort assessments to reduce health risks and promote socially sustainable communities. Full article

For the first time, the influence of random parametric errors (RPEs) on the nonlinear dynamic behaviors of a laminated composite cantilever beam (LCCB) is studied. A nonlinear dynamic model for the LCCB is first established based on Hamilton’s principle. In a numerical simulation, four different cases are presented to analyze the dynamic behavior of the studied LCCB. This study reveals that varying RPE levels cause significant changes in the dynamic response of the LCCB. The results indicate that RPE not only induces a transition from a periodic to a chaotic behavior but may also alter the maximum amplitude of chaotic vibrations, providing a critical theoretical basis for incorporating uncertainty factors in engineering design. Full article

Vibrotactile stimulation has applications in a variety of fields, including medicine, virtual reality, and human–computer interaction. Eccentric Rotating Mass (ERM) vibrating motors are widely used in wearable haptic devices owing to their small size, low cost, and low-energy features. User experience with vibrotactile stimulation is an important factor in ergonomic design for these applications. The effects of ERM motor vibrations on upper-extremity sensation and perception, which are important in the design of better wearable haptic devices, have not been thoroughly studied previously. Our study focuses on the relationship between user sensation and perception and on different vibration parameters, including frequency, location, and number of motors. We conducted experiments with vibrotactile stimulation on 15 healthy participants while the subjects were both at rest and in motion to capture different use cases of haptic devices. Eight motors were placed on a consistent set of muscles in the subjects’ upper extremities, and one motor was placed on their index fingers. We found a significant correlation between voltage and sensation intensity (r = 0.39). This finding is important in the design and safety of customized haptic devices. However, we did not find a significant aggregate-level correlation with the perceived pleasantness of the simulation. The sensation intensity varied based on the location of the vibration on the upper extremities (with the lowest intensities on the triceps brachii and brachialis) and slightly decreased (5.9 ± 2.9%) when the participants performed reaching movements. When a single motor was vibrating, the participants’ accuracy in identifying the motor without visual feedback increased as the voltage increased, reaching up to 81.4 ± 14.2%. When we stimulated three muscles simultaneously, we found that most participants were able to identify only two out of three vibrating motors (41.7 ± 32.3%). Our findings can help identify stimulation parameters for the ergonomic design of haptic devices. Full article

This study reports on green-synthesized zinc oxide nanoparticles (ZnONPs), focusing on their physicochemical characterization, photocatalytic properties, and agricultural applications. Dynamic light scattering (DLS) analysis revealed a mean hydrodynamic diameter of 337.3 nm and a polydispersity index (PDI) of 0.400, indicating moderate polydispersity and nanoparticle aggregation, typical of biologically synthesized systems. High-resolution transmission electron microscopy (HR-TEM) showed predominantly spherical particles with an average diameter of ~28 nm, exhibiting slight agglomeration. Energy-dispersive X-ray spectroscopy (EDX) confirmed the elemental composition of zinc and oxygen, while X-ray diffraction (XRD) analysis identified a hexagonal wurtzite crystal structure with a dominant (002) plane and an average crystallite size of ~29 nm. Photoluminescence (PL) spectroscopy displayed a distinct near-band-edge emission at ~462 nm and a broad blue–green emission band (430–600 nm) with relatively low intensity. The ultraviolet–visible spectroscopy (UV–Vis) absorption spectrum of the synthesized ZnONPs exhibited a strong absorption peak at 372 nm, and the optical band gap was calculated as 2.67 eV using the Tauc method. Fourier-transform infrared spectroscopy (FTIR) analysis revealed both similarities and distinct differences to the pigeon extract, confirming the successful formation of nanoparticles. A prominent absorption band observed at 455 cm⁻¹ was assigned to Zn–O stretching vibrations. X-ray photoelectron spectroscopy (XPS) analysis showed that raw pigeon droppings contained no Zn signals, while their extract provided organic biomolecules for reduction and stabilization, and it confirmed Zn²⁺ species and Zn–O bonding in the synthesized ZnONPs. Photocatalytic degradation assays demonstrated the efficient removal of pollutants from sewage water, leading to significant reductions in total dissolved solids (TDS), chemical oxygen demand (COD), and total suspended solids (TSS). These results are consistent with reported values for ZnO-based photocatalytic systems, which achieve biochemical oxygen demand (BOD) levels below 2 mg/L and COD values around 11.8 mg/L. Subsequent reuse of treated water for irrigation yielded promising agronomic outcomes. Wheat and barley seeds exhibited 100% germination rates with ZnO NP-treated water, which were markedly higher than those obtained using chlorine-treated effluent (65–68%) and even the control (89–91%). After 21 days, root and shoot lengths under ZnO NP irrigation exceeded those of the control group by 30–50%, indicating enhanced seedling vigor. These findings demonstrate that biosynthesized ZnONPs represent a sustainable and multifunctional solution for wastewater remediation and agricultural enhancement, positioning them as a promising candidate for integration into green technologies that support sustainable urban development. Full article

