Search Results (5,838)

The local segmental mobility of polymer chains in polydimethylsiloxane (PDMS) plays a critical role in determining the material’s behaviour. Incorporation of zeolite particles can modify these local dynamics, which is crucial as they affect the overall performance of the resulting composite material with potential for various industrial applications. The aim of this study was to investigate the influence of zeolite addition on the local dynamic behaviour of PDMS chain segments in PDMS–zeolite composites. To investigate the effect of zeolite morphology and loading on the segmental dynamics and phase behaviour of PDMS, Zeolite A (with cubic and spherical morphologies) and Zeolite X were incorporated into the PDMS matrix at 20, 30, and 40 wt%. The electron spin resonance (ESR)-spin probe method was used to study molecular dynamics, while the thermal behaviour was analysed using differential scanning calorimetry (DSC). ESR results revealed that the presence of zeolites increases the isothermal crystallisation rate affecting segmental mobility in the amorphous phase below the crystallisation temperature. This effect was found to depend more strongly on zeolite morphology than on filler content. DSC measurements showed no change in glass transition temperature with the addition of zeolite; however, shifts in cold crystallisation and melting behaviour were observed, indicating changes in crystal structure and its degree of perfection. These findings suggest that zeolites act as heterogeneous nucleation agents, with their structural properties playing a critical role in the crystallisation behaviour of PDMS. Full article

The precise prediction of high-speed railway bridge pier settlement plays a crucial role in construction, maintenance, and long-term operation; however, current mainstream prediction methods mostly rely on independent analyses based on traditional or hybrid models, neglecting the impact of geological and environmental factors on subsidence. To address this issue, this paper proposes a multi-factor settlement prediction model for high-speed railway bridge piers named the Reversible Instance Normalization Multi-Scale Adaptive Resolution Stream CMamba, abbreviated as RMCMamba. During the data preprocessing process, the Enhanced PS-InSAR technology is adopted to obtain the time series data of land settlement in the study region. Utilizing the cubic improved Hermite interpolation method to fill the missing values of monitoring and considering the environmental parameters such as groundwater level, temperature, precipitation, etc., a multi-factor high-speed railway bridge pier settlement dataset is constructed. RMCMamba fuses the reversible instance normalization (RevIN) and the multiresolution forecasting head (MARSHead), enhancing the model’s long-range dependence capture capability and solving the time series data distribution drift problem. Experimental results demonstrate that in the multi-factor prediction scenario, RMCMamba achieves an MAE of 0.049 mm and an RMSE of 0.077 mm; in the single-factor prediction scenario, the proposed method reduces errors compared to traditional prediction approaches and other deep learning-based methods, with MAE values improving by 4.8% and 4.4% over the suboptimal method in multi-factor and single-factor scenarios, respectively. Ablation experiments further verify the collaborative advantages of combining reversible instance normalization and the multi-resolution forecasting head, as RMCMamba’s MAE values improve by 5.8% and 4.4% compared to the original model in multi-factor and single-factor scenarios. Hence, the proposed method effectively enhances the prediction accuracy of high-speed railway bridge pier settlement, and the constructed multi-source data fusion framework, along with the model improvement strategy, provides technological and experiential references for relevant fields. Full article

Packed granular materials absorb sound. In previous studies, granular materials sized a few millimeters and samples of grain size as a powder were studied; however, the grain sizes in between have not been addressed. In this study, the sound absorption coefficients of materials ranging from granular materials with a grain size d = 4 mm to powder materials with d = 0.05 mm were analyzed theoretically and experimentally. In addition, five packing types were studied: four types of regular packing and random packing. For these packing structures, the propagation constants and characteristic impedances were substituted within a one-dimensional transfer matrix for sound wave propagation, from which the normal-incidence sound absorption coefficient was calculated. Furthermore, our analysis accounted for particle longitudinal vibrations due to sound pressure. According to analyses of cross-sectional CT images considering tortuosity, the theoretical values for random packing tended to be close to the experimental values for d = 0.8 mm and smaller. For random packing structures with d = 0.3 mm or smaller, the experimental values were closer to the theoretical values for simple cubic lattice than the theoretical values for random packing. Full article

