Search Results (656)

The fatigue constitutive model under cyclic loading is of vital importance for studying the fatigue deformation characteristics of soft rocks. In this paper, based on the classical Bingham model, a modified Bingham fatigue model for describing the fatigue deformation characteristics of soft rocks under cyclic loading was developed. Firstly, the traditional constant-viscosity component was replaced by an improved nonlinear viscoelastic component related to the number of cycles. The elastic component was replaced by an improved nonlinear elastic component that decays as the number of cycle loads increases. Meanwhile, by decomposing the cyclic dynamic loads into static loads and alternating loads, a one-dimensional nonlinear viscoelastic-plastic Bingham fatigue model was developed. Furthermore, a rock fatigue yield criterion was proposed, and by using an associated flow rule compatible with this criterion, the one-dimensional fatigue model was extended to a three-dimensional constitutive formulation under complex stress conditions. Finally, the applicability of the developed Bingham fatigue model was verified through fitting with experimental data, and the parameters of the model were identified. The model fitting results show high consistency with experimental data, with correlation coefficients exceeding 0.978 and 0.989 under low and high dynamic stress conditions, respectively, and root mean square errors (RMSEs) below 0.028. Comparative analysis between theoretical predictions and existing soft rock fatigue test data demonstrates that the developed Bingham fatigue model more effectively captures the complete fatigue deformation process under cyclic loading, including the deceleration, constant velocity, and acceleration phases. With its simplified component configuration and straightforward combination rules, this model provides a valuable reference for studying fatigue deformation characteristics of rock materials under dynamic loading conditions. Full article

Plasma has become an up-and-coming advanced oxidation technology for wastewater treatment. However, its efficiency is often limited due to the lack of high-performance catalytic materials. In this study, one-dimensional carbon nanofiber precursors were first fabricated via electrospinning, followed by the in situ growth of the Zn/Fe-MOF on their surfaces. After pyrolysis at different temperatures, a series of carbon-based catalysts (FeNFC) were obtained. This new type of catalyst possesses advantages such as high porosity, a large specific surface area, and mechanical stability. Using tetracycline (TTCH) as the target pollutant, the performance of the catalyst was evaluated in the dielectric barrier discharge (DBD) system. The study showed that the addition of FeNFC significantly increased the degradation rate of TTCH in the system. Comparing different pyrolysis temperatures, at 900 °C, the comprehensive performance of the catalyst (FeNFC-900) was the best (the kinetic constant was k_obs = 0.126 min⁻¹, and the removal rate of TTCH was 91.8% within 30 min). The catalytic performance was influenced by factors such as the dosage of the catalyst, the concentration of TTCH, the power of DBD, and the initial pH. The catalytic effect of the material increased within a certain range with the increase in the catalyst dosage. The increase in TTCH concentration led to a decrease in the catalytic performance. The higher the power of the DBD, the higher the removal rate of TTCH. Moreover, when the initial pH was strongly alkaline, the catalytic effect of the catalyst was the best (k_obs = 0.275 min⁻¹, and the removal rate of TTCH was 98.7% within 30 min). Ionic interference tests demonstrated the strong resistance of FeNFC to common water matrix components, while radical quenching experiments revealed that multiple reactive species contributed to TTCH degradation. This work has broad application prospects for enhancing the efficiency of DBD systems in the removal of TTCH. Full article

We design a one-dimensional magnetoelastic phononic crystal slab composed of the smart magnetostrictive material Terfenol-D and pure tungsten. Band inversion and topological phase transitions are achieved by modifying the geometric parameters of the non-magnetic medium within the unit cell. The emergence of topological interface states within overlapping bandgaps, exhibiting distinct topological properties, along with their robustness against interfacial structural defects, is confirmed. The coupling effects between adjacent topological interface states in a sandwich-like supercell configuration are investigated, and their tunability under external magnetic fields is demonstrated. A Su-Schrieffer-Heeger (SSH) phononic crystal slab system under gradient magnetic fields is proposed. Critically, and in stark contrast to previous static or structurally graded designs, we achieve reconfigurable rainbow trapping of topological interface states solely by reprogramming the gradient magnetic field, leaving the physical structure entirely unchanged. This highly localized, compact, and broadband-tunable topological rainbow trapping system design holds significant promise for applications in elastic energy harvesting, wave filtering, and multi-frequency signal processing. Full article