Vibration monitoring plays a crucial role in assessing the condition and operational safety of electric drive systems. In many industrial applications, scalar control is widely used due to its simplicity and reliability, yet its influence on vibration transmission within interconnected machines remains insufficiently explored. This study addresses the problem of understanding how mechanical vibrations are transmitted between a scalar-controlled induction motor coupled with an AC generator. A comparative experimental investigation was conducted using two different configurations of drive units, incorporating either an induction or a synchronous generator. Vibrations were measured at various operating speeds and analysed using different sensor types to ensure repeatability and reliability of the results. The findings have revealed distinct patterns of vibration transmission between the motor and generator, highlighting the importance of drive system configuration and measurement methodology. A novel approach to data presentation is proposed by normalising vibration levels between machines, offering a clearer interpretation of vibration amplification or damping effects. The results contribute to the development of diagnostic techniques and the optimisation of scalar-controlled drive designs. Full article

This paper investigates the influence of groundwater level fluctuations on the vibration response and isolation performance of saturated soil foundations under moving loads. A coupled model consisting of an overlying elastic layer and a saturated half-space is established, with water level variation simulated by adjusting the elastic layer thickness. Using Biot’s theory and Fourier transforms, the dynamic response is solved analytically and validated numerically via COMSOL6.0 simulations with perfectly matched layers. Results indicate that the groundwater level significantly affects wave propagation: deeper water levels lead to responses resembling an elastic half-space, while rising water levels amplify surface displacement due to wave reflection at the saturation interface. As water levels approach the surface, behavior converges to that of a fully saturated foundation. P-wave resonance at certain water levels reduces isolation effectiveness. Furthermore, isolation performance is sensitive to load frequency, soil permeability, and trench dimensions. These findings offer valuable insights for designing vibration mitigation measures in environments with variable groundwater conditions. Full article

Wiegand sensors are essential components in self-powered Internet of Things (IoT) nodes, as they can output pulse voltages without an external power supply. Previous research has established that the attachment of ferrite beads to Wiegand wire terminals substantially enhances the sensor’s pulse voltage output. However, the fundamental mechanism responsible for this enhancement remains unclear at the microscopic magnetic level. This investigation systematically examines how ferrite bead attachments alter magnetization reversal processes, Barkhausen jump characteristics, and the energy output in Wiegand wires. Experimental results reveal that ferrite beads enhance irreversible magnetization, modify interaction distributions, and transform the magnetic structure of Wiegand wires. These modifications collectively result in a 1.5–2.0 times higher pulse voltage amplitude and 30–40% greater output energy, establishing a theoretical framework for Wiegand sensor optimization. The research methodology combines vibrating sample magnetometer (VSM) measurements with first-order reversal curve (FORC) analysis to elucidate the underlying micromagnetic mechanisms. Full article

This study presents a flutter answer analysis of the Romanian IAR-99 HAWK advanced trainer aircraft equipped with multiple external store configurations. A high-fidelity finite element model (FEM) of the complete aircraft, including pylons and external stores, was coupled with a Doublet Lattice Method (DLM) aerodynamic model. The aeroelastic framework was validated against Ground Vibration Test (GVT) data to ensure structural accuracy. Four representative configurations were assessed: (A) RS-250 drop tanks on inboard pylons and PRN 16 × 57 unguided rocket launchers on outboard pylons; (B) four B-250 bombs; (C) eight B-100 bombs mounted on twin racks; and (D) a hybrid layout with B-100 bombs inboard and PRN 32 × 42 launchers outboard. Results show that spanwise distribution governs aeroelastic stability more strongly than total carried mass. Distributed stores lower wing-bending frequencies and densify the modal spectrum, producing critical pairs and subsonic crossings near M ≈ 0.82 at sea level, whereas compact heavy loads remain subsonic-stable. A launcher-specific modal family around ≈29.8 Hz is also identified in the hybrid layout. The validated FEM–DLM framework captures store-driven mode families (≈4–7 Hz) and provides actionable guidance for payload placement, certification, and modernization of the IAR-99 and similar platforms. Full article