All-inorganic halide perovskites have attracted significant interest in photodetector applications due to their remarkable photoresponse properties. However, the toxicity and instability of lead-based perovskites hinder their commercialization. In this work, we propose cubic Ba₃SbI₃ as a promising, environmentally friendly, lead-free material for next-generation photodetector applications. Ba₃SbI₃ shows good light absorption, low effective masses, and favorable elemental abundance and cost, making it a promising candidate compound for device applications. Its structural, mechanical, electronic, and optical properties were systematically investigated using density functional theory (DFT) with the Perdew–Burke–Ernzerhof (PBE) and hybrid HSE06 functionals. The material was found to be dynamically and mechanically stable, with a direct bandgap of 0.78 eV (PBE) and 1.602 eV (HSE06). Photodetector performance was then simulated in an Al/FTO/In₂S₃/Ba₃SbI₃/Sb₂S₃/Ni configuration using SCAPS-1D. To optimize device efficiency, the width, dopant level, and bulk concentration for each layer of the gadgets were systematically modified, while the effects of interface defects, operating temperature, and series and shunt resistances were also evaluated. The optimized device achieved an open-circuit voltage (Voc) of 1.047 V, short-circuit current density (Jsc) of 31.65 mA/cm², responsivity of 0.605 A W⁻¹, and detectivity of 1.05 × 10¹⁷ Jones. In contrast, in the absence of the Sb₂S₃ layer, the performance was reduced to a Voc of 0.83 V, Jsc of 26.8 mA/cm², responsivity of 0.51 A W⁻¹, and detectivity of 1.5 × 10¹⁵ Jones. These results highlight Ba₃SbI₃ as a promising platform for high-performance, cost-effective, and environmentally benign photodetectors. Full article

Background: Previous studies have shown that a diet with inflammatory and antioxidant properties can alter the risk of cognitive impairment. There are few studies using a large sample of the Chinese population. The specific relationship between inflammation, an antioxidant diet, and cognitive impairment remains unclear, and the potential impact of metabolic disorders remains to be determined. Methods: This is a cross-sectional study, with data from the China Health and Nutrition Survey (CHNS) in 2018. Individual and combined effects of the dietary inflammation index (DII) and composite dietary antioxidant index (CDAI) on cognitive impairment were assessed by binary logistic regression models. Nonlinear correlations and the inflection point were explored using restricted cubic splines (RCSs), and the mediation effects of triglyceride glucose–body mass index (TyG-BMI) were explored in greater depth using causal mediation analysis. Results: An increased CDAI was associated with a significantly decreased risk of cognitive impairment, at 0.68 (95%CI: 0.499–0.928). Contrary to this, the DII was positively associated with the risk of cognitive impairment, at 1.289 (95%CI: 1.03–1.613). The joint effects of the DII and CDAI indicated the minimal hazard effects on the risk of cognitive (0.787 (95%CI: 0.622–0.995)) impairment in subjects with low_DII + high_CDAI when compared with those with high_DII + low_CDAI. Furthermore, a significant nonlinear relationship was found between the CDAI and the risk of cognitive impairment, exhibiting an “L”-shaped curve (p-overall = 0.001, p-nonlinear = 0.007). However, no evidence was found for a nonlinear relationship between the DII and the risk of cognitive impairment. The mediation analysis did not reveal a mediating effect of TyG-BMI on the association between the CDAI and DII scores and the risk of cognitive impairment. Conclusions: Findings revealed that the CDAI could mitigate the adverse consequences of the DII on cognitive decline, which offers new insights into preventing early cognitive impairment through dietary intervention. Full article

As well as having corrosion resistance and mechanical properties, medical metallic biomaterials used in metal implants must allow imaging by MRI for prognostic diagnosis. Alloys based on Ti, Fe, Co, etc., have the disadvantage that those constituent elements have higher magnetic susceptibility than the tissue surrounding the metallic implant, and this condition results in defects and distortions (“artifacts”) in MR images during MRI imaging. In consideration of this issue, MRI-compatible low-magnetic-susceptibility materials are currently being researched and developed. In this study, microstructural control of Zr-based alloys by alloy design and heat treatment was investigated. The problem with pure Zr is its low corrosion resistance due to the α-phase of its hexagonal-close-packed (HCP) structure. However, alloys that were alloyed and solution heat-treated to a β-phase (body-centered cubic (BCC) structure) showed high corrosion resistance. In particular, when Zr-15Nb-5Ti-3Cr, which has relatively high corrosion resistance, was subjected to aging heat treatment at 673 K for 1.8 ks, precipitation of fine ω-phase in the β-phase was confirmed. The metallographic structure in which the ω-phase precipitated in the β-phase provided high corrosion resistance [≧1000 mV (vs. SHE)] derived from the β-phase, as well as low magnetic susceptibility (approximately 1.2 × 10⁻⁶ cm³/g), due to the effect of the ω-phase. This study provides guidelines for microstructural control to achieve both low magnetic susceptibility and high corrosion resistance in Zr-based metallic biomaterials for medical use. Full article

