Thermoset Composites Research Articles

Z-printing of continuous fiber-reinforced thermoset composites: The process development, and mechanical properties evaluation

This study presents a process development and mechanical characterization for through-the-thickness yarns (TTYs) incorporated into continuous fiber-reinforced thermoset composites (CFTCs) using a 3D printing system with photopolymer curing technology. Two types of CFTCs were prepared with different ply orientations and placement of TTYs. The mechanical properties of the samples were evaluated through three-point flexural strength tests and numerical simulations. The experimental and numerical results exhibited acceptable agreement up to the first peak of the reaction force. The presence of TTYs reduced the maximum stress and altered the failure mechanisms, while improving resistance to delamination cracking. The energyabsorption capacity of the samples with TTYs was increased by 23% to 53%. However, the flexural strength of the samples decreased by 14% to 23% with the incorporation of TTYs due to the formation of small sections with low fiber content around TTYs and the concentration of von Mises stress.

Thermoplastic and thermoset polymer matrix composites reinforced with bismuth oxide as radiation shielding materials

Polymer composites reinforced with heavy metals have wide applications in the nuclear industry as radiation shielding materials against emitted radiation from nuclear equipment. In this study, considering bismuth oxide as reinforcement, various polymers including thermoplastic polymers, such as high-density polyethylene, low-density polyethylene, polypropylene, polyvinyl acetate, polymethyl methacrylate, and thermosetting epoxy resin have been considered as matrices. After preparing various samples of polymer composites loaded with 60 % by weight of bismuth oxide, some physical, mechanical, and radiation shielding properties (neutron and gamma attenuation coefficients) of these polymer composites have been measured and compared with each other. First, the density of the samples was measured, and the response of these samples to varying compressive force was investigated. The stress-strain diagrams of composites with different matrices were compared. Subsequently, the linear and mass attenuation coefficients of the composites were measured over a wide range of energies (32–1480 keV) against direct and collimated beams from various standard gamma-ray sources (134Cs, 60Co, 154Eu, 133Ba, and 22Na) using an HPGe detector. A collimated beam from an Am–Be source was utilized to measure and compare the attenuation properties of the composite samples against neutron flux. Furthermore, the properties of the composites against neutron and gamma radiation were calculated using the MCNP Monte Carlo code over a broad energy range, and the results were compared and validated with the experimental data. The comparison of the calculated and measured results shows reasonable agreement. The results indicate that in situations where high attenuation properties coupled with high strength are desired, polymeric composites with an epoxy matrix can be considered as radiation shielding materials. If the use of flexible and malleable material is required, such as for reactor piping shielding or the fabrication of protective gloves and clothing in a radiation environment, among the polymers studied, polyvinyl acetate is a more suitable matrix.

Application of machine learning methods in the analysis of interface bonding strength for overmolded hybrid thermoset‐thermoplastic composites

AbstractThe focus of this study is to apply finite element method (FEM) and machine learning methods to investigate the interfacial bonding strength of continuous fiber reinforced thermoset composite (TSC)‐thermoplastic structures manufactured through co‐curing and overmolding processes, with polyamide 6 (PA 6) as the thermoplastic material. A model for interfacial healing degree in TSC‐PA 6 structures was developed. Then, FEM was employed to study the influence of various injection overmolding process parameters on the interfacial bonding strength of TSC‐PA 6 structures. The results show that there is a strong correlation between the degree of interface healing and the bonding strength. Subsequently, six machine learning methods were employed to correlate interfacial healing degree with diverse injection molding process parameters. Simulation data were utilized for training, calibration, and validation of the six machine learning models. Based on the results of simulation and machine learning predictions, a quantitative analysis of the significance of injection molding process parameters on healing degree was conducted. These parameters are ranked in descending order of importance as follows: insert temperature, melt temperature, and injection rate.Highlights The interfacial healing degree model of PA 6 was established and validated through the integration FEM and experiment. Six machine learning models were built to predict the interfacial healing degree. Grad boosting performed best in predicting the interfacial healing degree. Insert temperature had the greatest impact on the interface healing degree.

