Search Results (141)

The pressure response and structural stability of fluoranthene crystals up to 8 GPa are investigated using Raman spectroscopy. The vast majority of the Raman peaks upshift with pressure, either sublinearly (intermolecular modes) or quasilinearly (intramolecular modes), reflecting the bond hardening upon volume contraction. The frequency shifts, accompanied by intensity redistribution among the Raman peaks, are by far larger for the former than those for the latter vibrations, compatible with their nature: weak intermolecular van der Waals interactions and strong intramolecular covalent bonds. For pressures higher than 2 GPa, changes in the linear pressure coefficients of the Raman peak frequencies, mainly towards lower values, are observed. These are more pronounced for intermolecular and C–H stretching vibrations. For P > 4.7 GPa, the pressure coefficients are further reduced, while all the observed pressure-induced changes are fully reversible upon pressure release. These changes may be interpreted either as two structural transitions at ~2 and ~4.7 GPa or as a single, but sluggish, structural phase transition in the pressure range 2–4.7 GPa, featuring the reorientation and different stacking of the molecules. From the high-pressure Raman data in the low-pressure phase, a bulk modulus of ~7 GPa at ambient pressure is estimated for solid fluoranthene. Full article

It is well known that aqueous solutions can emit electromagnetic waves in the radio frequency range. However, the physical nature of this process is not yet fully understood. In this work, the possible role of gas nanobubbles formed in the bulk liquid is considered. We develop a theoretical model based on the concept of gas bubbles stabilized by ions, or “bubstons”. The role of bicarbonate and hydronium ions in the formation and stabilization of bubstons is explained through the use of quantum chemical simulations. A new model of oscillating bubstons, which takes into account the double electric layer formed around their gas core, is proposed. Theoretical estimates of the frequencies and intensities of oscillations of such compound species are obtained. It was determined that oscillations of negatively charged bubstons can occur in the GHz frequency range, and should be accompanied by the emission of electromagnetic waves. To validate the theoretical assumptions, we used dynamic light scattering (DLS) and showed that, after subjecting aqueous solutions to vigorous shaking with a force of 4 or 8 N (kg·m/s²) and a frequency of 4–5 Hz, the volume number density of bubstons increased by about two orders of magnitude. Radiometric measurements in the frequency range of 50 MHz to 3.5 GHz revealed an increase in the intensity of radiation emitted by water samples upon the vibrational treatment. It is argued that, according to our new theoretical model, this radiation can be caused by oscillating bubstons. Full article

This study reported covalent organic frameworks (COFs) and their hybrid composites with two-dimensional materials, graphene oxide (GO), graphitic carbon nitride (g-C₃N₄), and boron nitride (BN), to examine their structural, textural, and gas adsorption properties. Material characterization confirmed the crystallinity of COF-1 and the preservation of framework integrity after integrating the 2D nanomaterials. FT-IR spectra exhibited pronounced vibrational fingerprints of imine linkages and validated the functional groups from the COF and the integrated nanomaterials. TEM images revealed the integration of the two components, porous, layered structures with indications of interfacial interactions between COF and 2D nanosheets. Nitrogen adsorption–desorption isotherms revealed the microporous characteristics of the COFs, with hysteresis loops evident, indicating the development of supplementary mesopores at the interface between COF-1 and the 2D materials. The BET surface area of pristine COF-1 was maximal at 437 m²/g, accompanied by significant micropore and Langmuir surface areas of 348 and 1290 m²/g, respectively, offering enhanced average pore widths and hierarchical porous strcuture. CO₂ adsorption tests were investigated showing maximum adsorption capacitiy of 1.47 mmol/g, for COF-1, closely followed by COF@BN at 1.40 mmol/g, underscoring the preserved sorption capabilities of these materials. These findings demonstrate the promise of designed COF-based hybrids for gas capture, separation, and environmental remediation applications. Full article

The increasing demands for the reliability of modern industrial equipment and structures necessitate advanced techniques for design, monitoring, and analysis. This review article presents the latest research advancements in the application of machine learning techniques to vibration and acoustic signal analysis from 2015 to 2024. A total of 96 peer-reviewed scientific publications were examined, selected using a systematic Scopus-based search. The main research areas include processes such as modeling and design, health management, condition monitoring, non-destructive testing, damage detection, and diagnostics. In the context of these processes, a review of machine learning techniques was conducted, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), long short-term memory (LSTM), autoencoders, support vector machines (SVMs), decision trees (DTs), nearest neighbor search (NNS), K-means clustering, and random forests. These techniques were applied across a wide range of engineering domains, including civil infrastructure, transportation systems, energy installations, and rotating machinery. Additionally, this article analyzes contributions from different countries, highlighting temporal and methodological trends in this field. The findings indicate a clear shift towards deep learning-based methods and multisensor data fusion, accompanied by increasing use of automatic feature extraction and interest in transfer learning, few-shot learning, and unsupervised approaches. This review aims to provide a comprehensive understanding of the current state and future directions of machine learning applications in vibration and acoustics, outlining the field’s evolution and identifying its key research challenges and innovation trajectories. Full article

