Search Results (1,689)

This research explores microcrystalline diamond particles in poly(L-lactic acid) matrices to create structured porous composites for advanced biodegradable materials. While nanodiamond–polymer composites are well-documented, microcrystalline diamond particles remain unexplored for controlling hierarchical porosity in systems required by tissue engineering, thermal management, and filtration industries. We investigate diamond–polymer composites with concentrations from 5 to 75 wt% using freeze-drying methodology, employing two particle sizes: 0.125 μm and 1.00 μm diameter particles. Systematic porosity control ranges from 11.4% to 32.8%, with smaller particles demonstrating reduction from 27.3% at 5 wt% to 11.4% at 75 wt% loading. Characterization through infrared spectroscopy, X-ray computed microtomography, and Raman analysis confirms purely physical diamond–polymer interactions without chemical bonding, validated by characteristic diamond lattice vibrations at 1332 cm⁻¹. Thermal analysis reveals modified crystallization behavior with decreased melting temperatures from 180 to 181 °C to 172 °C. The investigation demonstrates a controllable transition from large-volume interconnected pores to numerous small-volume closed pores with increasing diamond content. These composites provide a quantitative framework for designing hierarchical structures applicable to tissue engineering scaffolds, thermal management systems, and specialized filtration technologies requiring biodegradable materials with engineered porosity and enhanced thermal conductivity. Full article

With the rapid progress of industrial technology in recent years, servo controllers have the characteristics of precise control and short response time and are widely used in different industrial fields. As for the electro-hydraulic servo valve being an important control element of the entire hydraulic system, the quality of its own characteristics has a significant impact on the normal operation and safety of the mechanical equipment. Therefore, the working stability of the servo valve in actual operation is of great importance to its body and the overall servo system. Similarly, during the vibration test of the electro-hydraulic servo shaking table, servo valve inevitably experiences various vibrations and shocks, which requires the servo system to be able to withstand the test and assessment under the extreme conditions in actual operation to ensure the smooth operation. This paper takes function of the shaker as the research target and studies the servo valve under various vibration conditions by constructing a digital modeling system. On this basis, an adaptive format filter is established, and corresponding vibration suppression methods are adopted for the vibration conditions inside the system. Finally, simulation examples are used to prove that this method can more effectively control the vibration in the servo valve and suppress the interference with shaking table function. Full article

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

The development of a multifunctional invention requires several refinements for optimizing each function. This study presents a Theory of Inventive Problem Solving (TRIZ)-based conceptual framework for enhancing an innovative multifunctional assistive technology device that integrates the functionalities of a rollator walker, wheelchair, Pilates chair, and stepladder. The limitations of the multifunctional rollator walker were identified from the user feedback of a foundational work and were then addressed by identifying the engineering and physical contradictions and problem modeling using Su-field analysis. Through TRIZ Inventive Principles, the proposed design eliminates common trade-offs between portability, stability, and usability. The conceptual enhancement incorporates features such as deployable steps, the utilization of high strength–to–weight ratio material, foldability, a passive mechanical brake-locking system, retractable armrests, the incorporation of spring-assist hinges, and the use of large tires with vibration-dampening hubs. This study contributes a novel, user-focused, and space-saving mobility solution that aligns with the evolving demands of assistive technology, laying the groundwork for future iterations involving smart control, power assist, and modular enhancements. 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

The accurate estimation of parameters in dynamical systems stands for an open key research issue in modeling, control, and fault diagnosis. The presence of noise in input and output signals poses a serious challenge for accurate real-time dynamical system parameter estimation. This paper proposes a new robust algebraic parameter estimation methodology for integer-order dynamical systems that explicitly incorporates the signal filtering dynamics within the estimator structure and enhances noise attenuation through fractional differentiation in frequency domain. The introduced estimation methodology is valid for Liouville-type fractional derivatives and can be applied to estimate online the parameters of differentially flat, oscillating or vibrating systems of multiple degrees of freedom. The parametric estimation can be thus implemented for a wide class of oscillating or vibrating, nth-order dynamical systems under noise influence in measurement and control signals. Positive values are considered for the inertia, stiffness, and viscous damping parameters of vibrating systems. Parameter identification can be also used for development of actuators and control technology. In this sense, validation of the algebraic parameter estimation is performed to identify parameters of a differentially flat, permanent-magnet direct-current motor actuator. Parameter estimation for both open-loop and closed-loop control scenarios using experimental data is examined. Experimental results demonstrate that the new parameter estimation methodology combining signal filtering dynamics and fractional calculus outperforms other conventional methods under presence of significant noise in measurements. Full article