Effects of through-thickness dielectric sensor on carbon fibre epoxy cure monitoring

Dielectric sensors are an appealing solution for in-situ cure monitoring of thermoset polymers and thermoset composites. Analysis techniques have been shown to produce highly accurate and repeatable insight into cure state metrics both during and after cure. However, most dielectric sensors only report data on the surface of the material that the sensor is in direct contact with, neglecting the remainder of the thickness of the component. This study evaluates a novel dielectric sensor which is designed with a 20 mm penetration depth to monitor through the thickness of the composite part. While the prototype sensor design was shown to influence the raw data signal, a correction factor was successfully applied, and signals were analysed in accordance with the standard set of dielectric methods. The corrected signal had good accuracy and repeatability across laminates from 2 to 20 mm thick, demonstrating a non-invasive, through-thickness monitoring for a range of part designs.

Additively manufactured 3D short carbon fiber scaffold for thermoset composites

Short-fiber-reinforced polymer composites offer advantages, like flexibility in complex geometries and cost-effectiveness, but typically exhibit lower mechanical properties because of the random orientation of short fibers. In this work, a novel process utilizing shear force to create 3D scaffold with customized fiber alignment for the manufacturing of short carbon fibers (SCF)-reinforced thermoset composites has been presented. The Computed tomography test confirmed the alignment of the SCF along printing directions. The results demonstrate that the aligned SCF-reinforced epoxy composites exhibited a 190% improvement in tensile strength and 388% improvement in tensile modulus compared to neat epoxy.Graphical abstract

Micromechanical Modelling of the Deformation Mechanisms of Friction-Spun Yarn from Recycled Carbon Fibres

The growing use of carbon fibre-reinforced polymers (CFRP) results in an increased amount of CF waste from offcuts or end-of-life components. A promising method to reuse the waste fibre materials in a structural component with excellent mechanical properties is the processing of recycled CF (rCF) and thermoplastic fibres into hybrid yarns. Spinning of friction spun yarns consisting of more than 90% rCF and containing almost no thermoplastic fibres that are suitable for thermoset composites, currently leads to high fibre damage and low yarn quality and is, therefore, addressed in this project. The technology is reported in another paper. One of the limiting factors for drapability of textiles is the stretchability of continuous fibres and draping of the semi-finished textile products for complex geometries is still error-prone. Friction spun yarns exhibit significantly higher yarn elongations due to sliding mechanisms between the fibres. The deformation properties of friction spun yarns are significantly influenced by fibre-fibre interactions and depend on a variety of process and material parameters. In the following, micromechanical finite element models of the spun yarns are created by using beam elements. Monte Carlo method is used to model local variabilities in the yarns. The models are then used to simulate yarn behaviour under deformation and to investigate the influence of various process parameters.

Tensile Properties of Different Yarn Structures Based on Recycled Carbon Fibre for Sustainable Thermoset Composites

The development of different hybrid yarn structures from recycled carbon fibre (rCF) (rCF content approx. 50% by weight) and thermoplastic fibres for thermoplastic composites has been reported earlier. However, manufacturing of yarns with high rCF content (>90%) required for thermoset composites is still not realizable due to high shortening (≥ 70%) in fibre length of rCF, which occurs during different processing steps of spinning. The reason lies in low shear strength, smooth fibre surface, small diameter and high brittleness of rCF. In addition to this, lack of crimp in rCF leads to drafting error during drawing and spinning process. Therefore, there is a high demand on rCF yarns for thermoset composites, as around 70% of composites are produced based on thermoset matrix. In this paper, yarns consisting of staple rCF with high rCF content (>90 weight%) are developed on DREF-friction spinning and wrap spinning technologies. For the production of yarns, slivers with different rCF content are produced using carding and drawing machine. The effect of different spinning parameters suction air pressure for DREF friction spun yarns and yarn twist for wrap spun yarns is investigated and their effect on tensile properties of yarn is analysed. The results show that the tensile properties of yarns can be adjusted to a wide range varying the yarn structure and spinning parameters.