With the rapid advancement of hyperspectral remote sensing technology, the security of hyperspectral images (HSIs) has become a critical concern. However, traditional image encryption methods—designed primarily for grayscale or RGB images—fail to address the high dimensionality, large data volume, and spectral-domain characteristics inherent to HSIs. Existing chaotic encryption schemes often suffer from limited chaotic performance, narrow parameter ranges, and inadequate spectral protection, leaving HSIs vulnerable to spectral feature extraction and statistical attacks. To overcome these limitations, this paper proposes a novel hyperspectral image encryption algorithm based on a newly designed two-dimensional cross-coupled hyperchaotic map (2D-CSCM), which synergistically integrates Cubic, Sinusoidal, and Chebyshev maps. The 2D-CSCM exhibits superior hyperchaotic behavior, including a wider hyperchaotic parameter range, enhanced randomness, and higher complexity, as validated by Lyapunov exponents, sample entropy, and NIST tests. Building on this, a layered encryption framework is introduced: spectral-band scrambling to conceal spectral curves while preserving spatial structure, spatial pixel permutation to disrupt correlation, and a bit-level diffusion mechanism based on dynamic DNA encoding, specifically designed to secure high bit-depth digital number (DN) values (typically > 8 bits). Experimental results on multiple HSI datasets demonstrate that the proposed algorithm achieves near-ideal information entropy (up to 15.8107 for 16-bit data), negligible adjacent-pixel correlation (below 0.01), and strong resistance to statistical, cropping, and differential attacks (NPCR ≈ 99.998%, UACI ≈ 33.30%). The algorithm not only ensures comprehensive encryption of both spectral and spatial information but also supports lossless decryption, offering a robust and practical solution for secure storage and transmission of hyperspectral remote sensing imagery. Full article

The present work investigates the electrochemical behavior of the Zr2.5Nb alloy in a biomedical context, emphasizing the influence of electrochemical oxidation treatment on its stability in simulated physiological environments. The alloy samples were oxidized in 1 M H₂SO₄ under controlled voltages (200–275 V) and times (1 min), identifying 200 V–1 min as the optimal condition for obtaining a uniform porous oxide layer with an average pore diameter of ~90 nm. The corrosion resistance was evaluated using open circuit potential (OCP) and electrochemical impedance spectroscopy (EIS) in Ringer’s solution and Ringer’s solution containing 40 g/L H₂O₂ to simulate physiological and inflammatory conditions. Electrochemical tests revealed that electrochemically oxidized samples exhibited a polarization resistance up to 14.78 MΩ·cm², about 26 times higher than that of the untreated alloy (0.56 MΩ·cm²). After 77 h of immersion, the oxidized alloy maintained a high resistance (17.54 MΩ·cm²), confirming long-term stability. Scanning Electron Microscopy (SEM–EDX) and X-Ray Diffraction (XRD) analyses highlighted significant increases in oxygen content and the transformation from the monoclinic baddeleyite to the cubic arkelite phase of ZrO₂, contributing to enhanced corrosion resistance. These findings demonstrate that controlled electrochemical oxidation significantly improves the durability of Zr2.5Nb alloy in oxidative environments, supporting its potential for long-term biomedical implant applications. Full article

Additive manufacturing via stereolithography (SLA) enables the fabrication of highly customized lattice structures, yet the interplay between geometry and graded density in defining mechanical behavior remains underexplored. This research investigates the mechanical behavior and failure mechanisms of cylindrical lattice structures considering uniform, linear, and quadratic density variations. Various configurations, including IsoTruss, face-centered cubic (FCC)-type cells, Kelvin structures, and Tet oct vertex centroid, were examined under a complete factorial design that allowed a thorough exploration of the interactions between lattice geometry and density variation. A 3D printer working with SLA was used to fabricate the models. For the analysis, a universal testing machine, following ASTM D638-22 Type I and ASTM D1621-16 standards, was used for tension and compression tests. For microstructural analysis and surface inspection, a scanning electron microscope and a digital microscope were used, respectively. Results indicate that the IsoTruss configuration with linear density excelled remarkably, achieving an impressive energy absorption of approximately 15 MJ/m³ before a 44% strain, in addition to presenting the most outstanding mechanical properties, with a modulus of elasticity of 613.97 MPa, a yield stress of 22.646 MPa, and a maximum stress of 49.193 MPa. On the other hand, the FCC configuration exhibited the lowest properties, indicating lower stiffness and mechanical strength in compression, with an average modulus of elasticity of 156.42 MPa, a yield stress of 5.991 MPa, and the lowest maximum stress of 14.476 MPa. The failure modes, which vary significantly among configurations, demonstrate the substantial influence of the lattice structure and density distribution on structural integrity, ranging from localized bending in IsoTruss to spalling in FCC and shear patterns in Kelvin. This study emphasizes the importance of selecting fabrication parameters and structural design accurately. This not only optimizes the mechanical properties of additively manufactured parts but also provides essential insights for the development of new advanced materials. Overall, the study demonstrates that both lattice geometry and density distribution play a crucial role in determining the structural integrity of additively manufactured materials. Full article

