This study investigates two incorporation techniques for integrating high concentrations (2-6 wt%) of industrial-grade mass-produced graphene into glass fibre-reinforced unsaturated polyester composites to create multiscale composites with enhanced functionality. The incorporation methods compared were direct mixing of graphene into the resin matrix and spray coating of graphene suspension onto fibre surfaces, along with a hybrid approach combining both techniques. A fabrication methodology for the multiscale composites was developed to address processing challenges associated with high graphene concentrations and increased resin viscosity. Mechanical characterization revealed that flexural strength and modulus decreased by up to 15 % and 9 %, respectively, with fibre-coated composites showing greater deterioration than resin-mixed samples. In contrast, interlaminar shear strength (ILSS) increased by up to 12 % when graphene was directly mixed into the resin, due to toughening of resin-rich mid-plane in the laminate structure. Fibre coating, however, resulted in reduced mechanical properties due to impaired resin infiltration and increased void content, as confirmed by optical microscopy and permeability measurements, which showed a decrease from 1.3 x 10-11 m2 for the neat preform stack to 3.8 x 10-12 m2 for the fibres coated with 4 wt% graphene. Electrical conductivity analysis demonstrated that graphene-coated fibre multiscale composites achieved the lowest percolation threshold at 2.7 wt%, compared to 3.1 wt% for resin-modified composites, attributed to preferential localisation of graphene along fibre surfaces. These findings provide important insights into the relationship between graphene incorporation technique, resulting microstructure, and composite properties in high-concentration multiscale systems.

The thermal expansion behaviour of short-fibre-reinforced 3D-printed (SFR 3DP) composites has been studied primarily through analytical models focusing on the longitudinal direction, whereas the transverse behaviour has received limited attention. In addition, full-field finite element (FE) modelling of thermal expansion in SFR 3DP composites remains relatively uncommon. In this study, the coefficient of thermal expansion (CTE) of SFR 3DP composites, specifically polycarbonate with various levels of glass fibre reinforcement, is predicted using five analytical models (Turner, Kerner, Schapery, No-Interaction (NI), and Mori-Tanaka (MT)) alongside full-field FE models, and the results are compared with thermo-mechanical analysis (TMA) data in both longitudinal and transverse directions. In the longitudinal direction, the Schapery model is most accurate at low fibre contents, the MT model at higher contents, while the FE model remains highly accurate across the entire range. In the transverse direction, the MT model provides virtually identical accuracy to the FE model at every fibre content. Overall, the analytical approaches can match the predictive power of full-field FE modelling for CTE of SFR 3DP composites. Longitudinally, the FE method remains the more general tool, whereas the accuracy of analytical models is more sensitive to fibre content. Transversely, both approaches perform equally well.

Compared to pin-driven thermoplastic melt impregnation for fibre-reinforced tape manufacture, a cross-head slot channel die with crests can be used to reduce polymer degradation and tape porosity. In a slot channel, polymer melt is driven from the gate to the die exit by a static pressure gradient and drag at the fibre-tow interface. To inform the wavy slot die design, this paper augments pin-assisted melt impregnation models to introduce a process model combining static pressure in the melt, wedge-driven pressure, and crest pressure. Between crests, pressure develops in the wavy channel, analogous to theoretical pin-driven models. The static pressure gradient in the slot with a moving tow was examined by computational fluid dynamics. Parametrically studying the pulling speed, number of crests, crest length, melt viscosity, and melt inlet velocity shows that the interactive trends significantly change depending on the static pressure. When static pressure dominates, parameters that raise driving pressure, such as melt viscosity and melt inlet velocity, substantially improve the impregnation. Additionally, extended residence time by increasing the crest length and the number of crests improves the degree of impregnation. Meanwhile, wedge-driven impregnation is principally enhanced by the number of crests. The model is calibrated to fit experimental results using a single theoretical parameter when applying (i) Kozeny-Carman’s general permeability or (ii) Bruschke and Advani’s theoretical transverse permeability. Since static pressure in the wavy slot channel strongly benefits impregnation, the introduced model can inform the die design and operating conditions needed to elevate static pressure for minimum porosity.