In optical one-dimensional grating-on-layer planar structures, an optical resonance occurs when the incident light wave becomes phase-matched to a leaky waveguide mode excited in the layer underneath the grating by an appropriate tuning of the grating periodicity. Changing the refractive indices of the grating’s constituents, and/or thickness, changes the resonance frequency. In the case of a two-dimensional grating atop such a smooth layer, a similar and also cavity-mode resonance can occur. This idea has straightforward usage in diverse optical sensor applications. In this study, a novel guided-mode resonance sensor design for detecting glucose and hemoglobin in minute concentrations at a wide range of incidence angles is presented. In this design, materials of the grating, such as a polymer and cesium-lead halide with a perovskite crystal structure, are examined, which will allow flexible, low-cost fabrication by soft-lithography/imprint-lithography methods. The sensitivity, figure of merit, and quality factor are reported for one- and two-dimensional grating structures. The simulations performed are based on rigorous coupled-wave analysis. Optical resonance quality factor of ∼$5·{10}^5$ is achieved at oblique incidence for a structure comprising a one-dimensional grating etched in a poly-vinylidene chloride layer atop a silicon nitride waveguide layer on a substrate. Record values of the above-noted characteristics are achieved with a synergetic interplay of the materials, structural dimensions, incidence angle, polarization, and grating geometry. Full article

Gallium-based room-temperature liquid metal is a promising multifunctional material for microfluidics and precision machining due to its high mobility and deformability. However, precise motion control of gallium-based liquid metal droplets, especially in abrasive particle-laden fluids, remains challenging. This study presents a hybrid control framework for regulating droplet motion in a one-dimensional PMMA channel filled with NaOH-based SiC abrasive suspensions. A dynamic model incorporating particle size and concentration effects on the damping coefficient was established. The system combines a setpoint controller, high-resolution voltage source, and vision feedback to guide droplets to target positions with high accuracy. Experimental validation and MATLAB simulations confirm that the proposed dynamic damping control strategy ensures stable, rapid, and precise positioning of droplets, minimizing motion fluctuations. This approach offers new insights into the manipulation of gallium-based liquid metal droplets for targeted material removal in micro-manufacturing, with potential applications in microelectronics and high-precision surface finishing. Full article

The development of lightweight, high-damping building materials is critical for enhancing the seismic resilience of civil infrastructure. This study introduces a novel approach to synergistically improve the damping and mechanical properties of cementitious composites by incorporating one-dimensional carbon nanotubes (CNTs) or two-dimensional graphene nanoplatelets (GNPs). The novelty lies in (1) a direct comparison of 1D versus 2D carbon nanomaterials efficacy within a vibration-relevant frequency range (0.5–2 Hz); (2) the use of the Ca(OH)₂ orientation index, derived from X-ray diffraction (XRD), to link microstructural texturing with macroscopic dynamic performance; and (3) establishing clear mechanistic link between carbon nanomaterials dispersion, pore structure evolution, and the resultant balance between stiffness and damping. Dynamic mechanical analysis identified an optimal dosage of 0.1% by weight for both nanomaterials. Comprehensive microstructural characterization (SEM, MIP, XRD, TGA/DTG) revealed that the carbon nanomaterials act as nucleation sites, promoting cement hydration and refining the pore structure. This structural enhancement concurrently improved mechanical strength and energy dissipation capacity. The primary damping mechanism was identified as interfacial friction and slippage at the nanofiller–matrix interface. These findings provide fundamental insights for the rational design of high-performance cementitious composites and offer an evidence-based pathway for creating advanced seismic-resistant materials. Full article