Friction and wear analysis of basalt micro-filler loaded various epoxies and esters based thermoset polymer composites

In this study, thermoset polymers (synthetic epoxy, bio-epoxy, polyester, and vinyl ester) and basalt-reinforced (30 wt%) polymer composites were examined for their hardness and tribological characteristics. Under two levels of basalt weight percentage (0% and 30%), and three levels of load (3, 6, and 9 N), speed (100, 150, and 200 rpm), and distance (100, 150, and 200 m) parameters, the coefficient of friction (COF) and specific wear rate (SWR) are examined. According to the L18 orthogonal array design, which was created using the statistical software MINITAB-19, the tests are carried out using Pin-on-Disk Tribometer as per ASTM G99 standard. The optimum parameters are determined for COF and SWR using Taguchi statistical method. The significance of each parameter and its contribution is analyzed using the ANOVA technique. For synthetic epoxy samples, the optimum set of parameters for the COF response is 30 wt% basalt (2nd rank), 9 N load (4th rank), 100 rpm speed (1st rank), and 150 m distance (3rd rank); for the SWR response, the parameters are 30 wt% basalt (1st rank), 3 N load (2nd rank), 100 rpm speed (4th rank), and 200 m distance (3rd rank). For bio-epoxy samples, the optimum set of parameters for the COF response is 30 wt% basalt (4th rank), 9 N load (1st rank), 150 rpm speed (3rd rank), and 100 m distance (2nd rank); for the SWR response, the parameters are 30 wt% basalt (4th rank), 6 N load (2nd rank), 200 rpm speed (3rd rank), and 200 m distance (1st rank). For polyester samples, the optimum set of parameters for the COF response are 30 wt% basalt (2nd rank), 6 N load (4th rank), 200 rpm speed (1st rank), and 200 m distance (3rd rank); for the SWR response, the parameters are 30 wt% basalt (1st rank), 3 N load (4th rank), 100 rpm speed (3rd rank), and 150 m distance (2nd rank). For vinyl ester samples, the optimum set of parameters for the COF response is 30 wt% basalt (1st rank), 9 N load (3rd rank), 100 rpm speed (4th rank), and 100 m distance (2nd rank); for the SWR response, the parameters are 30 wt% basalt (2nd rank), 6 N load (3rd rank), 100 rpm speed (1st rank), and 100 m distance (4th rank). The ANOVA method demonstrated that the addition of 30 wt% basalt considerably reduced both COF and SWR. The optimum parameters that are not included in the proposed array underwent confirmation tests, and the results showed that the optimum parameters had an error rate that was less than 10% and within the bounds of statistical acceptability. According to the SEM morphology, the basalt particles reduced the material's plastic flow under different processing conditions.

Extraction of Lightweight Platanus orientalis L. Fruit's Stem Fiber and Determination of Its Mechanical and Physico-Chemical Properties and Potential of Its Use in Composites.

Natural fibers extracted from plants are preferred as an alternative to synthetic products. The main reasons for this preference are their affordable cost, light weight and good mechanical properties. However, finding new natural raw materials is challenging due to growth limitations in different geographical areas. Platanus orientalis L. (Eastern plane tree) is a tree with abundant fruits that can grow in many regions of the world. The aim of this study was to determine the mechanical (tensile strength, tensile modulus, elongation), physical (density, fiber diameter) and chemical (cellulose, hemicellulose and lignin) properties of Platanus orientalis L. fruit's stem by fiber extraction from the stems of the tree. It was determined that the extracted fiber had good mechanical properties and cellulose content of 42.03%. As a result of thermogravimetric analysis, it was determined that the plane tree fruit's stem fiber had thermal resistance of up to 299 °C. The tensile strength value was 157.76 MPa, the tensile modulus value was 1.39 GPa and the elongation value was 22.01%. It was determined that it is suitable for use in fiber reinforcement in thermoplastic-based composites at temperatures below 299 °C. According to the results obtained by the mechanical, chemical and physical analysis of Platanus orientalis L. fruit's stem fiber (PoLfs), it could be recommended as a suitable alternative as a reinforcing fiber in thermoplastic and thermoset composites.

