Advanced Engineering Materials最新文献

The aim of this research is to validate a new prototyping method for microfluidic devices which could compete with the widely used polydimethylsiloxane soft lithography. This alternative methodology uses laser-etched glass and pre-cured silicone as main materials. A dual approach is chosen for validation, testing prototypes of a mixing device well known in the scientific literature. Specifically the focus is to evaluate the mixing efficiency (ME) of two fluids flowing through the device. After fine-tuning the fabrication process, the ME is experimentally evaluated, and the results are compared with a 3D computational fluid dynamic analysis.

This review examines the state-of-the-art sensors and sensing technologies employed for structural health monitoring (SHM) in aerospace composites, highlighting the shift from conventional nondestructive evaluation techniques to real-time monitoring systems. The review discusses the challenges associated with composite materials, such as their anisotropic nature and susceptibility to invisible damage, and how these challenges have driven the improvement of SHM techniques. Fiber-optic sensors, including interferometric, distributed, and grating-based sensors, are analyzed for their high sensitivity and multiplexing capabilities, making them suitable for distributed sensing applications. Piezoelectric sensors are evaluated for their effectiveness in both active and passive damage detection methods. At the same time, piezoresistive self-sensing systems are explored for their potential to integrate sensing directly into composite materials. The review also addresses the challenges encountered in implementing SHM systems. It suggests solutions like protective coatings, advanced data processing algorithms, and modular system design to overcome these challenges. In conclusion, this review provides a comprehensive overview of the current SHM technologies for aerospace composites, underscoring the need for sustained research and development to improve sensor technology, expand data processing capabilities, and ensure seamless integration with aircraft systems, thus contributing to the safety and efficiency of aerospace operations.

Two steps strategy were taken to effectively produce porous Si₂N₂O/SiC ceramics: 1) direct foaming combined with sol-gel curing at room temperature to form a green body, and 2) sintering assisted by in-situ production of Si₂N₂O fibers under microwave sintering conditions. Non-toxic silica sol was used to provide silicon source for in-situ synthesis of Si₂N₂O, the silica sol could form a gel that stabilizes the bubbles, creating a porous structure. A thorough investigation was conducted into how different sintering temperatures affected the microstructure, flexural strength, and porosity of the porous Si₂N₂O/SiC composites. The main bonding phase in the porous composites was the Si₂N₂O with fiber morphology. The optimal microwave sintering temperature for fabricating porous Si₂N₂O/SiC ceramics, using a combination of sol-gel and direct foaming techniques, has been determined to be 1200 °C. At this temperature, the porosity can be controlled between 73.32% and 83.16% by proportionally adjusting the ratio of the raw materials. Under the condition of high porosity, the thermal radiation is dominant and the thermal conductivity increases with the increase of temperature. With the decrease of porosity, the heat conduction is dominant, and the thermal conductivity decreases with the increase of temperature.

In the quest for lightweight high-performance metallic materials in transportation, the limitations of high-strength Al-based alloys in high-temperature (HT) applications have posed a significant challenge. To overcome this long-standing bottleneck, an innovative design strategy, combining entropy-driven compositional design and rapid solidification processing, to develop “Al-based superalloys” with a γ/γ′ duplex microstructure reminiscent of Ni-based superalloys is presented. By incorporating multirefractory elements (Ti, Zr, Hf, Nb, and Ta) into the alloy design, a high-volume fraction of thermally stable coherent γ′ phase for strengthening the Al-rich face-centered cubic matrix from room temperature (RT) to temperatures close to the melting point is achieved. The developed Al-based superalloys exhibit exceptional specific yield strength and specific Young's modulus, surpassing aerospace aluminum, cobalt, nickel, and titanium alloys from RT to HT. Moreover, our ultra-strong alloys demonstrate deformability and exhibit fine-dimpled fracture behavior. The versatility of our fundamental research on Al-based superalloys demonstrates their potential and can inspire further research in this field. This work opens new possibilities for the development of next-generation lightweight alloys with novel microstructures and outstanding mechanical properties.

In photocatalysts aimed to degrade environmental pollutants, photons are generally used as primary stimuli to generate electron–hole pairs to target the chemical bonds to disintegrate. Recently, electron spin has been reported as an essential degree of freedom to improve the performance of photocatalysts. In this work, spin-polarized electrons and holes are introduced into a brownmillerite KBi_0.9Co_0.1Fe₂O₅ semiconductor and a two-dimensional (2D) MXene composite system by application of an external magnetic field. The spin polarization properties are monitored by measuring the magnetoresistance effect of the MXene-KBCFO device, which is related to the carrier transfer efficiency. Remarkably, the photocatalytic performance of MXene-KBCFO is significantly enhanced by the simultaneous application of an external magnetic field and illumination due to the increased number of spin-polarized photoexcited carriers caused by the synergy effect of the 2D MXene heterostructure together with the ferromagnetic spin ordering. This results in increased reaction hotspots, effective built-in electric field, extended carrier lifetime, and reduced charge recombination owing to parallel alignment of electron spin orientation. The results show that the efficiency and stability of photocatalytic dye degradation can be effectively enhanced by manipulating the spin-polarized electrons in the MXene-based oxide-perovskite heterostructure photocatalyst.