This paper presents a systematic review of vibration sensors and their application in industrial-monitoring systems, aiming to provide a comprehensive reference for both academic research and practical applications in this field. Through the classification of measured parameters and sensing principles, this work endeavors to establish a structured understanding of vibration sensor’s working mechanism and deliver an in-depth analysis of their recent research achievements. By integrating practical cases from typical domains, this manuscript comprehensively demonstrates the practical value and application potential of vibration sensors in equipment-monitoring systems, illustrating how these sensors are utilized to detect mechanical failures and enhance the performance and safety of industrial systems, such as wind turbine, tunnel boring machine, and aerospace engine. Looking forward, with the rapid advancement of the Internet of Things (IoT) and artificial intelligence (AI) technologies, vibration sensors are anticipated to evolve towards multifunctionalization, miniaturization and intelligentization, thereby forming a comprehensive monitoring network that improves overall efficiency and reliability of the mechanical systems. Full article

Deep hole structures are widely used in the fields of aerospace, engineering machinery, marine, etc. During the deep hole machining processes, especially for boring procedures, the vibration phenomenon caused by the large aspect ratio of boring tools seriously restricts the machining accuracy and production efficiency. Therefore, extensive research has been devoted to the design and development of damped boring tools with different structures to suppress machining vibration. According to varied vibration reduction technologies, the damped boring tools can be divided into active and passive categories. This paper systematically reviews the advancements of vibration reduction principles, structure design, and practical applications of typical active and passive damped boring tools. Active damped boring tools rely on the synergistic action of sensors, actuators, and control systems, which can monitor vibration signals in real-time during the machining process and achieve dynamic vibration suppression through feedback adjustment. Their advantages include strong adaptability and wide adjustment capability for different machining conditions, including precision machining scenarios. Comparatively, vibration-absorbing units, such as mass dampers and viscoelastic materials, are integrated into the boring bars for passive damped tools, while an energy dissipation mechanism is utilized with the aid of boring tool structures to suppress vibration. Their advantages include simple structure, low manufacturing cost, and independence from an external energy supply. Furthermore, the potential development directions of vibration damped boring bars are discussed. With the development of intelligent manufacturing technologies, the multifunctional integration of damped boring tools has become a research hotspot. Future research will focus more on the development of an intelligent boring tool system to further improve the processing efficiency of deep hole structures with difficult-to-machine materials. Full article

The concept behind this undertaking was to create environmentally friendly and sustainable air-conditioning systems supported by energy storage units, as well as to conduct comparative calculations of investment and operational costs to assess their economic viability. In order to meet sustainability requirements, detailed analysis was followed by a decision to utilise cold storage units in which energy is stored through the phase change of water into ice. Aiming to achieve high efficiency, strong reliability and enhanced operational dynamics, a multi-circuit model for coolant flow was developed, incorporating a variable-speed compressor drive. High functionality and performance were attained through the introduction of container vibrations, which resulted in the formation of ice slurry particles in spherical containers placed within an aqueous glycol solution serving as the heat exchange medium. The concept of this technology, along with its accompanying mathematical models, was validated, and the results of this work are presented in the article. To evaluate the competitiveness of air-conditioning systems, the developed solution based on cold storage technology is compared with a lithium-ion battery system and a conventional configuration powered directly by the grid. The results demonstrate that the cold-storage-based air-conditioning system outperforms both reference systems in terms of energy efficiency. An analysis of the full operational cycle indicates that the proposed solution consumes significantly less energy than systems using lithium-ion battery storage. The investment costs are almost twenty percent lower, while service, maintenance and disposal expenses are negligible. These attributes make it a competitive solution that is both economically and environmentally sustainable. In summary, the proposed technology fully satisfies the key principles of sustainability. It does not deplete natural resources, minimises the environmental impact, offers long-term reliability and contributes to lower energy bills and more responsible resource use. Full article