Xanthones are a group of polyphenolic compounds widely known to have antitumor, anti-inflammatory, antibacterial, antifungal, antiviral, and antioxidant properties. To fully utilize their therapeutic potential, this study aimed to enhance the solubility of a poorly soluble xanthone by preparing a 1:1 molar ratio of xanthone–urea complex utilizing a cogrinding method via a vibration rod mill. DSC analysis revealed the disappearance of the characteristic endothermic peaks of xanthone (177 °C) and urea (136 °C) in the ground mixture (GM), along with the appearance of a new endothermic peak at 185 °C, indicating potential complexation. Additionally, new peaks were observed in the PXRD patterns of the GM at 9.1°, 12.0°, 14.0°, 18.6°, 19.6°, and 24.6°, suggesting structural changes that were also observed in SEM morphology. FTIR spectroscopy revealed significant shifts in the -NH and C=O peaks of xanthone and urea, as well as the disappearance of a -CN peak. Altered diffusion coefficients for both xanthone and urea were measured using DOSY-NMR, accompanied by notable improvements in solubility and dissolution profiles. The GM exhibited nearly a 2-fold increase in solubility, reaching 88.08 ± 1.25 µg/mL at 24 h and 90.97 ± 0.98 µg/mL at 72 h, alongside a 2-fold and 5-fold increase in dissolution at 0.21 µg/mL and 0.51 µg/mL for the physical mixture (PM) and GM, respectively. Furthermore, an enhanced antioxidant capacity was observed, as demonstrated in the calculated Trolox equivalent (TE) value, which increased from 1.48 ± 1.12 for xanthone alone to 1.65 ± 1.03 in the xanthone–urea complex. These findings confirm the successful complexation of xanthone and urea in a 1:1 molar ratio. Full article

This research focuses on creating CuO/PANI nanocomposite films by electrodepositing copper oxide nanoparticles into a polyaniline matrix on ITO substrates. The CuO nanoparticle content was adjusted between 7% and 21%. These nanocomposites are promising for various applications, such as optoelectronic devices, gas sensors, electromagnetic interference shielding, and electrochromic devices. We utilized UV-Vis spectroscopy to examine the nanocomposites’ interaction with light, allowing us to ascertain their refractive indices and absorption coefficients. The Scherrer formula facilitated the determination of the average crystallite size, shedding light on the material’s internal structure. Tauc plots indicated a reduction in the energy-band gap from 3.36 eV to 3.12 eV as the concentration of CuO nanoparticles within the PANI matrix increased, accompanied by a rise in electrical conductivity. The incorporation of CuO nanoparticles into the polyaniline matrix appears to enhance the conjugation length of PANI chains, as evidenced by shifts in the quinoid and benzenoid ring vibrations in FTIR spectra. SEM analysis indicates that the nanocomposite films possess a relatively smooth and homogeneous surface. Additionally, FTIR and XRD analyses demonstrate an increasing degree of interaction between CuO nanoparticles and PANI chains with higher CuO concentrations. At lower concentrations, interactions were minimal. In contrast, at higher concentrations, more significant interactions were observed, which facilitated the stretching of polymer chains, improved molecular packing, and facilitated the formation of larger crystalline structures within the PANI matrix. The incorporation of CuO nanoparticles resulted in nanocomposites with electrical conductivities ranging from 1.2 to 17.0 S cm⁻¹, which are favorable for optimum performance in optoelectronic devices. These results confirm that the nanocomposite films combine pronounced crystallinity, markedly enhanced electrical conductivity, and tunable band-gap energies, positioning them as versatile candidates for next-generation optoelectronic devices. Full article

