Journal of Composite Materials

Optimized process parameters of a top–down approach via the ultrasonic dual-mode mixing process are adopted to disperse and exfoliate graphene nanoplatelets uniformly in the epoxy resin and fabricate hybrid GFRP laminates. The in-plane tensile and out-of-plane flexural behavior of the hybrid GFRPs made with different concentration of GNPs have been investigated. The test results show that ∼39.47% and ∼40.87% enhancement in tensile strength and flexural strength has been attained for the hybrid GFRPs made with 1 wt% of GNPs. In addition, the enhancement of ∼117% in absorbed failure energy and ∼28.56% in work of fracture is also achieved. Mori Tanaka Method has been used to calculate the modulus of the GNP-epoxy composite system, and these results are used further to predict the modulus of the hybrid GFRPs. The theoretical moduli so obtained are used to compare the experimental modulus of the hybrid GFRPs as a function of GNP concentration. Fractography examination of the fractured hybrid GFRPs reveals it reduced interlaminar delamination, which is governed by the effective load transferability of GNP-infused epoxy network.

In this study, carbon fiber/thermoplastic (Elium^®) honeycombs were manufactured using the resin infusion process in a customized metallic mold. Honeycomb cores, based on different carbon fiber layers, were manufactured to achieve four different fiber weight fraction composites. Two different types of specimens, based on a single honeycomb cell and five honeycomb cells, were prepared and subjected to compression loading. The results of these tests were compared with data from similar honeycomb structures based on carbon fiber–reinforced epoxy composite. It has been shown that the compressive strength and the specific energy absorption capacity of the honeycombs increase rapidly with increasing fiber weight fraction. The specific energy absorption capability of the novel thermoplastic honeycomb structures has been shown to be as high as 50 kJ/kg which compares favorably with other energy-absorbing core materials. The thermoplastic honeycomb specimens exhibited a similar specific energy absorption capability and an improved compressive strength compared to their epoxy counterparts. Furthermore, the CF/thermoplastic honeycombs exhibited enhanced structural stability and displayed a more uniform and progressive core failure mode than the longitudinal splitting observed in the CF/epoxy honeycombs. The honeycomb core that exhibited the best performance was then used to manufacture thermoplastic sandwich specimens based on CF/thermoplastic face sheets. Three point bend tests were conducted to determine the flexural strength of the sandwich samples and to identify the failure modes. Optical micrographs revealed that the flexural damage was primarily due to the core crushing and adhesive failure between the core and the composite skins.

Siloxane-modified cyanate ester resins are ideal matrix materials for next-generation, high-precision composites used for radomes and satellite structures. They provide extremely low moisture uptake, excellent microcracking resistance, and protection from atomic radiation. However, cyanate ester resins have been shown to be susceptible to hydrolysis during cure, which may significantly impact both mechanical and thermal performance. In this investigation, we evaluate the cure kinetics and hydrolysis susceptibility of a siloxane-modified prepreg system (TC410/M55J). DSC tests verified that the E_a of polymerization for the TC410 system is 65 KJ/mol. Samples were also exposed to moisture during cure at several temperatures, and FTIR was used to follow changes in the carbonyl peak absorption intensity to compare the rate kinetics and activation energy for hydrolysis leading to carbamate formation (52 KJ/mol). DMA tests of composites exhibited significantly reduced Tg’s with increasing moisture levels during cure. TGA of these cured samples exhibited both a significant decrease in the onset of the thermal decomposition temperature as well as an increase in the relative degree of volatiles generated at low temperature. Flatwise tension strength tests showed a linear reduction in strength with decreasing Tg, at an equivalent trend to previous work on an M55J/RS3C system indicating a similar mechanism. However, the added margin provided from the higher initial FWT strength in the TC410 system allows for larger decreases in Tg before significant degradation occurs. Laminates manufactured on composite mandrels resulted in parts with larger decreases in the tool-side Tg of the part when compared to the bag-side Tg, with the differential depending on the initial moisture content of the tool. AFM was shown to selectively identify these carbamate-affected regions by showing that the recession behavior of these less cross-linked areas was greater than in areas where the resin was properly cured. Composites with increased carbamate formation resulted in increasing warpage of the part with elevated temperature exposure due to variations in stress relaxation. This effect should be considered when manufacturing precision, high-dimensional stability composite hardware.

The present article aims to re-derive a (de-)homogenization model for particularly investigating the behavior of thin laminated plates withstanding transverse loads. Instead of starting with Kirchhoff-type of assumptions, we directly apply perturbation analysis, in terms of the small parameter introduced by the thinness of composite plates, to the original three-dimensional governing elastostatic equations. The present article sees its intriguing points in the following three aspects. First, it is shown that transverse loads applied on a thin laminated plate induce an in-plane stress response, which essentially differs from the case of single-layered homogenous plates. A scaling law estimating the magnitude of the in-plane stresses due to transverse loads is then given, and a size effect in such induced in-plane stresses arises. Second, the stress state at any position of interest in the original three-dimensional configuration can be asymptotically estimated following a (de-)homogenization scheme, and the (de-homogenization) accuracy is shown, both theoretically and numerically, to be at a same order of magnitude as the thickness-to-size ratio. Third, the asymptotic analysis here identifies the right order of magnitude for the transverse normal strain, which is often set to vanish, leading to the so-called Poisson’s locking problem in classical thin plate theories.

