Composites Part A: Applied Science and Manufacturing最新文献

Though the micro-structure of 3D printed short carbon fiber reinforced thermoplastic (SCFRTP) composites is well reckoned to have a great influence on their mechanical performances, the existing models are deficient in considering microscopic factors and thus large errors existed in their predictions. In this work, the effects of micro-structure on the mechanical properties of 3D printed SCFRTP composites are systematically analyzed. The microscopic representative volume elements (micro-RVEs) of 3D printed SCFRTP composites with fibers of probability density distributed length and void defects are established using the modified random sequential adsorption (RSA) algorithm based on experimental results. The present model (m-RVE_{fv_d}) can evaluate the mechanical performances of 3D printed SCFRTP composites more accurately and effectively compared with the existing models that did not consider the effects of void defects and fiber probability density distributions. In addition, it is observed that as the fiber content increases, the average length of short fibers decreases while the content of void defects increases. When fiber content is less than 5 wt%, the composite mechanical properties are dominated by fiber content; as the fiber content exceeds 5 wt%, the composite mechanical properties are mainly affected by microscopic defects. Finally, a strategy is proposed for achieving high mechanical performance SCFRTP composites based on the systematical mechanical analyses conducted in this work.

It is necessary to segment fiber bundles in the reconstruction of the mesoscopic model of ceramic matrix composites using XCT images. Existing methods have great subjectivity, poor recognition accuracy, and heavy workload. To solve this problem, an improved lightweight YOLOv8 was proposed, which is a deep learning approach. By adding Slim-neck and VanillaNet, the complexity of the model was greatly reduced. Additionally, by replacing the loss function of the model with the Wise-IoU loss function, the ability of feature extraction of the model was improved. The effectiveness of the improved YOLOv8 in fiber bundle identification was demonstrated. Finally, a mesoscopic model was reconstructed by XCT images where fiber bundles were segmented by using the improved YOLOv8. The linear elastic modulus of the material was predicted and the error was found to be small, indicating that the improved YOLOv8 can effectively segment fiber bundles and thus reconstruct a high-precision mesoscopic model.

Developing new-form factor devices has led to the creation of foldable and rollable displays. However, next-step stretchable devices with shape changes face a new issue different from conventional displays. When the screen is stretched, screen distortion occurs due to the nature of contraction perpendicular to the stretching direction to preserve the volume. To address this issue, we focused on the composite approach with mechanical anisotropy using continuously aligned fiber fillers. In this study, we fabricated transparent mechanically anisotropic stretchable substrates with near-zero Poisson's ratio by incorporating continuous and aligned transparent ribbon arrays within a transparent, stretchable matrix. The aligned ribbon-reinforced composite substrates have mechanical anisotropy by mainly reinforcing stiffness only in the ribbon-aligned direction. When unidirectional stretchable devices in the direction perpendicular to the alignment are developed, the stiffness of the substrate contracting in the ribbon alignment direction is relatively high compared to the vertical direction, and thus the vertical displacement is diminishing, so substrates with Poisson's ratio close to 0 can be realized. Based on this approach, we realized a light-emitting device (LED) array system with near-zero vertical distortion by attaching LED arrays and printed intrinsically stretchable interconnections on our mechanically anisotropic composite substrate.

Temperature-dependent tensile properties of carbon-fiber-reinforced polyetherketoneketone (CF/PEKK) composites with varying width-to-diameter (W/D) ratios in open-hole (OH) and bolted joint (BJ) were investigated. CF/PEKK exhibited higher modulus and strength at lower temperature due to restricted polymer chain mobility, and lower values at elevated temperature due to increased polymer ductility. OH net tensile strength decreased with decreasing W/D, with strain retention dropping significantly at W/D ≤ 2. The approximate average strain concentration factor determined from digital image correlation slightly exceeded theoretical values due to semi-crystalline nature of PEKK. Distinct failure behaviors highlighting the complex interplay between temperature, W/D, and failure characteristics. Evaluating W/D and temperature effects on BJ CF/PEKK revealed changing failure modes. Bolted joint efficiency emphasizing the need to optimize W/D ratios above 2 to achieve high efficiency. These findings highlight the geometry and temperature interplay affects CF/PEKK composites, which are crucial for designing high-performance materials, especially for aerospace applications.

As polypropylene (PP) is a competitive insulating material for next generation high-voltage cable, the corresponding PP based cable semi-conductive shielding layer material needs to be developed. This paper developed an excellent material prescription and proposed an analytical method of structure-performance relationship for the application and the evaluation of PP-based cable shielding layer. First, PP/POE/CB and PP/SEBS/CB composites with different carbon black (CB) loading were prepared and their electrical and mechanical properties were compared. Through thermal analysis technique, crystalline property and thermal stability of the composites were studied in detail. And the synchrotron radiation X-ray scattering techniques were employed to analyze the distribution of carbon black in the blend semi-quantitatively. The analysis result turns out the enrichment of carbon black in POE phase and its instability at high temperature limits its application under cable operation conditions. In contrast, PP/SEBS/CB30phr is recommended for lower thermal deformation, lower PTC effect and better mechanical parameters.