High-entropy alloys (HEAs) exhibit excellent properties such as high strength, good ductility, superior corrosion resistance, and thermal stability, making them highly promising for applications in the aerospace, energy, and automotive industries. Among them, the FeNiCrMn HEA demonstrates outstanding corrosion resistance while eliminating the expensive Co element present in the “Cantor” alloy, significantly reducing costs. However, current research on the FeNiCrMn HEA has primarily focused on its corrosion resistance, with relatively limited studies on its mechanical properties. This paper investigated the effects of different crystal orientations, temperatures, and strain rates on the mechanical properties and plastic deformation mechanisms of an equiatomic FeNiCrMn HEA using molecular dynamics simulations. The results revealed that the FeNiCrMn HEA exhibited significant anisotropy under loading along different orientations, with the maximum yield stress observed along the <11-1> direction. During the elastic stage, all crystals maintained a single FCC structure. As strain increased, yielding occurred, accompanied by a sudden drop in stress, which was attributed to the generation of dislocations. The mechanical properties of the FeNiCrMn HEA were highly sensitive to temperature variations. Elevated temperatures intensify atomic thermal vibrations, making it easier for atoms to deviate from their equilibrium positions and facilitating dislocation nucleation and movement. Consequently, the yield strength and yield strain decreased with increasing temperature. In contrast, the yield strength of the FeNiCrMn HEA was relatively insensitive to strain rate variations. Instead, the strain rate primarily affected the alloy’s flow stress. During tensile loading, higher strain rates led to higher dislocation densities. When the stress stabilized, the flow stress increased with the strain rate. These findings provide a theoretical foundation for the future development of FeNiCrMn HEAs. Full article

Based on first-principles calculations, the stability of three adsorption configurations of glycine on the (100) surface of diamonds was studied, leading to an investigation into the surface-enhanced Raman scattering (SERS) effect of the diamond substrate. The results showed that the carboxyl-terminated adsorption configuration (CAR) was the most stable and shortest interface distance compared to other configurations. This stability was primarily attributed to the formation of strong polar covalent bonds between the carboxyl O atoms and the surface C atoms of the (100) surface of diamonds. These results were further corroborated by first-principles molecular dynamics simulations. Within the temperature range of 300 to 500 K, the glycine molecules in the carboxyl-terminated adjacent-dimer phenyl-like (CAR) configuration exhibited only simple thermal vibrations with varying amplitudes. In contrast, the metastable ATO and carboxyl-terminated trans-dimer phenyl-like ring (CTR) configurations were observed to gradually transform into benzene-ring-like structures akin to the CAR configuration. After adsorption, the intensity of glycine’s characteristic peaks increased substantially, accompanied by a blue shift phenomenon. Notably, the characteristic peaks related to the carboxyl and amino groups exhibited the highest enhancement amplitude, exceeding 200 times, with an average enhancement amplitude exceeding 50 times. The diamond substrate, with its excellent adsorption properties and strong surface Raman spectroscopy characteristics, represents a highly promising candidate in the field of biomedicine. Full article

Hydrodynamic noise is induced by hydrodynamic phenomena, such as pressure fluctuations, shear layers, and eddy currents, which have a significant impact on ship performance, pumping equipment efficiency, detection accuracy, and the living environment of marine organisms. Specifically, hydrodynamic noise increases fluid resistance around the hull, reduces speed and fuel efficiency, and affects the stealthiness of military vessels; whereas, in pumping equipment, noise generation is usually accompanied by energy loss and mechanical vibration, resulting in reduced efficiency and accelerated wear and tear of the equipment. Traditional physical experiments, theoretical modeling, and numerical simulation methods occupy a key position in hydrodynamic noise research, but each have their own limitations: physical experiments are limited by experimental conditions, which make it difficult to comprehensively reproduce the characteristics of the complex flow field; theoretical modeling appears to be simplified and idealized to cope with the multiscale noise mechanism; and numerical simulation methods, although accurate, are deficient in the sense that they are computationally expensive and difficult to adapt to complex boundary conditions. In recent years, intelligent algorithms represented by data-driven algorithms and heuristic algorithms have gradually emerged, showing great potential for development in hydrodynamic noise optimization applications. To this end, this paper systematically reviews progress in the application of intelligent algorithms in hydrodynamic noise research, focusing on their advantages in the optimal design of noise sources, noise prediction, and control strategy optimization. Meanwhile, this paper analyzes the problems of data scarcity, computational efficiency, and model interpretability faced in the current research, and looks forward to the possible improvements brought by hybrid methods, including physical information neural networks, in future research directions. It is hoped that this review can provide useful references for theoretical research and practical engineering applications involving hydrodynamic noise, and point the way toward further exploration in related fields. Full article