Stochastic modelling of out-of-autoclave epoxy composite cure cycles under uncertainty

Thermoset polymers and composites are subject to several sources of uncertainty which can produce a range of cure outcomes. Recent research into stochastically modelled thermoset cure has indicated that accounting for raw material and process uncertainty can model this range of expected output parameters. However, the uncertainty quantification methods are highly test-intensive, and the results of the simulations have been validated with limited experimental data. This study proposes a simple approach to cure kinetics uncertainty quantification that can be applied to any cure kinetics model without the need for additional testing. Stochastic cure kinetics and temperature conditions for a popular out-of-autoclave carbon fibre/epoxy prepreg were used to produce output distribution functions for key cure events, and the results were validated using data from ten cure replicates. The quantified variation expected from the cure of this prepreg resulted in processing recommendations to ensure quality metrics are met during processing.

Prediction of shape distortions in thermosetting composite parts using neural network interfaced visco-elastic constitutive model

The work aims to enhance the capabilities of a Finite Element tool, specifically related to a rheological thermo-chemo-viscoelastic constitutive model. This enhancement is intended to improve the tool’s ability to predict the distortions in composite parts caused by the polymerization of the thermoset composite matrix. These distortions occur due to internal residual stress generated by the inherent anisotropic properties of the thermoset composite material, including coefficients of thermal expansion and chemical shrinkage. The research work’s improvement is tied to the precise modelling of curing behaviour, which literature acknowledges as having a significant impact on manufacturing defects. In order to accommodate the influence of curing behaviour on various process variables—specifically, different thermal loading rates—a neural network model is implemented as an alternative to a standard diffusion cure-kinetics model. The neural network model is trained using Differential Scanning Calorimetry data and is integrated with the classical visco-elastic constitutive model to more accurately predict the progression of distinct thermoset resin states. This transition between cure states is assessed using two cure state variables: the degree of cure and the glass transition temperature. The enhanced predictions of state transitions lead to accurate assessments of internal residual stresses, especially when dealing with thick components subjected to thermal fluctuations. The anisotropic properties of thermoset composites, crucial for numerical analysis, are captured at various stages of cure. Ultimately, this methodology is employed to compare process-induced defects in the case study of the Z-shaped carbon/epoxy woven part, and the defects closely align with experimental measurements.

Coupling effect of ionic liquids on the mechanical, thermal, and chemical properties of polymer composites: A succinct review

AbstractThe growing study of polymer composites has motivated scientists to explore more methodologies to enhance the final demanding properties of polymer composites. Polymer composites have commonly been fabricated using thermosets or thermoplastics with synthetic or natural fillers. Lately, ionic liquids have been applied as coupling agents for polymer composites. In this succinct review, two types of ionic liquids, specifically imidazolium‐ and phosphonium‐based ionic liquids that are applied as coupling agents, are identified. Additionally, the synthesis of ionic liquids with different precursors and reactions is explained. The coupling effect of ionic liquids on the mechanical, thermal, and chemical properties of polymer composites is also succinctly reviewed. The knowledge shown in this review gives a more transparent comprehension of the fabrication of polymer composites coupled with ionic liquids and the essential properties of polymer composites. In conclusion, most imidazolium‐ and phosphonium‐based ionic liquids can improve several mechanical, thermal, and chemical properties of thermoset and thermoplastic composites.