Thermoplastic sandwich panel structures have extensively been used in automobiles, aerospace, construction, civil and marine engineering for decades, attributable to their high strength-to-weight ratio and lightweight yet durable framework. This, however, causes significant volume of waste generation adversely affecting the environment. Present research is an attempt to mitigate this issue and enable sustainable practices, by recycling the entire thermoplastic sandwich structures and remanufacture them, thus minimizing waste production and optimizing materials value. Principal challenge, however, lies in heterogeneity of the materials used in sandwich panels production. To tackle this, first, the properties of constituent materials were investigated followed by subsequent re-manufacturing of new panels by compression moulding. Process optimization was performed employing Response Surface Methodology (RSM) with the Box-Behnken Design (BBD) approach. The analysis of variance (ANOVA) test was conducted to assess the accuracy of mathematical models derived from experimental data. To alleviate thermal degradation during the recycling process, recycled materials were blended with neat polycarbonate (PC) at controlled weight ratios. Afterwards, the properties of newly developed recycled panels were evaluated through thermal analysis, rheology, and mechanical tests. Results revealed that no detectable mass-loss degradation below 300 degrees C (TGA), while rheology analysis indicates minor early-stage molecular reduction at elevated processing temperatures (285 degrees C). Among all the compositions, the recycled panel with 10% PC content exhibited the highest mechanical performance, a storage modulus of 8.3 GPa. The findings indicate that the manufactured recycled panels not only retained but also enhanced their thermal and mechanical properties, making them suitable for various applications. This research highlights promising advancements in improving the recyclability and circular use of thermoplastic sandwich structures.

Thermoplastic composites (TPCs) can be joined via welding due to their ability to be melted, enabling both assembly and repair. When the interfacial temperature exceeds the glass transition or melting temperatures (𝑇𝑔 or 𝑇𝑚 for amorphous and semi-crystalline materials, respectively), the polymer viscosity decreases, enabling polymer chain inter-diffusion (healing) across the interface, while applied pressure ensures intimate contact. Interfacial temperature is an important parameter that influences weld quality. In this context, the Thermo-Adhesion by COnductive heating of composite MAterials (TACOMA) bench is used to investigate the interfacial healing behaviour, effect of resin content, and fracture toughness of AS4 carbon fibre (CF) poly ether(imide) (PEI) and poly ether ether ketone (PEEK) substrates welded with the Thermabond™ process using one or two PEI interlayers. Increasing the PEI content enhances the Mode I interlaminar fracture toughness and reduces the welding time required to attain full degree of healing. Process maps that relate the healing temperature and the contact time to degree of healing and fracture toughness are established, providing a framework for process optimization. These results support the development of robust, process-driven methodologies for thermoplastic composite welding and repair.

This study explores part geometrical deviations with manufacturing strategies for composite materials, focusing on highly reactive thermoset resins processed through Resin Transfer Moulding (RTM). A simulation framework that integrates the filling stage and stress-deformation analysis using a thermo-viscoelastic (TVE) model was developed to improve the understanding of material behaviour and its impact on part quality. The influence of key process parameters, including process temperature, nominal injection pressure, number of plies, and ply stacking sequence, was investigated for part geometrical deviations. The results show that the ply stacking sequence and the number of plies are the most significant factors affecting part geometrical deviation. In contrast, process temperature and injection pressure had only a minor effect. This work demonstrates the potential of the proposed simulation approach as a reliable tool for guiding experimental implementation and improving part quality when using highly reactive thermosets.

