Search Results (1,285)

Metallic nanofoams with amorphous structures demonstrate exceptional properties and significant potential for diverse applications. However, their mechanical properties at different temperatures are still unclear. By using molecular dynamics simulation, this study investigates the mechanical responses of representative CuZr amorphous metallic nanofoam (AMNF) under uniaxial tension and compression at various temperatures. Our results reveal that the mechanical properties, such as Young’s modulus, yield stress, and maximum stress, exhibit notable temperature sensitivity and tension–compression asymmetry. Under tensile loading, the Young’s modulus, yield strength, and peak stress exhibit significant reductions of approximately 30.5%, 33.3%, and 32.9%, respectively, as the temperature increases from 100 K to 600 K. Similarly, under compressive loading, these mechanical properties experience even greater declines, with the Young’s modulus, yield strength, and peak stress decreasing by about 34.5%, 38.0%, and 41.7% over the same temperature range. The tension–compression asymmetry in yield strength is temperature independent. Interestingly, the tension–compression asymmetry in elastic modulus becomes more pronounced at elevated temperatures, which is attributed to the influence of surface energy effects. This phenomenon is further amplified by the increased disparity in surface-area-to-volume ratio variations between tensile and compressive loading at higher temperatures. Additionally, as the temperature rises, despite material softening, the structural resistance under large tensile strains improves due to delayed ligament degradation and more uniform deformation distribution, delaying global failure. Full article

Superplastic materials are characterised by extreme lightness and remarkable ductility. Instead of a punch, a gas is used to push the sheet into the die cavity, and it is precisely regulated to control the material’s strain rate. Forming a superplastic material while maintaining a high strain rate sensitivity index requires the forming gas to follow a precise pressure–time loading curve. This can be excellently predicted with the aid of the finite element method (FEM). Therefore, for the superplastic material to exhibit its best formability throughout the entire process, it is necessary to control the strain rate step by step to keep the maximum strain rate within the material’s optimal superplastic range. In this work, the results of a superplastic-forming process used to create a hemispherical shell are presented. This was carried out using both a circular blank of uniform thickness and a blank with a conical cross-section. The analysis was performed using finite element modelling. Specifically, the results obtained using 3D analysis were compared with those obtained using axisymmetric analysis for conditions of axial symmetry. Using the conical cross-section blank helped achieve a more uniform thickness distribution in the produced hemispherical shell. The success of the numerical activity was validated through results from appropriate experimental work conducted on the magnesium alloy AZ31. The results show that, by employing a blank characterised by a conical section profile, the thickness distribution appears more uniform than that of a constant-thickness blank. Full article

A novel single-walled carbon nanotube (SWNT), silver (Ag) nanoparticle, and zinc benzene carboxylate (ZnBDC) metal–organic framework (MOF) composite was synthesised and systematically characterised to develop an efficient platform for mercury ion (Hg²⁺) detection. X-ray diffraction confirmed the successful incorporation of Ag nanoparticles and SWNTs without disrupting the crystalline structure of ZnBDC. Meanwhile, field-emission scanning electron microscopy and energy-dispersive spectroscopy mapping revealed a uniform elemental distribution. Thermogravimetric analysis indicated enhanced thermal stability. Electrochemical measurements (cyclic voltammetry and electrochemical impedance spectroscopy) demonstrated improved charge transfer properties. Electrochemical sensing investigations using differential pulse voltammetry revealed that the SWNTs/Ag@ZnBDC-modified glassy carbon electrode exhibited high selectivity toward Hg²⁺ ions over other metal ions (Cd²⁺, Co²⁺, Cr³⁺, Fe³⁺, and Zn²⁺), with optimal performance at pH 4. The sensor displayed a linear response in the concentration range of 0.1–1.0 nM (R² = 0.9908), with a calculated limit of detection of 0.102 nM, slightly close to the lowest tested point, confirming its high sensitivity for ultra-trace Hg²⁺ detection. The outstanding sensitivity, selectivity, and reproducibility underscore the potential of SWNTs/Ag@ZnBDC as a promising electrochemical platform for detecting trace levels of Hg2+ in environmental monitoring. Full article