Optimization Techniques in Compression Moulding: A Comprehensive Review

Quality and productivity have been used as terms to control process parameters and lower process defects. Several defects emerge when products are manufactured using the compression moulding process.Since the second-largest industrial process used to produce plastic goods and also the most popular method of producing thermoset and thermoplastic polymer composites is compression moulding.By this method control of temperature and pressure gives the desired shape of product. This method can be applied to both thermoset and thermoplastic materials. Due to the low flow index of thermoset plastics, considerable pressure is needed, which can only be achieved by the compression moulding method.The components, functionality, equipment, and tooling behaviour of the compression moulding process are covered in this study of paper. The advantages, drawbacks, and equipment used, as well as the material processing parameters, part design, tooling, and cost of compression moulding process parts are also discussed.In this work, many process variables—including moulding temperature, pressure, preheat time, and material weight are taken into account for the response research of the mechanical properties and internal defects created by the compression moulding process.

A comparative machinability analysis of polyimine vitrimer, epoxy and polycarbonate polymers through orthogonal machining experiments

End-of-life management of fibre-reinforced thermoset composites is challenging due to the difficult-to-recycle reinforcements and the irreversibly polymerised thermoset matrix; therefore, researchers proposed the vitrimers as a sustainable alternative to thermosetting polymers. Although the early results of the material scientists are promising, the machinability of vitrimers has yet to be explored. Therefore, this paper aims to present a comparative machinability study of polyimine vitrimer, pentaerythritol-based epoxy (PER) and polycarbonate polymers through orthogonal machining experiments. Reflecting on the temperature-dependent properties of vitrimers, the starting temperature of the cutting tool was varied between room temperature and an elevated temperature above 155 °C. The cutting tool was heated by a 2000-W hot air gun until the surface temperature of the cutting tool, monitored by a VariocamHD thermographic IR camera (with Jenoptik IR 1.0/60 LW lens) and checked by a Fluke 51 II thermometer with a type K thermocouple, was permanently above 155 °C for 5 min. The cutting force was measured by a Kistler 9257B dynamometer, and the machined surface was characterised by a Mitutoyo Surftest SJ-400 surface roughness tester and Keyence VHX-5000 (with VH-Z20UT VH lens) microscope. The analysis of variances (ANOVA) results show that the sustainable vitrimer polymer is an appropriate substitute for thermosetting epoxy polymers, especially at low cutting temperatures.

Adaptive Data-Driven Deep-Learning Surrogate Model for Frontal Polymerization in Dicyclopentadiene.

Frontal polymerization (FP) is a self-sustaining curing process that enables rapid and energy-efficient manufacturing of thermoset polymers and composites. Computational methods conventionally used to simulate the FP process are time-consuming, and repeating simulations are required for sensitivity analysis, uncertainty quantification, or optimization of the manufacturing process. In this work, we develop an adaptive surrogate deep-learning model for FP of dicyclopentadiene (DCPD), which predicts the evolution of temperature and degree of cure orders of magnitude faster than the finite-element method (FEM). The adaptive algorithm provides a strategy to select training samples efficiently and save computational costs by reducing the redundancy of FEM-based training samples. The adaptive algorithm calculates the residual error of the FP governing equations using automatic differentiation of the deep neural network. A probability density function expressed in terms of the residual error is used to select training samples from the Sobol sequence space. The temperature and degree of cure evolution of each training sample are obtained by a 2D FEM simulation. The adaptive method is more efficient and has a better prediction accuracy than the random sampling method. With the well-trained surrogate neural network, the FP characteristics (front speed, shape, and temperature) can be extracted quickly from the predicted temperature and degree-of-cure fields.