Optimal sensing devices exhibit a combination of key performance attributes, including an extensive detection limit, exceptional selectivity, high sensitivity, consistent repeatability, precise measurement, and rapid response times with efficient analyte flow. In recent years, biosensing platforms incorporating nanoscale materials have garnered considerable attention due to their diverse applications across various scientific and technological domains. The integration of nanoparticles (NPs) in biosensor design primarily bridges the dimensional gap between the signal transduction element and the biological recognition component, both of which operate at nanometer scales. The synergistic combination of NPs with electrochemical techniques has facilitated the development of biosensors characterized by enhanced sensitivity and superior analyte discrimination capabilities. This comprehensive analysis examines the evolution and recent advancements in nanomaterial (NM)-based biosensors, encompassing an extensive array of nanostructures. These consists of one-dimensional nanostructures including carbon nanotubes (CNTs), nanowires (NWs), nanorods (NRs), and quantum dots (QDs), as well as noble metal and metal and metal oxide nanoparticles (NPs). The article examines how advancements in biosensing techniques across a range of applications have been fueled by the growth of nanotechnology. Researchers have significantly improved biosensor performance parameters by utilizing the distinct physiochemical properties of these NMs. The developments have increased the potential uses of nanobiosensors in a wide range of fields, from food safety and biodefense to medical diagnostics and environmental monitoring. The continuous developments in NM-based biosensors are the result of the integration of several scientific areas, such as analytical chemistry, materials science, and biotechnology. This interdisciplinary approach continues to drive innovations in sensor design, signal amplification strategies, and data analysis techniques, ultimately leading to more sophisticated and capable biosensing platforms. As the field progresses, challenges related to the scalability, reproducibility, and long-term stability of nanobiosensors are being addressed through innovative fabrication methods and surface modification techniques. These efforts aim to translate the promising results observed in laboratory settings into practical, commercially viable biosensing devices that can address real-world analytical challenges across various sectors. Full article

Composite materials are widely used in various fields due to their superior properties. Given their complex internal structures, they are often modeled as homogeneous materials in engineering applications to simplify temperature distribution analysis. The key parameter in this approach is effective thermal conductivity (ETC). Conventional ETC models, based on Fourier’s law or the effective field approach, tend to underestimate temperatures when applied to composites containing internal heat sources, such as nuclear fuels. Preliminary studies have been conducted on ETC models for composite plates and particle-dispersed spheres with internal heat sources, using average temperature as the conserved quantity instead of the heat flux. This study focuses on dispersed disks containing internal heat sources. The finite element method is used to calculate its average-temperature-based ETC. The influence of filler size, filling fraction, and component thermal conductivities on the ETC is analyzed. Additionally, the impact of internal heat sources on ETC is discussed based on the theoretical model for the ETC of a one-dimensional composite plate. This research enhances understanding of ETC in composites with internal heat sources, reveals the connection between conventional and temperature-based ETC models, and provides insights for developing an ETC model for dispersed disks. Full article