Considering the growing demand for modern facility agriculture, it is essential to develop non-destructive technologies for assessing lettuce nutritional status. To overcome the limitations of traditional methods, which are destructive and time-consuming, this study proposes a multimodal non-destructive nitrogen detection method for lettuce based on multi-source imaging. The approach integrates terahertz time-domain spectroscopy (THz-TDS) and near-infrared hyperspectral imaging (NIR-HSI) to achieve rapid and non-invasive nitrogen detection. Spectral imaging data of lettuce samples under different nitrogen gradients (20–150%) were simultaneously acquired using a THz-TDS system (0.2–1.2 THz) and a NIR-HSI system (1000–1600 nm), with image segmentation applied to remove background interference. During data processing, Savitzky–Golay smoothing, MSC (for THz data), and SNV (for NIR data) were employed for combined preprocessing, and sample partitioning was performed using the SPXY algorithm. Subsequently, SCARS/iPLS/IRIV algorithms were applied for THz feature selection, while RF/SPA/ICO methods were used for NIR feature screening, followed by nitrogen content prediction modeling with LS-SVM and KELM. Furthermore, small-sample learning was utilized to fuse crop feature information from the two modalities, providing a more comprehensive and effective detection strategy. The results demonstrated that the THz-based model with SCARS-selected power spectrum features and an RBF-kernel LS-SVM achieved the best predictive performance (R² = 0.96, RMSE = 0.20), while the NIR-based model with ICO features and an RBF-kernel LS-SVM achieved the highest accuracy (R² = 0.967, RMSE = 0.193). The fusion model, combining SCARS and ICO features, exhibited the best overall performance, with training accuracy of 96.25% and prediction accuracy of 95.94%. This dual-spectral technique leverages the complementary responses of nitrogen in molecular vibrations (THz) and organic chemical bonds (NIR), significantly enhancing model performance. To the best of our knowledge, this is the first study to realize the synergistic application of THz and NIR spectroscopy in nitrogen detection of facility-grown lettuce, providing a high-precision, non-destructive solution for rapid crop nutrition diagnosis. Full article

The influence of axial ultrasonic vibration (the dominant vibration mode) on the filling behavior of polymer melt in microcavities and its effect on microstructure formation remains inadequately understood. Based on the plasticization location and the extent to which the microcavity is covered by the ultrasonic sonotrode action surface, existing ultrasonic plasticization molding technologies were classified into three types—ultrasonic pressing (UP), ultrasonic plasticizing and pressing (UPP), and ultrasonic plasticization injection molding (UPIM). The effects of these configurations on melt fluidity and filling performance were evaluated and compared through slit flow tests. The interaction mechanisms between polymer melts and templates were elucidated based on melt pressure measurements and morphological changes in nickel micropillar arrays and silicon templates after molding. The results indicated that polymer melt exhibits improved flow behavior within microcavities when under the coverage area of the ultrasonic sonotrode action surface and subjected to the axial ultrasonic vibration. Continuous ultrasonic vibration contributed to sustaining melt fluidity during micropore filling. Among the three technologies, the most complex and intense mechanical interactions on the template microstructure were observed in UP, followed by UPP and then UPIM. Full article