To overcome the brittle fracture of ceramic matrix composites, the interfacial coatings between continuous fibers and the ceramic matrix, especially boron nitride (BN) and silicon carbide (SiC) coatings were often introduced into the composites to improve the interface properties. This work focused on the use of chemical vapor infiltration (CVI) and precursor infiltration and pyrolysis (PIP) to fabricated SiC fiber-reinforced SiC (SiC_f/SiC) minicomposites with interfacial coatings. Single BN, double-layered BN/SiC, and multi-layered (BN/SiC)₂ interfacial coatings were deposited on SiC fibers from BCl₃-NH₃-H₂ and MTS (Methyltrichlorosilane)-H₂ systems in a low pressure hot-wall CVI reactor. Room-temperature tensile testing was used to evaluate the influence of different interfacial coatings on the tensile properties and failure mechanism of SiC_f/SiC minicomposites. The minicomposites with (BN/SiC)₂ coatings performed the highest fracture strength of 630.9 MPa. The mechanical behaviour of the composites was characterized by the universal testing machine with an acoustic emission (AE) detector, a scanning electron microscope (SEM), and an energy dispersive X-ray spectrometer (EDS). The existence of (BN/SiC)₂ coatings provoked the interface debonding in the minicomposite both at the BN/fiber interface and the interface between BN and SiC layers, prolonging the crack propagation paths and noticeably improving the fracture properties of the minicomposite.

Materials design and development continue to be more relevant as applications continue to rise for additively manufactured carbon-fiber-reinforced-plastic (CFRP) composites. Plastic matrixes bond and protect the fiber and help to transfer load through the composite to support intended applications. This makes it more necessary to understand the influences of thermoplastic matrixes on the mechanical performance of the composites fabricated through the additive manufacturing (AM) technique. This study investigated Acrylonitrile–Butadiene–Styrene (ABS) and Polyamide (PA) matrixes, which represent the bulk of the amorphous and semicrystalline engineering-grade thermoplastics matrixes, respectively, used in CFRP composite applications. Mechanical properties: tensile, compression, flexural, and thermal properties were examined, with the results showing the thermoplastic matrixes compositions and morphologies influences on the mechanical properties. The CF-PA was found to offer superior strength, ductility, and toughness because of their close-packed ordered lamellar matrix morphology, while the CF-ABS was found to offer superior modulus because of their loose morphology which more easily rearrange in reaction to stress upon elastic deformation. The mechanical properties results were reinforced by the fracture failure modes and the thermal analysis results which showed the CF-PA composite’s ability to withstand higher mechanical performance and temperatures before failure.

Natural fiber-reinforced composites (NFRC) are cheaper and more eco-friendly alternatives compared to synthetic composites for automotive applications. As there is limited understanding about the balance of different physical properties in NFRC, optimizing these properties is an important consideration for a more widespread application of NFRC. The goal of this research was to statistically develop an optimum formulation for oat-hull-reinforced polypropylene composite. Mechanical properties of the composites were first experimentally measured. Then, the mixture design experiment approach was utilized to generate response models for different properties, and diagnostic tools were utilized to validate the models. In addition to optimizing the desired material properties, the overall cost of the composite was minimized, which adds novelty to the work.

Machine learning (ML) has emerged as a useful predictive tool based on mathematical and statistical relationships for various engineering problems. The pairing of structural health monitoring (SHM) and nondestructive evaluation (NDE) methods with ML algorithms has yielded beneficial results in addressing the damage state of a material or system. Damage state descriptions addressed with ML include detecting a damage mechanism, locating a mechanism, identifying the type of mechanism, assessing the extent of the damage mechanism, and estimating the useful remaining life of a material or system. Damage evaluation research of composite materials has progressed with the increased usage of composite structural elements in the aerospace industry. NDE methods are a viable candidate for pairing with ML algorithms to improve damage state monitoring of composite materials due to the complexity associated with the structure of composites. Fiber-reinforced polymers (FRP), for example, contain at least two constituent materials a fiber and matrix material whose mechanical behavior and interactions contribute to the performance of an FRP. Unlike conventional composite analytical models that require explicit information about the constituents and microstructure of a laminate, an ML algorithm can construct damage evaluation predictions when employing exclusively past operational performance or data from an SHM or NDE method. A researcher determines the type of data selected when applying an ML model for trend analysis, anomaly detection, or prediction making. However, no one specific input feature is required for utilizing an ML model, and examples of possible data features include material properties, physical dimensions, and collected evaluation data. In the present review, applications of ML combined with the damage state evaluation of composite materials, particularly examining FRPs, are discussed to demonstrate the predictive capabilities of ML and its viability for future applications, especially in industrial environments, to minimize costs and improve damage detection rates.

Nanocomposites based on graphene oxide (GO) or reduced graphene oxide (rGO) grafted with hollow gold nanoshells (HGNs) were developed as enhanced photothermal agents with improved biocompatibility. Infrared and Raman spectroscopy allowed determining that graphene was highly oxidized due to the presence of oxygenated groups that allowed further functionalization and provided anchor points for the grafting of HGNs. Using HRTEM and STEM, good dispersion of the HGN on the surface of the graphitic materials was observed. Meanwhile, using UV–Vis spectroscopy, an increase of absorbance in the near-infrared region was appreciated, resulting in an enhancement of the photothermal properties of the nanocomposites in contrast to the materials separately. Remarkable temperature increases were obtained in short periods of irradiation using a low-power laser. Moreover, a decrease in the cytotoxicity of GO and rGO was observed in the human neuronal line hNS1 under the presence of the plasmonic nanoparticles on the surface.