This study investigates the behavior and performance of a newly proposed cone-top pile foundation designed to improve stability in layered, deformable, or strain-sensitive soils. Traditional shallow and uniform conical foundations often suffer from excessive settlement and reduced capacity when subjected to vertical loads and horizontal soil deformations. To address these limitations, a hybrid foundation was developed that integrates an inverted conical base with a central pile shaft and a rolling joint interface between the foundation and the superstructure. Laboratory model tests, full-scale field loading experiments, and axisymmetric numerical simulations using Plaxis 2D (Version 8.2) were conducted to evaluate the foundation’s bearing capacity, settlement behavior, and load transfer mechanisms. Results showed that the cone-top pile foundation exhibited lower settlements and higher load resistance than columnar foundations under similar loading conditions, particularly in the presence of horizontal tensile strains. The load was effectively distributed through the conical base and transferred into deeper soil layers via the pile shaft, while the rolling joint reduced stress transmission to the structure. The findings support the use of cone-top pile foundations in soft soils, seismic areas and areas affected by underground mining, where conventional designs may be inadequate. This study provides a validated and practical design alternative for challenging geotechnical environments. Full article

Traditional perforated duct designs fail to resolve the energy consumption-uniformity conflict in semi-closed greenhouses. To address this, we develop a CFD-RSM-NSGA-II framework that simultaneously minimizes velocity non-uniformity (CV-v), pressure loss (ΔP), and temperature variation (CV-t). Key parameters—hole diameter (6–10 mm), spacing (30–70 mm), and inlet velocity (4–8 m/s)—are co-optimized. Model validation showed that the mean relative errors were 8.6% for velocity, 2.3% for temperature, and pressure deviations below 5 Pa, with the response surface model achieving an R² of 0.9831 (p < 0.0001). Larger hole diameters improved CV-v, while wider spacings led to a decrease in uniformity. Pressure loss followed an opposite trend. Temperature variation was mostly affected by inlet velocity. Sensitivity analysis revealed that hole diameter was the most influential factor, followed by spacing and velocity, with a significant interaction between diameter and spacing. Using entropy-weighted TOPSIS coupled with NSGA-II, the optimization identified an optimal configuration (hole diameter = 9.0 mm, spacing = 65 mm, velocity = 7.0 m/s). This solution achieved a 58.8% reduction in CV-v, a 10.8% decrease in ΔP, and a 5.2% improvement in CV-t, while stabilizing inlet static pressure at 72.8 Pa. Critically, it reduced power consumption by 17.4%—directly lowering operational costs for farmers. The “larger diameter, wider spacing” strategy resolves energy-uniformity conflicts, demonstrating how integrated multi-objective process control enables efficient greenhouse ventilation. Full article

The rapid expansion of Internet of Things (IoT) devices has heightened the demand for lightweight and secure cryptographic mechanisms suitable for resource-constrained environments. While SHA-256 remains a widely used standard, the emergence of SHA-3 particularly the KangarooTwelve variant offers potential benefits in flexibility and post-quantum resilience for lightweight resource-constrained devices. This paper presents a comparative evaluation of the energy costs associated with SHA-256 and SHA-3 hashing in Contiki 3.0, using three generationally distinct IoT platforms: Sky Mote, Z1 Mote, and Wismote. Unlike previous studies that rely on hardware acceleration or limited scope, our work conducts a uniform, software-only analysis across all motes, employing consistent radio duty cycling, ContikiMAC (a low-power Medium Access Control protocol) and isolating the cryptographic workload from network overhead. The empirical results from the Cooja simulator reveal that while SHA-3 provides advanced security features, it incurs significantly higher CPU and, in some cases, radio energy costs particularly on legacy hardware. However, modern platforms like Wismote demonstrate a more balanced trade-off, making SHA-3 viable in higher-capability deployments. These findings offer actionable guidance for designers of secure IoT systems, highlighting the practical implications of cryptographic selection in energy-sensitive environments. Full article