Adhesive bonding of glass-fibre thermoplastic composite: process optimisation and sustainability analysis using LCA methodology

In recent years, great attention has been paid to the challenge of integrating more sustainable circular approaches to manufacturing, which involve optimising the entire product cycle, from design to fabrication, assembly and eventual reuse/recycling. In this context, the use of thermoplastic composite materials in combination with adhesive bonding is attracting increasing attention to achieve this dual objective. Therefore, the proposed research focuses on the experimental and statistical optimisation of an adhesive bonding process for glass-fibre–reinforced composite substrates with polypropylene matrix, with the aim of comparing its performance with that of joints made using more conventional configurations, i.e. utilising thermosetting substrates. A low-pressure plasma pre-bonding surface treatment is adopted, and its effectiveness in enhancing joint performance compared to more conventional preparations for plastics is discussed. By varying plasma parameters according to the design of experiments statistical approach, the joint response is studied in terms of tensile shear strength and modelled in accordance with the response surface methodology to identify the optimum condition of process parameters within the established system boundaries. The study found that with optimised pre-treatment, adhesive joints of glass-fibre–reinforced composites with thermoplastic matrices (first scenario) can achieve tensile shear strength (TSS) comparable to that of thermoset composites (second scenario), making them viable options in various applications. Two alternative scenarios—namely, joints with thermoplastic composite or thermoset composite substrates—are then analysed by the life cycle assessment methodology and compared according to their relative environmental impact, demonstrating that glass-fibre thermoplastic composite joints are competitive alternatives to thermoset joints in terms of mechanical static performance achieved, but significantly preferable with regard to environmental sustainability.

Core-shell structured tow-pregs enabled additive manufacturing of continuously reinforced thermoset composites

One of the major challenges in thermally curable polymer composite additive manufacturing is the slow curing time of thermally curable resins, coupled with a significant drop in thermoset viscosity upon heating, making the formation of complex shapes difficult. To tackle these issues, we have introduced a novel rapid composite preformation strategy called Tow-Preg Cladding (TPC). This technique involves the use of a thin and rapidly curable dual-cure resin, which combines a thermally curable resin (such as epoxy) with a fast photo-curable resin. The dual-cure resin is applied as a coating over a thermally curable resin tow-preg, enabling the formation of a rigid cladding that supports and shapes the tow-pregs into the desired geometries and patterns. The key advantage of this approach lies in the sequential formation of an interpenetrating polymer network (IPN) at the interlayer between laminates, resulting from the curing of the photocurable resin and the thermally curable resin sequentially. This IPN formation enhances interlaminar bonding in the composite, contributing to its overall strength and performance. The composites produced using this technique exhibited impressive mechanical properties, including longitudinal tensile strength of 1058.2 MPa, longitudinal tensile modulus of 74.2 GPa, flexural strength of 1080.4 MPa, and flexural modulus of 41.7 GPa. Overall, our Tow-Preg Cladding approach shows great promise in overcoming the challenges associated with thermally curable polymer composite additive manufacturing. It offers a viable solution to creating strong, shape-specific thermoset composites efficiently with enhanced mechanical properties.

Fluorinated‐polyhedral oligomeric silsesquioxane (F‐POSS) functionalized halloysite nanotubes (HNTs) as an antifouling additive for epoxy resin