The present study assists the industrial sectors by implementing low-weight high-strength aluminium composite. The pristine magnesium as a reinforcement in three different weight percentages (3.5, 7, and 10.5) is utilized to fabricate the A 413 composite using centrifugal casting. The density analysis concludes a higher level of Mg inclusion prompts the material to save 3.9% of weight. Microstructural study of centrifugal casting specimens reveal a rich existence of hard phase Mg₂Si in the outer zone, with its richness decreasing toward the inner zone. The tensile test result affirms the functionally graded nature of the material with the increasing trend of tensile strength from the inner to the outer. Fractured surface analysis concludes the existence of cracks and their propagation for the inner region specimen. The influence of magnesium on the surface finish of functionally graded composite at the wire cut electric discharge machining (WEDM) zone is predicted using a machine learning-based random forest regressor (RFR) algorithm. The supervised learning algorithm declares that 10.5 wt% of Mg facilitates the minimal surface roughness of 0.229 µm with the optimal combination of parameters 6 A of current, 115 µs of pulse-on time, 60 µs of pulse-off time, and 8 N of wire tension.

Flexible compressible sensors are widely used in the human health monitoring field for their numerous advantages. However, the dynamic loads and possible injuries associated with long-term living and exercise pose a challenge to the long-term piezoresistive performance stability of these sensors. In this study, the application of deep learning for predicting the long-term performance of these sensors is explored, aiming to enhance the assessment of sensor stability and ensure accurate and reliable long-term monitoring. Samples with different Ti₃C₂T_x MXene/aramid nanofiber mass ratios (1:1, 1:2, 1:3) are prepared and piezoresistive characterization is conducted under long-term loading cycles to obtain training data. Three distinct deep-learning prediction models, convolutional neural network (CNN), long short-term memory, and recurrent neural network (RNN), are utilized to assess their influence on prediction accuracy. To assess the effectiveness of the proposed method, its prediction of long-term piezoresistive sensing performance with experimental data not used for training purposes is compared. The CNN model demonstrates optimal results with a mean absolute error of 0.0251 for the 1:3 mass ratio sample. Based on the experimental results, the model is expected to be integrated into human health monitoring systems, thus improving the assessment of sensor stability throughout its lifetime.

Special wetting surfaces have attracted attention owing to their potential applications in the automotive, engineering, environmental, and biomedical industries. Specifically, nature-inspired superhydrophobic surfaces are more effective in blocking moisture, thus limiting corrosion. Hence, surface wettability analysis remains the primary method for demonstrating the corrosion mitigation characteristics of rough-engineered surfaces. Herein, the influence of wettability measurements on the corrosion inhibition of 316L stainless steel surfaces etched in HCl: HNO₃ acid is systematically investigated. Interestingly, etched hydrophobic surfaces with a contact angle of ≈125° significantly improve the corrosion resistance by 50%, resulting in suppressed corrosion rates. Furthermore, the surface chemical states of the etched 316L steel are analyzed and discussed in detail.

Herein, the tribological behavior of 316L stainless steel (SS) fabricated using metal extrusion additive manufacturing (MEAM) is investigated both under dry and simulated body fluid (SBF)-lubricated conditions. The results and mechanisms are compared with those of 316L SS fabricated via selective laser melting (SLM) and hot rolling (HR). Under dry-friction conditions, the 316L SS fabricated via MEAM shows inferior tribological performance compared with those fabricated via SLM and HR, primarily because of its lower initial hardness and better plasticity, which increase both abrasive and adhesive wear. Under SBF-lubricated conditions, the tribological performance of the 316L SS fabricated via MEAM is comparable to that fabricated via HR and superior to that fabricated via SLM. The wear rate of the MEAM-fabricated 316L SS is 16.8% and 3.2% lower than SLM- and HR-fabricated, respectively. The numerous pores on 316L SS serve as traps for wear particles, which contribute to the reduction of three-body wear. In terms of wear under SBF-lubricated conditions, MEAM technology appears to be a promising method for the fabrication of customized 316L orthopedic implants.

The microstructural evolution and mechanical properties of cast Al–Li–Cu–Cd–Mn–Zr–Ti alloy during heat treatment are investigated systematically. In these findings, it is shown that the as-cast alloy exhibits fine and equiaxed grains. During the solid solution treatment, Al₂₀Cu₂Mn₃ dispersoids effectively restrict grain growth, and reducing the solid solution time has a similar effect. Subsequently, the precipitation behavior and its effect on the mechanical properties during the aging process are revealed. Al₃(Ti, Zr) particles are uniformly distributed throughout the matrix, acting as nucleation sites for δ′, θ′, and T₁ precipitates. Overtime, δ′ precipitates gradually coarsen and decrease in number, and some δ′ precipitates attach to Al₃(Ti, Zr) particles, forming core–shell Al₃(Li, Ti, Zr) phases. At the same time, plate-shaped θ′ and T₁ precipitates emerge and coarsen. After aging at 160 °C for 24 h, the alloy exhibits an excellent combination of strength (yield strength =293.3 ± 4 MPa, ultimate tensile strength =468.0 ± 3 MPa) and ductility (elongation =9.6 ± 0.4%), surpassing those reported in other cast Al–3Li–2Cu–X alloys. Critically, the underlying mechanisms behind the microstructure and mechanical properties are discussed extensively, providing valuable insights for the advancement of cast Al–Li alloys.