To address the growing demand for environmentally friendly flexible sensors, here, a composite hydrogel of nanocellulose (NC) and polyvinyl alcohol (PVA) was designed and fabricated using Camellia oleifera shells as a sustainable alternative to petroleum-based raw materials. Firstly, NC was extracted from Camellia oleifera shells and modified with 2-chloropropyl chloride to obtain a nanocellulose-based initiator (Init-NC) for atomic transfer radical polymerization (ATRP). Subsequently, sulfonyl betaine methacrylate (SBMA) was polymerized by Init-NC initiating to yield zwitterion-functionalized nanocellulose (NC-PSBMA). Finally, the NC-PSBMA/PVA hydrogel was fabricated by blending NC-PSBMA with PVA. A Fourier transform infrared spectrometer (FT-IR), proton nuclear magnetic resonance spectrometer (¹H-NMR), X-ray diffraction (XRD), scanning electron microscope (SEM), transmission electron microscope (TEM), universal mechanical testing machine, and digital source-meter were used to characterize the chemical structure, surface microstructure, and sensing performance. The results indicated that: (1) FT-IR and ¹H NMR confirmed the successful synthesis of NC-PSBMA; (2) SEM, TEM, and alternating current (AC) impedance spectroscopy verified that the NC-PSBMA/PVA hydrogel exhibits a uniform porous structure (pore diameter was 1.1737 μm), resulting in significantly better porosity (15.75%) and ionic conductivity (2.652 S·m⁻¹) compared to the pure PVA hydrogel; and (3) mechanical testing combined with source meter testing showed that the tensile strength of the composite hydrogel increased by 6.4 times compared to the pure PVA hydrogel; meanwhile, it showed a high sensitivity (GF = 1.40, strain range 0–5%; GF = 1.67, strain range 5–20%) and rapid response time (<0.05 s). This study presents a novel approach to developing bio-based, flexible sensing materials. Full article

Antioxidant nanomaterials, particularly mesoporous silica nanoparticles (MSNs) functionalized with polyphenols, offer innovative solutions for protecting oxidation-sensitive components and enhancing bioavailability in pharmaceuticals or extending the shelf life of nutraceutical and food products. This study investigates the influence of MSNs functionalized with caffeic acid (MSN-CAF) on powder flow properties and their tableting performance. Aminated MSNs were synthesized via co-condensation and conjugated with caffeic acid using EDC/NHS chemistry. Antioxidant capacity was evaluated using DPPH^●, ABTS^●+, ORAC, and FRAP assays. Powder blends with varying MSN-CAF concentrations (10–70%) were characterized for flow properties (angle of repose, Hausner ratio, Carr’s index), tablets were produced via direct compression, and critical quality attributes (weight uniformity, hardness, friability, disintegration, nanoparticle release) were assessed. MSN-CAF exhibited reduced antioxidant capacity compared with free caffeic acid due to pore entrapment but retained significant activity. Formulation F1 (10% MSN-CAF) showed excellent flowability (angle of repose: 12°, Hausner ratio: 1.16, Carr’s index: 14%), enabling robust tablet production with rapid disintegration, low friability, and complete nanoparticle release in 10 min. Additionally, the antioxidant nanomaterial demonstrated biocompatibility with the HepG2 cell line. MSN-CAF is a versatile nanoexcipient for direct compression tablets, offering potential as an active packaging agent and delivery system in the nutraceutical and food industries. Full article

This study presents an analytical and experimental approach to enhance cantilever-based piezoelectric energy harvesters by optimizing thickness distribution. Using a gradient projection algorithm within a state-space framework, the unimorph beam’s geometry is tailored while constraining the first natural frequency. The objective is to amplify axial strain within the piezoelectric layers, thereby increasing electric polarization and maximizing the conversion efficiency of mechanical vibrations into electrical energy. The steady-state response under harmonic base excitation at resonance was modeled to evaluate the harvester’s dynamic behavior against uniform-thickness counterparts. Results show that the optimized beam achieves significantly higher output voltage and energy harvesting efficiency. Simulations reveal effective strain concentration in regions of high piezoelectric sensitivity, enhancing power generation under resonant conditions. Two independent experimental setups were employed for empirical validation: a non-contact laser vibrometry system (Polytec 3D) and a first resonant base excitation setup. Eigenfrequencies matched within 5% using a Polytec multipath interferometry system, and constant excitation tests showed approximately 30% higher in optimal shapes electrical potential value generation. The outcome of this study highlights the efficacy of geometric tailoring—specifically, non-linear thickness shaping—as a key strategy in achieving enhanced energy output from piezoelectric harvesters operating at their fundamental frequency. This work establishes a practical route for optimizing unimorph structures in real-world applications requiring efficient energy capture from low-frequency ambient vibrations. Full article