AbstractAntifouling epoxy resin serves as a member of advanced nanocomposite coatings and engineered surfaces. Nevertheless, developing an antifouling epoxy composites is a state‐of‐the‐art technology. Herein, a complex nanostructure is tailored to be served as an advanced additive giving the antifouling characteristics to the epoxy resin. F‐POSS@HNT hybrid nanostructure, that is, halloysite nanotubes (HNTs) decorated with fluorinated polyhedral oligomericsil sesquioxane (F‐POSS), was synthesized and characterized. Chemical structure changes, thermal stability and morphology of hydroxylated HNTs (hHNTs) intermediate and F‐POSS@HNT ultimate nanostructures were analyzed by FTIR spectroscopy, TGA and TEM, respectively. The F‐POSS@HNTs catalyzed the epoxy‐amine crosslinking reaction, taking “Good” or “Excellent” crosslinking tags an quantified by the “Cure Index.” The apparent activation energy values were calculated for the epoxy (reference), epoxy/hHNTs, and epoxy/F‐POSS@HNTs systems (26, 51, and 47 kJ mol−1, respectively). Contact angle measurements were performed via dynamic tests demonstrating improved hydro‐ and oleophobicity of the thermoset composites. The advancing contact angle with diiodomethane increased 36% and 30% for nanocomposites containing 5 and 10 wt.% of the developed hybrid nanostructure, respectively, compared with the neat epoxy. Likewise, 54% and 67% reduction in paraffin fouling in the same order confirmed their antifouling ability. Regarding self‐cleaning characteristics, 24% and 33% surface recovery were observed, respectively.Highlights Antifouling surface was achieved in epoxy thermoset nanocomposites for potential industrial applications. Self‐cleaning behavior correlated with low wetting and antifouling properties. F‐POSS@HNT nanofillers were synthesized and successfully added to epoxy matrix. Both hHNT and F‐POSS@HNT showed a beneficial autocatalytic effect on epoxy‐amine reaction yielding satisfactory polymer crosslinking. Activation energy was reduced by incorporating F‐POSS@HNT compared with hHNT, signature of facilitated crosslinking.

Recent advancements in thermoplastic composite materials in aerospace industry

It is a known fact that aerospace industry requires very strict requirements in terms of weight, material properties, and product lifetime performance. Therefore, composite materials are key candidates to satisfy these stringent requirements. Thermoplastic composites have become more competitive in the fields of aerospace, defense, energy, electronics, and automotive industries compared to thermoset composites, due to their ease of formability, short production cycles, and recyclability. Considering the benefits of thermoplastic composite materials, more thermoplastic parts will be produced in near future in aerospace industry. This study highlights the most recent advancements in thermoplastic composite technology. The latest advances in thermoplastic composite technology are highlighted by reviewing material technologies and production methods. Conclusion of this study, it has been observed that the use of thermoplastics in the aerospace industry is increasing day by day, owing to the advantages they offer compared to traditional materials. Especially in critical and trending areas such as stamp forming, press consolidation, Automatic Fiber Placement (AFP), and welding methods, research and development activities are intensifying. Furthermore, this study provides insights into the direction of current investments in thermoplastic technology and discusses how these investments are likely to shape future applications within the aerospace industry.

Manufacturing multifunctional vascularized composites by through-thickness frontal polymerization and depolymerization: A numerical study on the impact of sacrificial fiber configurations

Concurrent through-thickness frontal polymerization and vascularization (FP-VaSC) is emerging as a promising alternative to conventional multi-step fabrication approaches for vascularized thermoset polymers and composites. This method relies on a localized and self-propagating exothermic polymerization reaction front of the polymer matrix, to simultaneously cure the matrix, and depolymerize pre-embedded sacrificial templates. It delivers fully cured thermoset polymers and composites rapidly and energy-efficiently with the desired vascular system in a single step. While previous studies demonstrated the capability of this method for making woven laminates with a single vascular channel created by embedding a single straight sacrificial fiber, it is desirable to explore the potential of this method for making composites with multiple channels for more practical applications. We employ a previously validated thermo-chemical model from our prior study, to systematically investigate the reaction process with the presence of multiple sacrificial fibers. Two sacrificial fiber configurations are considered, namely, inline and staggered fiber configurations. Within each configuration, we consider a range of horizontal and vertical fiber spacing, which also lead to different sacrificial fiber volume fractions. This study reveals the interactions between the sacrificial fiber and the reactions, identifies the working window of this method for different sacrificial fiber configurations, and provides guidance for manufacturing laminates with multiple vascular channels. We also propose an analytical model that can quickly approximate the maximum sacrificial fiber volume fraction that can lead to successful FP-VaSC for a given carbon fiber volume fraction and compare the results with those from the thermo-chemical modeling.