Advanced Engineering Materials最新文献

Reduced graphene oxide (rGO) reinforced copper (Cu) matrix composites were produced using arc induction melting (AIM) to investigate the microstructural, mechanical, tribological, and electrical responses of the system. rGO additions of 0.5 and 1.0 wt% were introduced to clarify interfacial strengthening and functional synergies within the Cu matrix. Characterization through X-ray Diffraction, Scanning Electron Microscopy, Energy-Dispersive X-ray Spectroscopy, Atomic Force Microscopy, and Lateral Force Microscopy confirmed homogeneous rGO dispersion, refined grain structure, and the absence of undesirable secondary phases. Incorporating rGO led to a significant increase in hardness, rising from 65 ± 4HV30 for pure Cu to 225 ± 3HV30 for the composite containing 1 wt% rGO. This improvement is associated with Hall–Petch strengthening, Orowan looping, and effective interfacial load transfer. Tribological evaluations demonstrated up to 78% reduction in wear rate and more than 60% decrease in friction coefficient, linked to the formation of a stable, self-lubricating carbonaceous tribofilm. SEM/EDX analyses of worn surfaces confirmed the presence of a continuous protective carbon layer. Electrical conductivity showed a slight improvement, maintaining the structural integrity of the Cu–rGO interface. Overall, AIM proved to be a scalable and energy-efficient approach for fabricating dense and multifunctional Cu–rGO nanocomposites suitable for electromechanical and thermal management applications.

Advancing multifunctional mechanical metamaterials requires harmonizing auxetic behavior (negative Poisson's ratio, NPR) with high-energy absorption (EA) capabilities. This study presents a snowflake-perforated honeycomb metamaterial where radial buckling activates NPR-driven EA enhancement. Plastic hinges at 45° ligaments initiate auxetic contraction, while NPR-induced transverse compression forces hierarchical folding, delaying densification and amplifying energy dissipation. Geometric parameters (a/b, d) tune this cooperative mechanism within an optimal design window, enabling NPR to intrinsically reinforce EA. Integrated experiments and simulations confirm that NPR actively elevates EA through biaxial strain constraints and extended folding sequences. Parametric studies establish aspect ratio (a/b) as the primary regulator of NPR-EA synergy, while inscribed diameter (d) governs structural stability. A gradient design strategy further leverages NPR-induced compaction through spatially coordinated parameters, maximizing multifunctional performance. This work pioneers a tunable metamaterial paradigm where NPR fundamentally fortifies impact protection.

Textile-based wearable sensors are gaining popularity in healthcare and soft robotics due to their rapid, scalable, and low-cost production. Among them, strain sensors have been drawing attention in various human motion detection and health monitoring applications. In this article, knitted strain sensors based on interlock structures have been fabricated for capturing human movement and their remote monitoring. To achieve high stretchability and electrical stability, elastic core spun (nylon/PU) with conductive (polyester/stainless steel) yarn has been realized to prototype the sensors. Six different samples with different yarn variations have been extensively investigated by various electromechanical characterizations. The developed strain sensors show a maximum gauge factor of 3.04 with excellent linearity (R² = 0.9911) and remarkable durability of 1500 cycles. These sensors also demonstrate rapid response (≈80 ms) and recovery time (≈120 ms) and exhibit good performance after 10 wash cycles, assessing the real-world application of the sensors. To validate the applicability of the strain sensors in human motion monitoring, an elbow support guard and a kneecap have been constructed to demonstrate bending angle detection as well as wireless monitoring of various human locomotion. The developed strain sensors hold immense possibilities in health monitoring, physical rehabilitation, and sports applications.