The rational design of transition metal oxides with tailored electronic structures and defect chemistries is critical for advancing high-performance supercapacitors. Herein, we report the engineering of cobalt oxide (Co₃O₄) gels through controlled sol–gel synthesis and rare earth (RE) incorporation using neodymium (Nd), gadolinium (Gd), and dual neodymium/gadolinium (Nd/Gd) doping. X-ray diffraction (XRD) confirmed the preservation of the cubic spinel structure with systematic peak shifts and broadening, evidencing lattice strain, oxygen vacancy generation, and defect enrichment. Field-emission scanning electron microscopy (FE-SEM) analyses revealed distinct morphological evolution from compact nanoparticle assemblies in pristine Co₃O₄ to highly porous, interconnected frameworks in Nd/Gd–Co₃O₄ (Nd/Gd-Co). X-ray photoelectron spectroscopy (XPS) verified the stable incorporation of RE ions, accompanied by electronic interaction with the Co–O matrix and enhanced oxygen defect states. Electrochemical measurements demonstrated that the Nd/Gd–Co electrode achieved a remarkable areal capacitance of 25 F/cm² at 8 mA/cm², superior ionic diffusion coefficients, and the lowest equivalent series resistance (0.26 Ω) among all samples. Long-term cycling confirmed 84.35% capacitance retention with 94.46% coulombic efficiency after 12,000 cycles. Furthermore, the asymmetric pouch-type supercapacitor (APSD) constructed with Nd/Gd–Co as the positive electrode and activated carbon as the negative electrode delivered a wide operational window of 1.5 V, an areal capacitance of 140 mF/cm², an energy density of 0.044 mWh/cm², and 89.44% retention after 7000 cycles. These findings establish Nd/Gd-Co gels as robust and scalable electrode materials and demonstrate that RE co-doping is an effective strategy for bridging high energy density with long-term electrochemical stability in asymmetric supercapacitors. Full article

Garnet-type Li₇La₃Zr₂O₁₂ (LLZO) is a solid electrolyte candidate for ASSLBs, owing to its wide electrochemical window and intrinsic safety. Yet phase-pure LLZO remains difficult because secondary phases form, and the transition towards the tetragonal phase, aliovalent doping, mitigates these issues. Still, the phase formation pathway is not fully understood. Here, we present comparative in situ and ex situ studies of Nb- and Ta-doped LLZO (LLZNO and LLZTO) that were synthesized by a solid-state reaction. In situ/ex situ XRD reveals that the lithium precursor dictates the reaction path: differing decomposition temperatures of the lithium precursor define reaction windows that control cubic-phase purity and particle morphology. In air, limited Li diffusion favors oxycarbonates and pyrochlore, necessitating 950–1050 °C to achieve phase-pure cubic LLZO. Under N₂, faster Li availability and diffusion enable uniform nucleation and a route to cubic LLZO without detectable secondary phases. These findings demonstrate the coupled effects of temperature, precursor, dopant, and atmosphere, guiding process optimization and scalable production. Full article