Chinese lacks explicit word boundary markers, creating frequent temporary segmental ambiguities where character sequences permit multiple plausible lexical analyses. Skilled native (L1) Chinese readers resolve these ambiguities efficiently. However, mechanisms underlying word segmentation in second language (L2) Chinese reading remain poorly understood. Our study investigated: (1) whether L2 readers experience greater difficulty processing temporary segmental ambiguities compared to L1 readers, and (2) whether visual boundary cues can facilitate ambiguity resolution in L2 reading. We measured the eye movements of 102 skilled L1 and 60 high-proficiency L2 readers for sentences containing temporarily ambiguous three-character incremental words (e.g., “音乐剧” [musical]), where the initial two characters (“音乐” [music]) also form a valid word. Sentences were presented using either neutral mono-color displays providing no segmentation cues, or color-coded displays marking word boundaries. The color-coded displays employed either uniform coloring to promote resolution of the segmental ambiguity or contrasting colors for the two-character embedded word versus the final character to induce a segmental misanalysis. The L2 group read more slowly than the L1 group, employing a cautious character-by-character reading strategy. Both groups nevertheless appeared to process the segmental ambiguity effectively, suggesting shared segmentation strategies. The L1 readers showed little sensitivity to visual boundary cues, with little evidence that this influenced their ambiguity processing. By comparison, L2 readers showed greater sensitivity to these cues, with some indication that they affected ambiguity processing. The overall sentence-level effects of color coding word boundaries were nevertheless modest for both groups, suggesting little influence of visual boundary cues on overall reading fluency for either L1 or L2 readers. Full article

This study presents a novel multi-material additive manufacturing (MMAM) strategy by combining virgin polylactic acid (vPLA) with recycled polylactic acid (rPLA) in a layered configuration to improve both performance and sustainability. Specimens were produced using fused deposition modelling (FDM) with various vPLA: rPLA ratios (33:67, 50:50, and 67:33) and two distinct layering approaches: one with vPLA forming the external layers and rPLA as the core, and a second using the reversed arrangement. Mechanical testing revealed that when vPLA is used as the exterior, printed components exhibit tensile strength and elongation improvements of 10–25% over conventional single-material prints, while the tensile modulus is largely influenced by the distribution of the two materials. Thermal analysis shows that both vPLA and rPLA begin to degrade at approximately 330 °C; however, rPLA demonstrates a higher end-of-degradation temperature (461.7 °C) and increased residue at elevated temperatures, suggesting improved thermal stability due to enhanced crystallinity. Full-field strain mapping, corroborated by digital microscopy (DM) and scanning electron microscopy (SEM), revealed that vPLA-rich regions display more uniform interlayer adhesion with minimal voids or microcracks, whereas rPLA-dominated areas exhibit greater porosity and a higher propensity for brittle failure. These findings highlight the role of optimal material placement in mitigating the inherent deficiencies of recycled polymers. The integrated approach of combining microstructural assessments with full-field strain mapping provides a comprehensive view of interlayer bonding and underlying failure mechanisms. Statistical analysis using analysis of variance (ANOVA) confirmed that both layer placement and material ratio have a significant influence on performance, with high effect sizes highlighting the sensitivity of mechanical properties to these parameters. In addition to demonstrating improvements in mechanical and thermal properties, this work addresses a significant gap in the literature by evaluating the combined effect of vPLA and rPLA in a multi-material configuration. The results emphasise that strategic material distribution can effectively counteract some of the limitations typically associated with recycled polymers, while also contributing to reduced dependence on virgin materials. These outcomes support broader sustainability objectives by enhancing energy efficiency and promoting a circular economy within additive manufacturing (AM). Overall, the study establishes a robust foundation for industrial-scale implementations, paving the way for future innovations in eco-efficient FDM processes. Full article

To meet the growing demand for secure and reliable image protection in digital communication, this paper proposes a novel image encryption framework that addresses the challenges of high plaintext sensitivity, resistance to statistical attacks, and key security. The method combines a two-dimensional dynamically coupled map lattice (2D DCML) with elementary cellular automata (ECA) to construct a heterogeneous chaotic system with strong spatiotemporal complexity. To further enhance nonlinearity and diffusion, a multi-source perturbation mechanism and adaptive DNA encoding strategy are introduced. These components work together to obscure the image structure, pixel correlations, and histogram characteristics. By embedding spatial and temporal symmetry into the coupled lattice evolution and perturbation processes, the proposed method ensures a more uniform and balanced transformation of image data. Meanwhile, the method enhances the confusion and diffusion effects by utilizing the principle of symmetric perturbation, thereby improving the overall security of the system. Experimental evaluations on standard images demonstrate that the proposed scheme achieves high encryption quality in terms of histogram uniformity, information entropy, NPCR, UACI, and key sensitivity tests. It also shows strong resistance to chosen plaintext attacks, confirming its robustness for secure image transmission. Full article