Porous tantalum scaffolds with composite pore structures, combining cubic and dodecahedron unit cells, are designed and fabricated using electron beam powder bed fusion. The static compressive and compressive fatigue properties of these composite scaffolds, featuring varying combination directions, are systematically investigated. Notably, under the equal strain condition, the elastic modulus and compressive yield strength of the composite scaffold are 0.95 GPa and 41.5 MPa, respectively, which are higher than scaffold under equal stress state. During fatigue tests, initial failure initiates within the weaker dodecahedron structure under the equal stress model. Following the complete failure of this structure, local tensile stress induces fracture in the struts of the cubic, resulting in a compressive fatigue strength lower than that of a uniform dodecahedral structure. Conversely, under the equal strain model, the composite scaffold demonstrates reduced cyclic ratcheting strain and a slower crack propagation rate during compressive fatigue, contributing to its compressive fatigue strength of 30.1 MPa at 2 × 10⁶ cycles, which is much higher than the scaffold under equal stress condition. These findings demonstrate the effectiveness of strain-matched composite pore design in improving the mechanical reliability of porous tantalum scaffolds, offering valuable insights for advanced implant development.

The quenching method significantly affects the mechanical properties of Al–Mg–Si–Cu alloy energy-absorbing boxes. This study examines the inherent mechanism of the quenching process's action while methodically examining how it affects mechanical properties of the alloy's energy-absorbing boxes. The results demonstrate that, in comparison to samples treated with air cooling (AC), the mechanical properties of those treated with online water cooling (WC) are substantially improved. Specifically, the WC samples achieve optimal levels of tensile strength, elongation, and fracture toughness and perform well overall. Comparing it to the AC samples, its tensile strength (383.1 MPa), bending angle (148.6°), and peak crush load (410.4 kN) are all enhanced by 21.3%, 38.3%, and 31.3%, respectively. In this study, it is found that rapid cooling significantly inhibits the diffusion of solute atoms into the crystal, and more vacancies and solute atoms are obtained. This helps create the narrow grain boundary, precipitate-free zone, and aging-strengthening precipitation of dense and fine β″ phases. In addition, the WC quenching process inhibits crack propagation, which ultimately results in WC samples exhibiting high strength along with high toughness. This guarantees that the energy-absorbing box profiles has outstanding plastic deformability and energy-absorbing qualities under bending and crushing loads.

Comprehensive materials characterization requires precise structural knowledge beyond traditional methods. The robot-assisted automated serial-sectioning and imaging (RASI) platform, developed at BAM, provides automated 3D metallographic reconstructions, enabling detailed microstructural analysis of technical materials. This article showcases RASI's capabilities through several case studies, including characterization of lamellar graphite in gray cast iron, porosity in sintered steel, melt pool morphology in additively manufactured 316L stainless steel, defects in metal-ceramic packages, and oxidation behavior in an Fe-12Cr-2Co alloy. By automating sample handling, mechanical serial-sectioning, etching, and optical imaging, RASI captures complex 3D microstructures with high precision and at high speed. This approach reveals microstructural features missed by 2D analysis, even using stereological assumptions. Specifically, statistically rare and large microstructural features, such as secondary phases or interconnected pores, become apparent, which 2D methods cannot reveal. The generated volumetric data can furthermore serve as quantitative reference datasets (i.e., the ‘ground truth’) essential for validating other 3D characterization techniques and computational models, helping to bridge the gap between predictive simulations and real-world material behavior. RASI's modular design makes it a flexible tool that provides realistic 3D insights into materials, which can be used for advanced materials research, process optimization, and quality control.

This work presents a comprehensive experimental and analytical study of twisted and coiled artificial muscles (TCAMs) fabricated from three types of silver-coated nylon 6,6 precursor fibers. The coupled thermo-electromechanical response of these actuators is investigated through systematic characterization and a physics-based analytical model. Built upon Castigliano's theorem, the model captures nonlinear contraction behavior with high accuracy while remaining computationally efficient compared to more complex formulations. Experimental validation demonstrates maximum contractions up to 19.3%, strongly influenced by precursor type and the applied prestrain. Beyond displacement, actuator performance is quantified through additional metrics. The specific mechanical work per cycle reaches values as high as 8 kJ kg⁻¹, highlighting the excellent work density achievable with minimal actuator mass. Conversely, electromechanical efficiency is found to be limited (0.15 ± 0.2% under optimized conditions), primarily due to thermal losses resulting from convection, radiation, and conduction. Time-constant analysis reveals fiber-dependent trends: Thinner fibers exhibit faster overall dynamics but slower heating than cooling, while thicker fibers display longer relaxation times due to their larger thermal mass. The combined experimental and analytical approach provides both a detailed understanding and a predictive tool for TCAMs, offering insights into their strengths and limitations for future integration into wearable and soft robotic systems.