Cyanate esters are key thermosetting resins for composite materials that require structural integrity and resistance to elevated temperatures. Because cyanate ester composites require relatively high processing temperatures, they are susceptible to the formation of process-induced residual stresses, which compromise their overall strength and durability. Process modeling is a key strategy for optimizing processing parameters to minimize such residual stresses. A necessary component of effective and efficient process modeling of composites is computationally established resin property evolution relationships for a range of processing parameters. In this study, the physical, mechanical, and thermal properties of a cyanate ester resin are established as a function of processing time and temperature using experimentally validated molecular dynamics modeling. The results show that the properties are strongly dependent on the processing temperature. At processing temperatures above 160 °C, the properties quickly approach their fully cured values, whereas at processing temperatures below 140 °C, the chemical cross-linking is significantly inhibited, and processing times to complete cure are relatively long. The evolution of the physical, mechanical, and thermal properties as a function of processing time is established, which is critical data needed as input into multiscale process modeling and optimization of cyanate ester composites for computationally driven composite design.

In the collaborative effort towards standardisation of out-of-plane permeability measurement, an international benchmarking exercise was carried out whereby 19 participants worldwide were instructed to measure the out-of-plane permeability following a number of strict guidelines, informed by the outcomes of the first international benchmarking exercise completed in 2021. This paper presents the results of the exercise and an assessment of the reproducibility of the data and the suitability of the proposed test method. The data returned were subjected to a number of statistical analysis methods, which showed that adherence to the test guidelines resulted in a high likelihood of a participant not being an outlier and therefore providing evidence that the test method proposed in this paper is a suitable way forward for a standardised test method.

Recent advances in cost-effective graphene mass production highlight its potential for industrial applications, along with the challenges of achieving and controlling uniform dispersion at a large scale. State-of-the-art approaches such as functionalization, solvent mixing, and sonication are costly for large-scale use. As for dispersion analysis, microscopy techniques such as scanning electron microscopy and transmission electrical microscopy are still commonly employed, while emerging quantitative methods, including electrical conductivity measurements, micro-CT, and machine learning, remain time-intensive and are limited to fully-cured nanocomposites. This study aims to evaluate three mixing techniques-mechanical mixing, high shear mixing, and probe sonication-for dispersing an industrial mass-produced graphene powder in an unsaturated polyester resin. Their impact on processing parameters is examined using thermal and rheology analysis. Furthermore, dispersion states throughout the processing window are quantified for the first time. Results indicate that graphene addition inhibits resin curing, delaying gelation and increasing peak temperatures. Mechanical mixing exhibited the lowest dispersion efficiency with dispersion indices of 62.87%, 65.15%, and 66.37% at 0.25, 0.5, and 0.75 Wt.% graphene, respectively. Probe sonication was most effective at lower concentrations (66.65% and 68.20% at 0.25 and 0.5 Wt.%), while high shear mixer excelled at 0.75 Wt.% graphene (69.11%) due to increased viscosity. The dispersion states remained stable during curing, as the resin's higher viscosity restricted nanofiller mobility.Highlights Graphene delays resin curing (5.8%-40%) by radical scavenging and hindrance. Objective method for quantitative graphene dispersion across processing window. Better dispersion obtained using high shear mixer at higher graphene content. High resin viscosity stabilizes graphene dispersion, limits mobility in curing.

This work presents the development of a comprehensive model to describe the cure kinetics and viscosity behaviour of polyester-based resin systems used in liquid composite moulding applications. The model accounts for both inhibition and diffusion effects, providing a unified equation that simplifies the complex integral expressions often required in sequential or piecewise approaches. Thermogravimetric analysis (TGA), Differential Scanning Calorimetry (DSC), and rheological characterization were performed to assess the thermal stability, curing behaviour, and viscosity changes over a range of isothermal temperatures. Time-temperature graphs generated by the model highlight critical regions for processing, including the processability window and the rapid crosslinking region. These insights are crucial for optimizing process parameters in the large-scale manufacturing of composite parts, particularly for complex geometries.