Multidrug resistance has also been accompanied by the prolonged use of antibiotics that makes complications in treatment. Biofilm in pathogenic bacteria is the most serious challenge linked with chronic illnesses and also contributes to virulence and drug resistance. Several bacterial pathogens employ the Quorum-sensing (QS) mechanism to coordinate their collective behaviors like bioluminescence, virulence, and biofilm formation. Therefore, agents that inhibit or interfere with bacterial QS and biofilm formation are emerging as a new class of next-generation antibacterial. Recently, nanoparticles have been employed to improve the efficacy of existing antibacterial agents. In the present study, gold nanocrystals were synthesized by using Koelreuteria paniculata (KP) leaf extract. Synthesized nanocrystals were characterized by a face-centered cubic structure of ~20 nm by XRD, FTIR, Zeta sizer, and TEM. Biogenic Gold nanocrystals (BGNCs) exhibited extended QS inhibition in bio-indicator strains Chromobacterium violaceum and Pseudomonas aeruginosa biosensor strains. BGNCs strongly suppressed QS-controlled violacein production in C. violaceum CV026, and elastase, protease, pyocyanin, alginate, and biofilm formation in P. aeruginosa (PA01). In addition, BGNCs notably suppressed the relative expression of PA01 quorum sensing, biofilm-forming, and virulence-regulating genes, as quantified by qRT-PCR. As a result of the broad-spectrum suppression of QS and biofilm by BGNCs, it is anticipated that these nontoxic bioactive nanocrystals can be employed as surface sterilization agents in nosocomial infections. Full article

In addition to the performance parameters of a mechanical manipulator—such as precision, repeatability, payload and maximum speed—path optimization can bring significant improvements in terms of cycle time and energy consumption. In this paper, a method is proposed for post-processing trajectories initially generated by spline interpolation in joint space (cubic or quintic interpolation), so that the distances traveled are shorter. The principle of least action is used as a theoretical foundation trying to find the best cost function in terms of trajectory lengths using. In the pursuit of minimizing this cost function, an iterative method is applied. Initial trajectories are split into multiple internal nodes that are displaced little by little from their initial positions, recomposing trajectories that pass through these displaced nodes at every iteration. The purpose of this paper is to demonstrate that by post-processing trajectories initially generated by the usual spline interpolation in joint space, alternative, shorter variants can be obtained. Full article

This study aims to extend the understanding of groundwater level dynamics in the Abu Dhabi Emirate by evaluating the performance of two interpolation models, local polynomial interpolation (LPI) and exponential ordinary kriging (EXP-OK), over a 20-year period. These models were selected for their demonstrated effectiveness in groundwater studies, with LPI offering strong local adaptability to spatial variability and EXP-OK providing robust geostatistical modeling for regional patterns. This study also aims to assess the performance of the two interpolation models in identifying missing groundwater level measurements to accurately estimate groundwater storage. The evaluation of the two models is conducted using ArcGIS and IBM-SPSS statistics, including cross-validation, descriptive statistics and exploratory spatial data analysis (ESDA). The findings revealed that both LPI and EXP-OK are effective in analyzing groundwater fluctuations in the study area, with LPI demonstrating a slight edge in predictive accuracy. The ability of the LPI to capture local data variations resulted in a smoother representation of groundwater level data. Owing to its superior performance, the LPI was selected for the estimation of groundwater storage. The study reports that the average change in groundwater storage over the study period could range from −0.066 to −2.112 cubic meters per square meter of aquifer area. These findings emphasize the importance of continuous monitoring and analysis for sustainable water resource management in the study area. Full article

The stability of a circular vortex is studied in the thermal quasi-geostrophic (TQG) model. Several radial distributions of vorticity and buoyancy (temperature) are considered for the mean flow. First, the linear stability of these vortices is addressed. The linear problem is solved exactly for a simple flow, and two stability criteria are then derived for general mean flows. Then, the growth rate and most unstable wavenumbers of normal-mode perturbations are computed numerically for Gaussian and cubic exponential vortices, both for elliptical and higher mode perturbations. In TQG, contrary to usual QG, short waves can be linearly unstable on shallow vorticity profiles. Linearly, both stratification and bottom topography (under specific conditions) have a stabilizing role. In a second step, we use a numerical model of the nonlinear TQG equations. With a Gaussian vortex, we show the growth of small-scale perturbations during the vortex instability, as predicted by the linear analysis. In particular, for an unstable vortex with an elliptical perturbation, the final tripolar vortices can have a turbulent peripheral structure, when the ratio of mean buoyancy to mean velocity is large enough. The frontogenetic tendency indicates how small-scale features detach from the vortex core towards its periphery, and thus feed the turbulent peripheral vorticity. We confirm that stratification and topography have a stabilizing influence as shown by the linear theory. Then, by varying the vortex and perturbation characteristics, we classify the various possible nonlinear regimes. The numerical simulations show that the influence of the growing small-scale perturbations is to weaken the peripheral vortices formed by the instability, and by this, to stabilize the whole vortex. A finite radius of deformation and/or bottom topography also stabilize the vortex as predicted by linear theory. An extension of this work to stratified flows is finally recommended. Full article