Accurately identifying the load status of a ball mill is critical for optimizing grinding efficiency and ensuring operational stability. However, the one-dimensional vibration signals collected from ball mills exhibit strong non-stationarity and a high degree of entanglement between multi-scale local transient features and long-range temporal evolution patterns. To address this, rather than relying on a purely black-box approach, this paper introduces a novel Deep Multi-scale Spatial–Temporal Feature Decoupling Network (DMSTFD-Net) guided by a clear feature decoupling philosophy to enhance model interpretability. The core of DMSTFD-Net lies in its hierarchical collaborative feature refinement mechanism. It first utilizes a one-dimensional residual network (ResNet) to adaptively capture and preliminarily decouple multi-scale spatial characteristics from the raw signal. Subsequently, the extracted high-level feature sequences are fed into a bidirectional gated recurrent unit (Bi-GRU) to decouple high-order temporal dynamic patterns. Experiments on a multi-condition dataset demonstrate that the proposed network achieves a state-of-the-art accuracy of 97.65%. Furthermore, dedicated cross-condition experiments and t-SNE visualizations validate the framework’s effectiveness. The results confirm that DMSTFD-Net provides a powerful, robust, and more interpretable solution for ball mill load identification. Full article

Understanding the interactions between carbon quantum dots (CDs) and promising food preservatives (FPs), like pyrogallol (PG), benzoic acid (BA), and gallic acid (GA), is highly relevant. This knowledge is crucial for designing CD-based sensors capable of determining the safe levels of these molecules in food and beverages. Additionally, such sensors could be exploited in the development of sustainable, intelligent packaging that controls food shelf life. Based on those considerations, in this study, we post-functionalized blue-emitting CDs, prepared according to a synthetic approach previously developed, with the FP molecules PG, BA, and GA to obtain CD-(FP) systems. UV-vis absorption and FTIR spectroscopy confirmed the presence of the FP molecules on the CD surface. The appearance of a new vibrational band at 1196 cm⁻¹ in the FTIR spectra of all CD-(FP) systems suggested that the three FP molecules interact with the CD surface via electronic interactions between the aromatic and delocalized electron systems. Further electrochemical analyses of the CD-(PG) and CD-(GA) systems show that the interactions between PG and GA benzene rings and CDs prevent their oxidation to the corresponding quinone forms. Full article

Wire-rope isolators (WRIs) are widely used in vibration and seismic protection due to their multidirectional flexibility and amplitude-dependent hysteretic damping. However, their complex nonlinear behavior, especially under inclined and combined-mode loading, poses challenges for predictive modeling. This study presents a simplified finite-element modeling framework using constant-property Timoshenko beam elements with tuned Rayleigh damping to simulate WRI behavior across various configurations. Benchmark validation against analytical ring deformation confirmed the model’s ability to capture geometric nonlinearities. The framework was extended to five WRI types, with effective cross-sectional properties calibrated against vendor-supplied quasi-static data. Dynamic simulations under sinusoidal excitation demonstrated strong agreement with experimental force-displacement loops in pure modes and showed moderate accuracy (within 29%) in inclined configurations. System-level validation using a rocking-control platform with four inclined WRIs showed that the model reliably predicts global stiffness and energy dissipation under base accelerations. While the model does not capture localized nonlinearities such as pinched hysteresis due to interstrand friction, it offers a computationally efficient tool for engineering design. The proposed method enables rapid evaluation of WRI performance in complex scenarios, supporting broader integration into performance-based seismic mitigation strategies. Full article

Motion perception is a fundamental function of the tactile system, essential for object exploration and manipulation. While human studies have largely focused on discrete or pulsed stimuli with staggered onsets, many natural tactile signals are continuous and rhythmically patterned. Here, we investigate whether phase differences between “simultaneously” presented, “continuous” amplitude-modulated vibrations can induce the perception of motion across fingertips. Participants reliably perceived motion direction at modulation frequencies up to 1 Hz, with discrimination performance systematically dependent on the phase lag between vibrations. Critically, trial-level confidence reports revealed the lowest certainty for anti-phase (180°) conditions, consistent with stimulus ambiguity as predicted by the mathematical framework. I propose two candidate computational mechanisms for tactile motion processing. The first is a conventional cross-correlation computation over the envelopes; the second is a probabilistic model based on the uncertain detection of temporal reference points (e.g., envelope peaks) within threshold-defined windows. This model, despite having only a single parameter (uncertainty width determined by an amplitude discrimination threshold), accounts for both the non-linear shape and asymmetries of observed psychometric functions. These results demonstrate that the human tactile system can extract directional information from distributed phase-coded signals in the absence of spatial displacement, revealing a motion perception mechanism that parallels arthropod systems but potentially arises from distinct perceptual constraints. The findings underscore the feasibility of sparse, phase-coded stimulation as a lightweight and reproducible method for conveying motion cues in wearable, motion-capable haptic devices. Full article