At present, the research on the overall residual stress of additively manufactured superalloy components still faces challenges. This study systematically investigates the influence of annealing temperature on the evolution behavior of residual stress in IN718 superalloy fabricated via selective laser melting using X-ray diffraction and the contour method, and analyzes the mechanism of residual stress relief in combination with microstructure characterization. The results indicate that there is significant tensile stress on the surface of the as-built sample, and the longitudinal stress (σ_z) is higher than the transverse stress (σ_x). Internal stress primarily consists of compressive residual stress. However, after annealing treatment, most residual stress is alleviated through static recovery and recrystallization. Under medium-low temperature (550–750 °C) annealing, recrystallization does not occur and the recovery capacity is relatively weak; thus, residual stress is partially relieved, reaching 20% and 50% respectively. Under high-temperature (950–1150 °C) annealing, residual stress is significantly reduced, up to 90%. Especially at 1150 °C, dislocation is almost completely annihilated, recrystallization is mostly completed, and residual stress is nearly eliminated, approaching 0 MPa. The results provide technical support for the annealing process to eliminate residual stress in the superalloy.

Bone tissue repair requires biomaterials that possess excellent biocompatibility, bioactivity, and mechanical strength. Polyamide 66 (PA 66) and nanohydroxyapatite (n-HA) show promise as scaffolds in this field, but improving composite construction methods to enhance performance is still a key challenge. In this article, an n-HA/PA66 composite material is prepared using a simple and environmentally friendly method. Subsequently, a patient-specific artificial vertebra is developed utilizing advanced 3D printing techniques. Characterizations, including scanning electron microscopy and transmission electron microscopy, have identified the nanostructure of n-HA/PA66 material. Fourier transform infrared spectroscopy reveals the covalent binding of n-HA to PA66. Further Raman spectroscopy and X-ray diffraction analyses confirm the crystalline nature and uniformity of the material. The result of thermal stability determinations suggests that the vertebral body material remains structurally intact at temperatures below 300 °C. Compared with the traditionally made artificial vertebrae, the 3D-printed vertebra exhibited more superior mechanical properties. It has been demonstrated that the 3D printing technique enhances the mechanical capability of n-HA/PA66 material. By integrating n-HA/PA 66 with 3D printing, artificial vertebrae can be custom-designed for specific bone defect locations and sizes, addressing large bone defect issues in clinical settings and offering significant clinical potential.

Comprehensive materials characterization requires precise structural knowledge beyond traditional methods. The robot-assisted automated serial-sectioning and imaging (RASI) platform, developed at BAM, provides automated 3D metallographic reconstructions, enabling detailed microstructural analysis of technical materials. This article showcases RASI's capabilities through several case studies, including characterization of lamellar graphite in gray cast iron, porosity in sintered steel, melt pool morphology in additively manufactured 316L stainless steel, defects in metal-ceramic packages, and oxidation behavior in an Fe-12Cr-2Co alloy. By automating sample handling, mechanical serial-sectioning, etching, and optical imaging, RASI captures complex 3D microstructures with high precision and at high speed. This approach reveals microstructural features missed by 2D analysis, even using stereological assumptions. Specifically, statistically rare and large microstructural features, such as secondary phases or interconnected pores, become apparent, which 2D methods cannot reveal. The generated volumetric data can furthermore serve as quantitative reference datasets (i.e., the ‘ground truth’) essential for validating other 3D characterization techniques and computational models, helping to bridge the gap between predictive simulations and real-world material behavior. RASI's modular design makes it a flexible tool that provides realistic 3D insights into materials, which can be used for advanced materials research, process optimization, and quality control.