We developed dye-sensitized solar cells based on anatase–titanium dioxide (A-TiO₂) nanotubes (TiNTs) and nanocubes (TiNcs) with {001} crystal facets generated using simple and facile electrochemical anodization. We also demonstrated a simple way of developing one-dimensional, two-dimensional, and three-dimensional self-assembled TiO₂ nanostructures via electrochemical anodization, using them as an electron-transporting layer in DSSCs. TiNTs maintain tubular arrays for a limited time before becoming nanocrystals with {001} facets. Using FESEM and TEM, we observed that the TiO₂ nanobundles were transformed into nanocubes with {001} facets and lower fluorine concentrations. Optimizing the reaction approach resulted in better-ordered, crystalline anatase TiNTs/Ncs being formed on the Ti metal foil. The anatase phase of as-grown TiO₂ was confirmed by XRD, with (101) being the predominant intensity and preferred orientation. The nanostructured TiO₂ had lattice values of a = 3.77–3.82 and c = 9.42–9.58. The structure and morphology of these as-grown materials were studied to understand the growth process. The photoconversion efficiency and impedance spectra were explored to analyze the performance of the designed DSSCs, employing N719 dye as a sensitizer and the I⁻/I³⁻ redox pair as electrolytes, sandwiched with a Pt counter-electrode. As a result, we found that self-assembled TiNTs/Ncs presented a more effective photoanode in DSSCs than standard TiO₂ (P25). TiNcs (0.5 and 0.25 NH₄F) and P25 achieved the highest power conversion efficiencies of 3.47, 3.41, and 3.25%, respectively. TiNcs photoanodes have lower charge recombination capability and longer electron lifetimes, leading to higher voltage, photocurrent, and photovoltaic performance. These findings show that electrochemical anodization is an effective method for preparing TiNTs/Ncs and developing low-cost, highly efficient DSSCs by fine-tuning photoanode structures and components. Full article

Understanding and accurately modelling mass transport phenomena in anode-supported solid oxide fuel cells (SOFCs) is essential for improving efficiency and mitigating performance losses due to concentration polarization. This study presents a one-dimensional, isothermal, multi-component diffusion framework based on the Stefan–Maxwell (SM) formulation to evaluate hydrogen, water vapour, and nitrogen transport in two different porous ceramic support materials: calcia-stabilized zirconia (CSZ) and magnesia magnesium aluminate (MMA). Both SM binary and SM ternary models are implemented to capture species interactions under varying hydrogen concentrations and operating temperatures. The SM formulation enables direct calculation of concentration polarization as well as the spatial distribution of gas species across the anode support’s thickness. Simulations are conducted for two representative fuel mixtures—20% H₂ (steam-rich, depleted fuel) and 50% H₂ (steam-lean)—across a temperature range of 500–1000 °C and varying electrode thicknesses. They are validated against experimental data from the literature, and the influence of electrode thickness and fuel composition on polarization losses is systematically assessed. The results show that the ternary SM model provides superior accuracy in predicting overpotentials, especially under low-hydrogen conditions where multi-component interactions dominate. MMA consistently exhibits lower polarization losses than CSZ due to enhanced gas diffusivity. This work offers a validated, computationally efficient framework for evaluating mass transport limitations in porous anode supports and offers insights for optimizing electrode design and operational strategies, bridging the gap between simplified analytical models and full-scale multiphysics simulations. Full article

This study introduces a novel energy-based inverse method for estimating residual stresses in structures composed of one-dimensional elements undergoing elastic–plastic deformation. The problem is reformulated as a global optimization task governed by the principle of minimum total potential energy. Rather than solving equilibrium equations directly, the internal stress distribution is inferred by minimizing the structure’s total potential energy using a real-coded genetic algorithm. This approach avoids gradient-based solvers, matrix assembly, and incremental loading, making it suitable for nonlinear and history-dependent systems. Plastic deformation is encoded through element-wise stress-free lengths, and a dynamic fitness exponent strategy adaptively controls selection pressure during the evolutionary process. The method is validated on single- and multi-bar truss structures under axial tensile loading, using a bilinear elastoplastic material model. The results are benchmarked against nonlinear finite element simulations and analytical calculations, demonstrating excellent predictive capability with stress errors typically below 1%. In multi-material systems, the technique accurately reconstructs tensile and compressive residual stresses arising from elastic–plastic mismatch using only post-load geometry. These results demonstrate the method’s robustness and accuracy, offering a fully non-incremental, variational alternative to traditional inverse approaches. Its flexibility and computational efficiency make it a promising tool for residual stress estimation in complex structural applications involving plasticity and material heterogeneity. Full article