Layered orthorhombic single crystals of EuYCuTe₃ are synthesized using the ampoule method from the elemental precursors taken in the ratio of 1 Eu:1 Y:1 Cu:3 Te by heating up to 1120 K with an excess of CsI as flux. The orthorhombic structure of EuYCuTe₃ is established, and structural parameters are obtained using X-ray diffraction. At ambient conditions, the sample crystallizes in the space group Pnma with the unit cell parameters a = 11.2730(7) Å, b = 4.3214(3) Å, c = 14.3271(9) Å. The structure is composed of vertex-connected [CuTe₄]⁷⁻ tetrahedra, which form chains along the [010] direction, and of edge-connected [YTe₆]⁹⁻ octahedra, which form layers parallel to the (010) plane. The Eu²⁺ cations are found in a capped trigonal prismatic coordination of Te²⁻ anions. The structural phase transition from the α to the β phase is discovered upon heating the sample to 323 K, which comes accompanied with a decrease of [CuTe₄]⁷⁻ tetrahedral distortion. The symmetry of the high-temperature phase is established as ordered in the space group Cmcm (a = 4.3231(3) Å, b = 14.3328(9) Å, c = 11.2843(7) Å). The nature and microscopic mechanism of the phase transition is discussed. By cooling it down below 3 K, the soft ferromagnetic properties of EuYCuTe₃ are discovered. The correlation of the ferromagnetic transition temperature in the series of chalcogenides EuYCuCh₃ (Ch = S, Se, Te) with the ionic radius of the chalcogenide anion is established. The structural dynamical elastic properties of α- and β-EuYCuTe₃ were calculated within the ab initio approach. The vibrational mode frequencies and decomposition on irreducible representations, as well as the degree of ion involvement in each mode, were determined. The calculations reveal an imaginary mode in the Y-point of the Brillouin zone in the high symmetry β-EuYCuTe₃ phase. This finding explains the nature of structural reconstruction in EuYCuTe₃ crystal as a second-order phase transition induced by soft mode condensation at the edge of the Brillouin zone. The exfoliation of a single layer is simulated theoretically. The exfoliation energy is estimated, and the dynamical properties of EuYCuTe₃ single layers are studied. Full article

Synchronous vibrations, which are caused by periodic excitations, can have a severe impact on the service life of impellers. Blade Tip Timing (BTT) is a promising technique for monitoring synchronous vibrations due to its non-intrusive nature and ability to monitor all blades at once. BTT generally employs a Once-per-Revolution (OPR) sensor that is mounted on the shaft for blade identification and deflection calculation. Nevertheless, OPR sensors can be unreliable, as they may be affected by shaft vibrations, and their implementation can be restricted by space constraints. Moreover, the low number of BTT sensors typically leads to under-sampled deflection signals, which consequently hinders the estimation of the vibration frequencies due to aliasing problems. For this reason, BTT is commonly accompanied by strain gauge (SG) measurements on some blades. In this paper, improved BTT techniques are presented, which enable the determination of vibration properties of synchronous vibrations without the need for an OPR sensor and ensure a reliable frequency assessment. Specifically, the blades are identified by unique characteristics resulting from manufacturing tolerances, while the blade deflections are calculated through a novel method, which relies on the impeller’s circumferential position. The proposed method enables accurate OPR-free calculation of blade deflections, by accounting for speed variations within a revolution and considering the actual blade positions on the impeller. By completely eliminating the need for an OPR sensor, the accuracy of BTT is enhanced, as the blade deflections are no longer affected by shaft vibrations, while speed variations within a revolution can be accounted for. Moreover, the implementation possibilities of BTT are improved, allowing its application in systems, where an OPR sensor cannot be instrumented due to space constraints. Subsequently, the vibration frequencies are accurately estimated, by employing an improved Multi-Sampling method based on Non-Uniform Fast Fourier Transform. This approach enables the blind analysis of BTT measurements and can identify multiple vibration frequencies. The proposed method expands the capabilities of BTT through a reliable assessment of vibration frequencies from under-sampled BTT signals. Therefore, it is no longer necessary to accompany BTT measurements with SG measurements for frequency identification. Finally, the vibration properties are determined using regression models. The proposed BTT techniques are validated through comparison with SG measurements as well as a commercial BTT system, using experimental data from a test bench of a turbocharger used for marine applications. The vibrations were recorded under real operating conditions, thus demonstrating the industrial applicability of the proposed BTT evaluation procedure. Full article