This study explores the optimization of extrusion process parameters for fabrication of short glass fibrereinforced polycarbonate filaments suitable for Fused Filament Fabrication. Employing Response Surface Methodology, the effects of fibre content, screw speed, and die temperature on mechanical properties and dimensional stability of filaments were investigated. This work introduces the application of Digital Image Correlation directly on filaments during tensile testing, contributing to the development of advanced filament characterization techniques. The optimal parameters-10 wt% fibre content, 40 rpm screw speed, and 239.9 degrees C die temperature-achieved a balance between high tensile modulus, high tensile strength, and minimal diameter deviation. The optimal processing condition led to a 148 % increase in tensile modulus, while maintaining good tensile strength and acceptable diameter deviation. Overall, fibre content had the most significant impact on filament properties, followed by screw speed. Fracture surface analysis provided valuable insights about the effects of process parameters on microstructure of the composites.

Compression moulded carbon fibre reinforced sheet moulding compounds aim to maximize the mechanical performance of discontinuous fibre composites, while maintaining low cycle times. The shape of the governs their in-mould flow behaviour, which is one of the most important factors influencing their mechanical performance. While high amounts of flow and the presence of weld lines have been identified as performance detractors, the practical implications of these finding on how charges should be designed yet been investigated in detail. The present study considers different charge configurations based on challenges that arise when balancing repeatable high performance and manufacturing efficiency in an industrial The influence of these configurations on the local internal microstructure is measured with micro-computed tomography and closely associated with the corresponding local mechanical performance measured digital image correlation. While a charge closely resembling the part indeed yields the most reliable isotropic results, some in-mould flow aids in evacuating trapped gases and is in many scenarios to piecing together charges from sheet moulding compound patches, thus introducing weld lines. Notably, even charge coverage is important, to avoid local complex flow patterns, which highly distort the and constitute significant weak spots.

The demand for advanced thermoplastics in three-dimensional (3D) printing is growing, particularly in fields that require materials with exceptional mechanical strength and dimensional stability. However, many commercially available filaments for 3D printing fail to meet these stringent requirements. This study aims to develop polymer blends of polyphenylene sulfide and polycarbonate that can be optimized for extrusion-based 3D printing to overcome these limitations. The research utilizes a compatibilizer to enhance phase dispersion and interfacial adhesion, thereby improving printability and end-use performance. The blends (filament form) were processed via twin extrusion for fused filament fabrication. Thermal analyses (differential scanning calorimetry and thermogravimetric analysis) revealed enhanced phase compatibility and thermal stability in the compatibilized blends. Rheological measurements indicated reduced melt viscosity and improved shear-thinning behavior, while mechanical tests demonstrated increased tensile strength and elongation at break. Microscopy and spectroscopy confirmed reduced phase separation and chemical interactions at the interface. These results suggest that compatibilized polyphenylene sulfide-polycarbonate blends as promising candidates for high-performance applications in aerospace, automotive, and biomedical sectors.

The demand for high-performance polymers in 3D printing continues to grow due to their ability to produce intricate and complex structures. However, commercially available high-temperature 3D printing materials often exhibit limitations such as brittleness, warping, thermal sensitivity, and high costs, highlighting the need for advanced filament development. This study investigates the fabrication of polyetherimide (PEI) and polycarbonate (PC) blends via melt extrusion to enhance material properties for stable additive manufacturing. The addition of PC improved the processability of the blends, enabling successful extrusion at temperatures ranging from 290 to 310 °C. Differential scanning calorimetry (DSC) confirmed a shift in the softening temperature (T) of PEI, indicating effective blending. To further improve the properties of the PEI:PC blends, 1 wt% of a compatibilizer was incorporated, resulting in homogeneous microstructures as observed through scanning electron microscopy (SEM). The optimized PEI:PC (70:30) blend with compatibilizer (1 wt%) demonstrated a 49% higher storage modulus than neat PEI and a 40% greater storage modulus than ULTEM9085. Moreover, reduced melt viscosity facilitated consistent and stable printing, making these materials highly suitable for applications in aerospace and transportation, where performance and reliability are critical.