Miller’s rule originated as an empirical relation between the nonlinear and linear optical coefficients of materials. It is now accepted as a useful tool for guiding experiments and computational materials discovery, but its theoretical foundation had long been limited to a derivation for the classical Lorentz model with a weak anharmonic perturbation. Recently, we developed a mathematical framework which enabled us to prove that Miller’s rule is equally valid for quantum anharmonic oscillators, despite different dynamics due to zero-point fluctuations and further quantum-mechanical effects. However, our previous derivation applied only to one-dimensional oscillators and to the special case of second- and third-harmonic generation in a monochromatic electric field. Here we extend the proof to three-dimensional quantum anharmonic oscillators and also treat all orders of the nonlinear response to an arbitrary multi-frequency field. This makes the results applicable to a much larger range of physical systems and nonlinear optical processes. The obtained generalized Miller formulae rigorously express all tensor elements of the frequency-dependent nonlinear susceptibilities in terms of the linear susceptibility and thus allow a computationally inexpensive quantitative prediction of arbitrary parametric frequency-mixing processes from a small initial dataset. Full article

We investigate the electronic properties of atomic chains placed on group-14 two-dimensional materials, Xenes, by analyzing the local electronic properties. Our results show that the hybridization between the chain and the substrate leads to significant modifications in the local density of states at each chain site, including peak splitting, broadening, and asymmetry. These effects are particularly pronounced for plumbene. Owing to the substrate’s V-shaped-like density of states, the chains exhibit strong localization effects and significant intensity variations in the electronic energy spectrum. In addition the present analysis reveals the emergence of charge density waves in atomic chains, for which the appearance and stability conditions are identified and provided. The charge density waves are more pronounced and stabilized by a specific electronic spectrum of Xenes, allowing them to penetrate deeper into the chain interior. Our findings contribute to the broader understanding of the interaction between one-dimensional chains and two-dimensional Xene materials, which have significant implications for developing advanced hybrid nanostructures and next generation electronic devices. Full article

The electric energy metering box serves as a crucial node in power grid operations, offering essential protection for key components in the distribution network, such as smart meters, data acquisition terminals, and circuit breakers, thereby ensuring their safe and reliable operation. However, the non-metallic housings of these boxes are susceptible to aging under environmental stress, which can result in diminished flame-retardant properties and an increased risk of fire. Currently, there is a lack of rapid and accurate methods for assessing the fire resistance of non-metallic metering box enclosures. In this study, laser-induced breakdown spectroscopy (LIBS), which enables fast, multi-element, and non-contact analysis, was utilized to develop an effective assessment approach. Thermal aging experiments were conducted to systematically investigate the degradation patterns and mechanisms underlying the reduced flame-retardant performance of sheet molding compound (SMC), a representative non-metallic material used in metering box enclosures. The results showed that the intensity ratio of aluminum ionic spectral lines is highly correlated with the flame-retardant grade, serving as an effective performance indicator. On this basis, a one-dimensional convolutional neural network (1D-CNN) model was developed utilizing LIBS data, which achieved over 92% prediction accuracy for different flame-retardant grades on the test set and demonstrated high recognition accuracy for previously unseen samples. This method offers significant potential for rapid, on-site evaluation of flame-retardant grades of non-metallic electric energy metering boxes, thereby supporting the safe and reliable operation of power systems. Full article

Nanomaterials are materials in which at least one dimension in three-dimensional space is at the nanoscale. In recent years, nano-alumina has attracted much attention due to its large specific surface area and pore volume, as well as novel optical, magnetic, electronic, and catalytic properties. This review summarizes the preparation methods of nano-alumina based on the basic phases and properties of alumina materials, focusing on one-dimensional, two-dimensional, and three-dimensional nano-alumina preparation methods, which can provide some theoretical guidance for the subsequent development of efficient nano-alumina materials. Finally, the application of nano-alumina materials in catalysis is reviewed, and some suggestions are provided for improving the use of nano-alumina in the catalysis field. Full article