A comprehensive review on polymer matrix composites: material selection, fabrication, and application

A Multi-Objective Optimization of Neural Networks for Predicting the Physical Properties of Textile Polymer Composite Materials

This paper explores the application of multi-objective optimization techniques, including MOPSO, NSGA II, and SPEA2, to optimize the hyperparameters of artificial neural networks (ANNs) and support vector machines (SVMs) for predicting the physical properties of textile polymer composite materials (TPCMs). The optimization process utilizes data on the physical characteristics of the constituent fibers and fabrics used to manufacture these composites. By employing optimization algorithms, we aim to enhance the predictive accuracy of the ANN and SVM models, thereby facilitating the design and development of high-performance textile polymer composites. The effectiveness of the proposed approach is demonstrated through comparative analyses and validation experiments, highlighting its potential for optimizing complex material systems.

Investigation of mechanical behavior of glass fiber reinforced extruded polystyrene core material composites

Layered composites are composite materials created by combining different layers of materials. Each layer can possess unique properties, often tailored to meet specific application or design requirements. These composites have found applications in various sectors due to their features, which include lightness, excellent impact properties, and customization according to specific application areas. In this study, glass fiber reinforced polymer foam core layered composite materials were produced. EPS polymer foam was used as the core material. During production, polymer foams and fibers were bonded to the upper and lower sides of the foams using resin. Samples were produced with 4 and 6 layers on both sides, totaling 8 and 12 layers, respectively. The vacuum bagging method was employed in production, utilizing the manual laying technique. Upon completion of production, the materials were cut into sizes conforming to standards and converted into samples. Subsequently, three-point bending and low-speed impact tests were conducted on the produced samples. As a result of the impact tests, perforation occurred in the 8-layer samples of 200 g m-2 glass fiber composites, while rebound was observed in the 12-layer samples. Although more deformation occurred in the 8-layer glass fiber composites of 300 g m-2 than in the 12-layer samples, both sets of experiments resulted in rebound. Similar results to the impact tests were obtained in three-point bending tests, with higher strengths observed in the 12-layer samples compared to the 8-layer samples. Composite samples with fiber layers of 300 g m-2 exhibited better performance than samples with 200 g m-2 fibers.

A multi-element flame retardant containing boron and double-bond structure for enhancing mechanical properties and flame retardancy of epoxy resins

A multi-element synergistic flame retardant with double-bond structure was synthesized and added to epoxy resin (EP) to obtain EP composites with high flame retardant and mechanical properties. The study demonstrated that the DOPO-KhCPA-5 composite, containing 5 wt% of DOPO, exhibits the limiting oxygen index (LOI) value of 32%, indicating a high resistance to combustion. Additionally, it successfully meets the UL-94 V-0 grade, indicating excellent self-extinguishing properties. The DOPO-KhCPA-5 compound exhibited a 48.7% decrease in peak heat release rate (PHRR) and a 7.2% decrease in total heat release (THR) compared to pure EP. The inclusion of double-bonded architectures in the DOPO-KhCPA-5 composites led to a significant enhancement in both the tensile strength and tensile modulus. Specifically, the tensile strength increased by 38.5% and the tensile modulus by 57.9% compared to pure EP. This improvement can be attributed to the formation of a fully interpenetrating network of macromolecular chain structures by DOPO-KhCPA within the EP matrix. This network increased the entanglement between molecular chains, resulting in positive effects on the mechanical properties of the EP. Multi-element of DOPO-KhCPA exhibits a synergistic effect, providing condensed and noncombustible gas-phase flame retardancy. Additionally, the mechanical properties were improved with the introduction of flame retardants due to the good impact of double-bond cross-linking. The effectiveness of DOPO-KhCPA as an additive for developing high-performance EP with significant potential applications has been proven.

Recent advances in metal-family flame retardants: a review

The use of polymer materials is inextricably linked to our manufacturing life. However, most of them are easily combusted in the air and the combustion process generates a large amount of toxic fumes and dangerous smoke. This can result in injuries and property damage, as well as limiting their use. It is essential to enhance the flame-retardant properties and smoke suppression performance by using multiple flame retardants. Metal-based flame retardants have a unique chemical composition. They are environmentally friendly flame retardants, which can impart good smoke suppression, flame retardancy to polymers and further reduce the production of toxic gases. The differences in the compounds formed between the transition metals and the main group metals make them act differently as flame retardants for polymers. As a result, this study presents the research progress and flame-retardant mechanism of flame-retardant polymers for flame retardants from different groups of metals in the periodic table of elements in a systematic manner. In view of the differences between the main group metals and transition metals, the mechanism of their application in flame retardant polymer materials is carefully detailed, as are their distinct advantages and disadvantages. And ultimately, prospects for the development of transition metals and main group metals are outlined. It is hoped that this paper will provide valuable references and insights for scholars in the field.

Performance Study of Lightweight Insulating Mortar Reinforced with Straw Fiber

The current research aimed to develop lightweight, environmentally friendly mortar materials using crop straw fibers with better insulation properties. The lightweight mortar samples were tested for moisture content, thermal conductivity and compressive strength on days 3, 7 and 28, respectively. Scanning electron tomography (SEM) was performed on the fiber-matrix bonding interface and internal fiber structure. The permeability rating was also measured to check the impermeability of the lightweight fiber mortar. Due to the high hygroscopicity of plant fibers, the thermal conductivity of the mortar was high at the initial molding stage; the thermal conductivity measured at day 28 decreased with increasing fiber content, while the mechanical properties gradually decreased. The impermeability test showed that the straw fiber mortar had better impermeability than the standard mortar. However, with the addition of 2% of 10 mm long fibers, we increased the compressive strength and thermal insulation properties. Numerical simulations verified that the fiber insulation mortar has good thermal insulation properties in high-temperature tunnels.

Using Regression Analysis for Automated Material Selection in Smart Manufacturing

In intelligent manufacturing, the phase content and physical and mechanical properties of construction materials can vary due to different suppliers of blanks manufacturers. Therefore, evaluating the composition and properties for implementing a decision-making approach in material selection using up-to-date software is a topical problem in smart manufacturing. Therefore, the article aims to develop a comprehensive automated material selection approach. The proposed method is based on the comprehensive use of normalization and probability approaches and the linear regression procedure formulated in a matrix form. As a result of the study, analytical dependencies for automated material selection were developed. Based on the hypotheses about the impact of the phase composition on physical and mechanical properties, the proposed approach was proven qualitatively and quantitively for carbon steels from AISI 1010 to AISI 1060. The achieved results allowed evaluating the phase composition and physical properties for an arbitrary material from a particular group by its mechanical properties. Overall, an automated material selection approach based on decision-making criteria is helpful for mechanical engineering, smart manufacturing, and industrial engineering purposes.