Compression resin transfer moulding (CRTM) has been widely used to manufacture automotive parts with reduced production cycle times. With the development of fast curing thermosetting resins, the CRTM process is a viable option for the high production rates in the transportation industry. However, the dynamic resin curing behaviour poses a potential risk of manufacturing defects in the part. In order to reduce the risk during the development of the tool and the process parameters, this paper proposes a modelling framework for the CRTM process when using fast curing resin systems. The work specifically focused on the coupling between heat transfer, resin cure, resin flow and preform compaction using a commercial code, PAM-RTM. The tool captures accurately the preform filling, temperature and resin pressure evolution during the injection and compression phase. The application of the framework was demonstrated for a complex 3D demonstrator. The predicted preform filling had an accuracy of 73% for the flow front evolution compared to the experimental results. This work demonstrates the validity of the framework proposed when dealing with resin systems that are challenging to process.

Fibre-cell-based fibre structure characterization approach was proposed recently to characterize the fibre distribution within discontinuous-fibre reinforced polymer matrix composites (DFR PMCs) over a 2D domain. This approach determines the distribution state of each fibre based on the relative size and topological features of its fibre cell. In this study, the fibre-cell-based approach is extended for 3D fibre domains. A convolutional neural network (CNN) encoder is trained through contrastive learning to quantitatively represent topological features of 3D fibre cells. Subsequently, the feature-property correlations are established using an artificial neural network (ANN). For practical application, the ANN is integrated with an image analysis software to provide in situ predictions of local elastic modulus of a DFR PMC based on its fibre structures observed from micro-CT images. The predictions are also compared with the experimental measurements acquired through microindentation testing, and it shows a good agreement.

This paper presents a methodology for developing thermo-mechanical properties model for highly reactive resins and its use for Resin Transfer Moulding process (RTM) modelling and prediction of residual stresses. Cure Hardening Instantaneously Linear Elastic (CHILE), and Thermoviscoelastic (TVE) models, were implemented to analyze the mechanical behaviour of the resin. Simulation of the RTM process was developed and applied to a representative curved plate geometry. An integral approach was considered where the degree of cure gradient, generated during the filling stage due to the reactivity of the resin, was implemented as initial condition of the stress-deformation process simulation. The validation process included fabricating experimental parts with the representative geometry. The degree of cure variation of highly reactive thermosets during injection caused a significant effect on the final shape of the parts. These effects were captured by the simulations, where the TVE model showed a more accurate prediction of the part distortion.

A novel algorithm based on radial basis functions is proposed for the removal of artifactual fibre overlap within fibre structures extracted from micro-computed tomography (micro-CT) images of fibre reinforced polymer matrix composites. The proposed algorithm is highly efficient and excels in preserving the original fibre structures extracted from the micro-CT images. Besides, graphics processing unit (GPU) acceleration is applied to further enhance the efficiency of the fibre overlap removal process. Furthermore, the proposed algorithm is also modified for the generation of periodic 3D microstructures. For practical application, the proposed algorithm is implemented for both the artifactual fibre overlap removal within micro-CT images from an injection moulded part and the microstructure generation for 3D printed samples. The unidirectional elastic modulus of the resultant microstructures is computed via numerical simulations and shows a close match to the experimental measurements with relative errors less than 2%. Overall, the proposed algorithm significantly facilitates the reconstruction of micro-CT image-based numerical models and can also be easily repurposed to generate complex microstructures, which is of great value for the development of data-driven models for characterization and design of composite materials that demands large amounts of data on material microstructures.

Recent advancements in mass production of graphene powders utilize less energy-intensive methods and milder chemicals compared to traditional lab-scale techniques. This can influence the properties of the resulting graphene particles. This study investigates the effect of mass-produced graphene powder on the curing and rheological properties of a resin transfer molding (RTM) grade unsaturated polyester resin. An objective dispersion quantification method was established to track the dispersion state of the nanocomposite throughout the curing process. The findings reveal that the graphene powder accelerated the curing evidenced by a shift in the peak temperature and gel point towards lower values. The sample containing 1 wt.% graphene exhibited remarkable dispersion stability with only 7.1% decrease by gelation. The resin matrix's low viscosity enhanced graphene particles mobility, while its fast-curing nature allowed less time for agglomeration.