Despite the known influence of chemical composition on the mechanical properties of basalt fibers, a clear understanding of this relationship is lacking. Chemical composition analysis and mechanical property tests are performed on basalt fiber samples. Test data is collected from various countries and regions to expand the dataset. An improved Physics-Informed Neural Network (PINN) approach is specifically designed to address the complexities of this relationship. By incorporating physical models like the Makishima-Mackenzie model, Rocherulle model and a symbolic regression formula, the PINN leverages established physical principles to enhance its ability to understand the underlying mechanisms governing the influence of chemical composition on mechanical properties. This focus on physical mechanisms not only improves the interpretability of the model but also empowers it to make accurate predictions, as evidenced by the high squared correlation coefficients of 0.8767 and 0.8145 between predicted and experimental values of modulus and strength, respectively.

Thermal energy harvesting, storage, conversion and utilization technologies based on phase change materials (PCMs) have received widely attention. The intelligent integration of PCMs with functional carriers or nano-additives enables the application of energy such as thermal, light, electricity and magnetism in different fields. Herein, we discuss strategies for the preparation of multifunctional composite PCMs with enhanced properties, including PCMs selection, encapsulation carrier design, thermal performance optimization, and functional integration methods. The latest progress of advanced applications of multifunctional composite PCMs in the fields of thermal management, thermal protection, medical, energy saving, and thermal camouflage is reviewed. The multifunctional design characteristics of PCMs for different applications are emphasized, as well as the relationship between the structure and thermo-physical properties of multifunctional composite PCMs. Finally, the remaining challenges of multifunctional composite PCMs and the fields that need to be broken through for advanced applications are envisioned.

This study proposes a novel topology optimisation method based on the Geometry Projection Topology Optimisation method (GPTO) with the consideration of manufacturing constraints for the 3D printing of continuous fibre reinforced polymer composite structures. The proposed method uses connecting bars in chains to represent the continuous fibre filaments in the composite structure, as opposed to the use of separate bars as primitives. Thus, the method is termed as Chain Projection Topology Optimisation (CPTO), in which the chain-like primitives are equivalent to clusters of real printing paths. The 3D printing paths can be acquired by splitting the primitives evenly, which simplified the printing path design procedure to a great extent. In addition, manufacturing constraints can be easily imposed on the primitives, making it superior to density-based topology optimisation methods. An MBB beam, a cantilever beam, and a bridge case are optimised to demonstrate the CPTO’s efficiency. It was found that the designs by CPTO possess comparable mechanical properties when compared to those by the Solid Orthotropic Material Penalization (SOMP) method while guaranteeing the composite structures are suitable for 3D printing and contain less microscopic defects in the printed fibre filaments.

Achieving a balance between strength and toughness is a vital requirement for the development of high-performance fiber-reinforced composites. Inspired by nature, this study integrates biomimetic intermittent porous carbon nanotubes (PCNT) structure into the composite for synergistically enhancing its strength and toughness. It was found that the interfacial shear strength, interfacial fracture toughness, 45FBT tensile strength, and interlaminar fracture toughness of the intermittent porous structure-coated fiber/resin composites obtained significant increases of 63.4%, 107.7%, 31.2%, and 64.3% than the baseline composites, respectively. The strengthening effect was contributed by the synergistic enhancement of the interfacial bonding areas and mechanical interlocking morphologies, as well as the significant frictional stresses induced by the morphological mismatches between adjacent gaps. The toughening mechanism was associated with the micro-crack formation, the PCNT structure rupture, and the crack deflection during the crack propagation. This work provides a promising pathway to overcome the trade-off between strength and toughness.

The percolation inception of CNT-polymer nanocomposites is studied considering the magneto-electric field effects on CNT subbands. The analytical model predicts the electrical conductivity where CNTs are modeled as slender rods with their geometric orientations as randomly distributed or aligned to transfer electrons at tunneling distance range. The tunneling effect takes into account the electron transmission between every linked pair of CNTs when evaluating electrical resistance. The subsequent CNT displacement computation and the resistance change comprise the other phase of the modeling approach. Piezoresistivity results of the analyses agree well with the experimental data when considering tunneling behavior in the percolation transition zone. The magnetic field enhances the field affected subbands and increases the electrical conductivity by enhancing the mobility of the charges. The results reveal that the efficiency of CNT network in transmitting charges is increased with higher aspect ratio CNTs that scaled the sensitivity to lower values.