Pump-driven liquid cooling systems are widely utilized in unmanned aerial vehicle (UAV) electronic thermal management. As a critical power component, the miniaturization and lightweight design of the pump are essential. Increasing the operating speed of the pump allows for a reduction in impeller size while maintaining hydraulic performance, thereby significantly decreasing the overall volume and mass. However, high-speed operation introduces considerable internal flow losses, placing stricter demands on the geometric design and flow-field compatibility of the impeller. In this study, a miniature high-speed centrifugal pump (MHCP) was investigated, and a multi-objective optimization of the impeller was carried out using response surface methodology (RSM) to improve internal flow characteristics and overall hydraulic performance. Numerical simulations demonstrated strong predictive capability, and experimental results validated the model’s accuracy. At the design condition (10,000 rpm, 4.8 m³/h), the pump achieved a head of 46.1 m and an efficiency of 49.7%, corresponding to its best efficiency point (BEP). Sensitivity analysis revealed that impeller outlet diameter and blade outlet angle were the most influential parameters affecting pump performance. Following the optimization, the pump head increased by 3.7 m, and the hydraulic efficiency improved by 4.8%. In addition, the pressure distribution and streamlines within the impeller exhibited better uniformity, while the turbulent kinetic energy near the blade suction surface and at the impeller outlet was markedly decreased. This work provides theoretical support and design guidance for the efficient application of MHCPs in UAV thermal management systems. Full article

In this study, we present a novel surface-enhanced Raman scattering (SERS) substrate based on porous silicon microcavities (PSiMCs) decorated with silver nanoparticles (AgNPs) for ultra-sensitive molecule detection. This substrate utilizes a dual enhancement mechanism: the localized surface plasmon resonance (LSPR) of AgNPs and the optical resonance of the PSiMC structure, which together create intense electromagnetic hot spots and prolong photon–molecule interactions. The porous architecture provides a large surface area for uniform nanoparticle distribution and efficient analyte adsorption. The AgNP/PSiMC substrate demonstrates an impressive detection limit of 1.0 × 10⁻¹³ M for rhodamine101 and 1.0 × 10⁻¹⁰ M for methyl parathion, outperforming many previously reported SERS platforms. Furthermore, the substrate exhibits excellent signal uniformity (RSD ≈ 6.14%) and long-term stability, retaining over 50% signal intensity after 28 days. These results underscore the potential of AgNP/PSiMCs as highly efficient, reproducible, and scalable SERS platforms for trace-level chemical and environmental sensing applications. Full article

Medical images demand robust privacy protection, driving research into advanced image encryption (IE) schemes. However, current IE schemes still encounter certain challenges in both security and efficiency. Fractional-order Hopfield neural networks (HNNs) demonstrate unique advantages in IE. The introduction of fractional-order calculus operators enables them to possess more complex dynamical behaviors, creating more random and unpredictable keystreams. To enhance privacy protection, this paper introduces a high-performance medical IE scheme that integrates a novel 4D fractional-order HNN with a differentiated encryption strategy (MIES-FHNN-DE). Specifically, MIES-FHNN-DE leverages this 4D fractional-order HNN alongside a 2D hyperchaotic map to generate keystreams collaboratively. This design not only capitalizes on the 4D fractional-order HNN’s intricate dynamics but also sidesteps the efficiency constraints of recent IE schemes. Moreover, MIES-FHNN-DE boosts encryption efficiency through pixel bit splitting and weighted accumulation, ensuring robust security. Rigorous evaluations confirm that MIES-FHNN-DE delivers cutting-edge security performance. It features a large key space ($2^{383}$), exceptional key sensitivity, extremely low ciphertext pixel correlations (<0.002), excellent ciphertext entropy values (>7.999 bits), uniform ciphertext pixel distributions, outstanding resistance to differential attacks (with average NPCR and UACI values of $99.6096\%$ and $33.4638\%$, respectively), and remarkable robustness against data loss. Most importantly, MIES-FHNN-DE achieves an average encryption rate as high as 102.5623 Mbps. Compared with recent leading counterparts, MIES-FHNN-DE better meets the privacy protection demands for medical images in emerging fields like medical intelligent analysis and medical cloud services. Full article