In mechanical engineering, the building industry, and many other branches of industry, vibration machines are widely used, in which circular and directed oscillations predominate in the form of movement of the working equipment. This article examines methods for generating asymmetric oscillations, which are estimated by a numerical parameter, namely by the coefficient of asymmetry of the magnitude of the driving force when changing the direction of action in a directed motion within each period of oscillations. It is shown that for generating asymmetric mechanical vibrations, vibration devices are used, consisting of vibrators of directed vibrations, called stages. These stages form the total asymmetric driving force. The behavior of the total driving force of asymmetric vibrations and the working equipment of the vibration machine are described by analytical equations, which represent certain laws of motion of the mechanical system. This article presents a numerical analysis of methods for obtaining laws of motion for a two-stage, three-stage, and four-stage vibration device with asymmetric oscillations. An analysis of the methodology for obtaining a generalized law of motion for a vibration device with asymmetric oscillations is performed based on the application of polyharmonic oscillation synthesis methods. It is shown that the method of forming the total driving force of a vibration device based on the coefficients of the terms of the Fourier series has limited capabilities. This article develops, substantiates, and presents a generalized method for calculating and designing a vibration device with asymmetric oscillations by the value of the total driving force and a given value of the asymmetry coefficient in a wide range of rational designs of vibration machines. The proposed method is accompanied by a numerical example for a vibration device with an asymmetry coefficient of the total driving force equal to 10. Full article

To address the vulnerability of rolling bearings to noise interference in industrial settings, along with the problems of weak noise resilience and inadequate generalization in conventional residual network frameworks, this study introduces an adaptive denoising residual network (AD-ResNet) for diagnosing rolling bearing faults. Initially, the sensors collect the bearing vibration signals, which are then converted into two-dimensional grayscale images through the application of a continuous wavelet transform. Then, a spatial adaptive denoising network (SADNet) architecture is incorporated to comprehensively extract multi-scale information from noisy images. By exploiting the improved pyramid squeeze attention (IPSA) module, which excels in extracting representative features from channel attention vectors, this unit substitutes the standard convolutional layers present in typical residual networks. Ultimately, this model was validated through experiments using publicly available bearing datasets from CWRU and HUST. The findings suggest that with −6 dB Gaussian white noise, the average accuracy of recognition achieves a rate of 90.96%. In scenarios of fluctuating speeds accompanied by strong noise, the recognition accuracy can reach 89.54%, while the training time per cycle averages merely 3.65 s. When compared to other widely utilized fault diagnosis techniques, the approach described in this paper exhibits enhanced noise resistance and better generalization capabilities. Full article

Vibration signal analysis, which aims to monitor and assess the operational status of mechanical systems in real time, has proven to be an effective method for fault diagnosis. As a crucial component of hoisting equipment, the identification of fault signals in rolling bearings is of paramount importance. However, in practical industrial applications, fault diagnosis often fails to achieve satisfactory results. The challenges stem from the fact that vibration signals generated during the operation of rolling bearings are often accompanied by complex noise, which significantly impairs the accurate identification of fault characteristics. To address this issue, a multi-path information fusion fault diagnosis network (MPIFNet) has been proposed for rolling bearings. Specifically, a time series two-dimensional transformation module is introduced to extract key periodic features from the time series signals, thereby extending the original one-dimensional signal into two-dimensional space. Additionally, the multi-path time series extractor is designed to represent multi-scale features. Experimental results demonstrate the superiority of the proposed method, achieving state-of-the-art performance on a public dataset. The potential extends beyond academic applications, offering significant benefits for industrial settings, including cost savings, improved operational efficiency, and enhanced safety by minimizing the risk of unexpected failures in critical machinery. Full article

We report absolute high-resolution vacuum ultraviolet (VUV) photoabsorption cross-sections of carbon tetrachloride (CCl₄) in the photon energy range 5.0–10.8 eV (248–115 nm). The molecular spectrum and electronic structure have been comprehensively investigated together with quantum chemical calculations, providing geometries, bond lengths, vertical excitation energies and oscillator strengths. The major electronic excitations have been assigned to valence and Rydberg transitions which are also accompanied by vibrational excitation assigned to degenerate stretching, $v_3^{\prime }\left(t_2\right)$ and degenerate deformation $v_4^{\prime }\left(t_2\right)$ modes. The rather complex nuclear dynamics along the degenerate deformation mode, $v_4^{\prime }\left(t_2\right)$, have been thoroughly investigated by Time-Dependent Density Functional Theory (TD-DFT) method. The relevant Jahn–Teller distortion operative within the lowest-lying electronic excited-state is shown here for the first time in order to yield a weak absorption feature at 6.156 eV. Further calculations on the potential energy curves for the singlet excited-states along the C–Cl stretching coordinate show the relevance of efficient C–Cl bond excision. Full article