Efficient production of high-quality cubical crushed stone is critical for road construction and concrete manufacturing. Conventional vibrating screens suffer from low cubicality and high energy consumption, limiting their applicability. We developed a novel spiral vibrating screen featuring a helical screening surface and adjustable oscillation parameters. Experimental studies were conducted on granite aggregates (5–20 mm) at vibration frequencies of 16–26 Hz and amplitudes of 1.5–4.0 mm to evaluate cubicality, screening efficiency, throughput, and energy consumption. Under optimal operating conditions (22 Hz, 3.0 mm amplitude), the prototype achieved 84–86% cubical particles, 93–95% screening efficiency, and specific energy consumption of 1.20 ± 0.05 kWh/t. Compared with conventional flat and drum screens, cubicality improved by 8–12 percentage points, while energy consumption decreased by up to 12%. The developed screen offers a scalable solution for producing high-quality cubical aggregates with lower energy demand and reduced clogging risks. These findings provide practical guidance for improving aggregate processing technologies. Full article

The overlying rock layers in a mining area may collapse or settle, subjecting pipelines to uneven forces that can lead to deformation or even fracture. This paper proposes a pipeline safety monitoring method that combines fiberoptic vibration and strain sensing to detect vibrations and deformations caused by rock layer collapse in mining zones. First, pipeline deformation monitoring under unknown force directions was investigated using fiber Bragg grating (FBG) sensing technology. Second, we constructed a mining area pipeline model and conducted vibration/deformation monitoring tests employing FBG sensors, distributed Brillouin strain sensing, and distributed fiberoptic vibration sensing technologies. The experimental results demonstrate that FBG sensor arrays deployed at 90-degree intervals can effectively identify the pipeline’s primary force direction and maximum strain, with direction angle errors of less than 5.2%. The integrated analysis of vibration and strain data enables accurate identification and measurement of extended vibration responses and pipeline deformations in open-air zones. This study establishes a comprehensive monitoring framework for ensuring pipeline safety in mining areas. Full article

Ultrasonic welding is an efficient and precise joining technology widely applied in aerospace, electronics, and medical industries. To overcome the limitations of conventional oscillators in high-frequency applications, this study proposes an innovative cylindrical oscillator design incorporating a 3.71 mm acoustic matching layer, operating at 1.76 MHz based on acoustic propagation theory. Through finite element analysis, a miniaturized oscillator with dimensions of 28 mm in diameter and 18 mm in height was developed, achieving optimized dynamic performance. Experimental validation via laser Doppler vibrometry confirmed a working surface amplitude exceeding 50 nm, while vibrations on non-functional walls were suppressed below 5 nm, with less than 5% deviation from simulation results. Prototype welding tests identified optimal process parameters—85 N welding pressure, 4 s welding time, and 3 s holding time—resulting in PVC joint tensile strengths exceeding 45 N. This work provides both an optimized hardware design and validated process guidelines, advancing the application of high-frequency micro-ultrasonic welding in precision, space-constrained environments. Full article

Electric vehicle (EV) drivetrains operate at high rotational speeds, which makes the noise, vibration, and harshness (NVH) performance of gear transmissions a critical design factor. Without the masking effect of an internal combustion engine, gear whine can become a prominent source of passenger discomfort. This paper provides the first comprehensive review focused specifically on gear tooth surface waviness, a subtle manufacturing-induced deviation that can excite tonal noise. Periodic, micron-scale undulations caused by finishing processes such as grinding may generate non-meshing frequency “ghost orders,” leading to tonal complaints even in high-quality gears. The article compares finishing technologies including honing and superfinishing, showing their influence on waviness and acoustic behavior. It also summarizes modern waviness detection techniques, from single-flank rolling tests to optical scanning systems, and highlights data-driven predictive approaches using machine learning. Industrial case studies illustrate the practical challenges of managing waviness, while recent proposals such as controlled surface texturing are also discussed. The review identifies gaps in current research: (i) the lack of standardized waviness metrics for consistent comparison across studies; (ii) the limited validation of digital twin approaches against measured data; and (iii) the insufficient integration of machine learning with physics-based models. Addressing these gaps will be essential for linking surface finish specifications with NVH performance, reducing development costs, and improving passenger comfort in EV transmissions. Full article