Comparison of Mechanical Property Simulations with Results of Limited Flexural Tests of Different Multi-Layer Carbon Fiber-Reinforced Polymer Composites.

This article is focused on the experimental study of flexural properties in different multi-layer carbon fiber-reinforced polymer (CFRP) composites and correlations with the results of finite element method (FEM) simulations of mechanical properties. The comparison of the results shows the possibility of reducing the number of experimental specimens for testing. The experimental study of flexural properties for four types of carbon fiber-reinforced polymer matrix composites with twill weaves (2 × 2) was carried out. As input materials, pre-impregnated carbon laminate GG 204 T and GG 630 T (prepreg) and two types of carbon fiber fabrics (GG 285 T and GG 300 T (fabric)) were used. Multi-layer samples were manufactured from two types of prepregs and two types of fabrics, which were hand-impregnated during sample preparation. The layers were stacked using same orientation. All specimens for flexural test were cut with the longer side in the weft direction. Pre-impregnated carbon laminates were further impregnated with resin DT 121H. Carbon fabrics were hand-impregnated with epoxy matrix LG 120 and hardener HG 700. To fulfill the aim of this research, finite element method (FEM)-based simulations of mechanical properties were performed. The FEM simulations and analysis were conducted in Hexagon's MSC Marc Mentat 2022.3 and Digimat 2022.4 software. This paper presents the results of actual experimental bending tests and the results of simulations of bending tests for different composite materials (mentioned previously). We created material models for simulations based on two methods-MF (Mean Field) and FE (Finite Element), and the comparative results show better agreement with the MF model. The composites (GG 285 T and GG 300 T) showed better flexural results than composites made from pre-impregnated carbon laminates (GG 204 T and GG 630 T). The difference in results for the hand-impregnated laminates was about 15% higher than for prepregs, but this is still within an acceptable tolerance as per the reported literature. The highest percentage difference of 14.25% between the simulation and the real experiment was found for the software tool Digimat FE 2022.4-GG 630 T composite. The lowest difference of 0.5% was found for the software tool Digimat MF 2022.4-GG 204 T composite. By comparing the results of the software tools with the results of the experimental measurements, it was found that the Digimat MF 2022.4 tool is closer to the results of the experimental measurements than the Digimat FE 2022.4 tool.

Computational Analysis of Mechanical Properties in Polymeric Sandwich Composite Materials.

This article focuses on the computational analysis of sandwich composite materials based on polypropylene, polyester, glass, and cotton fibers. In the automotive components prepared from these fiber materials, the various components are used in different proportions. Through the manufacturing process, isotropic materials become somewhat anisotropic. Part of this article is aimed at obtaining input values of material characteristics for calculations using finite element analysis (FEM) and the comparison of experimental results with FEM-based material models created using the Digimat 2023.1 software. This article analyzes the modeling of two-phase as well as multiphase composite materials. This work focuses on calculations using FEM according to the test defined in the PR375 standard for loading the finished product in the luggage compartment of a car. The defined methodology enables the application of the FEM-based calculation directly to the product design in the initial phase of research. The construction and production of expensive prototypes and the subsequent production of automotive parts is replaced by computer-based simulation. This procedure makes it possible to simulate several optimization cycles over a relatively shorter time. From the results of computational simulations, it is clear that materials based on PP/PET/glass fibers show a much higher modulus of elasticity than materials created using cotton, i.e., materials of the PP/PET/cotton type. In order to achieve a high strength and stiffness, it is, therefore, appropriate to use glass fibers in the composite materials used for such applications.

An impedance flow cytometry with integrated dual microneedle for electrical properties characterization of single cell.

Electrical characteristics of living cells have been proven to reveal important details about their internal structure, charge distribution and composition changes in the cell membrane, as well as the extracellular context. An impedance flow cytometry is a common approach to determine the electrical properties of a cell, having the advantage of label-free and high throughput. However, the current techniques are complex and costly for the fabrication process. For that reason, we introduce an integrated dual microneedle-microchannel for single-cell detection and electrical properties extraction. The dual microneedles utilized a commercially available tungsten needle coated with parylene. When a single cell flows through the parallel-facing electrode configuration of the dual microneedle, the electrical impedance at multiple frequencies is measured. The impedance measurement demonstrated the differential of normal red blood cells (RBCs) with three different sizes of microbeads at low and high frequencies, 100 kHz and 2 MHz, respectively. An electrical equivalent circuit model (ECM) was used to determine the unique membrane capacitance of individual cells. The proposed technique demonstrated that the specific membrane capacitance of an RBC is 9.42 mF/m-2, with the regression coefficients, ρ at 0.9895. As a result, this device may potentially be used in developing countries for low-cost single-cell screening and detection.

Development of Lightweight Cricket Pads Using Knitted Flexible Thermoplastic Composites with Improved Impact Protection.

Cricket is one of the most popular global sports, and cricket pads are important personal protective gear used for shock absorption and peak deceleration of the impact forces of the cricket ball for both batsmen and wicket keepers. The materials selection of the padding should be considered according to requirements. In the present study, flexible composites were manufactured using knitted unidirectional thermoplastic composite prepregs. Prepregs were fabricated using thermoplastic yarns, e.g., High Density Polyethylene (HDPE), Polypropylene (PP), and Low Melting Polyester (LMPE). Para-aramid (Kevlar) and Flax yarns were used as inlay. The structures were stacked in three and five layers, and hot compression was used to convert thermoplastic yarn into matrix. A total of twelve samples were prepared, and their mechanical properties were evaluated. Tensile and flexural properties, short beam strength, and impact properties were optimized using the multi-criteria decision-making (MCDM) technique for order performance by similarity to ideal solution (TOPSIS). This approach was used to select the best material for use in cricket pads. The candidate samples were ranked using statistical techniques. The optimum sample was found to be FP5, i.e., Flax with polypropylene using five layers, which exhibited the maximum impact strength. The results showed that the mechanical properties were improved in general by increasing the number of layers. The significance and percentage contribution of each factor was obtained by ANOVA (α = 0.10) and pie chart, which showed Factors A and C (inlay yarn and number of layers) to be the main contributors. The optimal samples showed superior impact-related performance compared to a market sample cricket pad.

Comfort evaluation of ZnO coated fabrics by artificial neural network assisted with golden eagle optimizer model.

This paper introduces a novel technique to evaluate comfort properties of zinc oxide nanoparticles (ZnO NPs) coated woven fabrics. The proposed technique combines artificial neural network (ANN) and golden eagle optimizer (GEO) to ameliorate the training process of ANN. Neural networks are state-of-the-art machine learning models used for optimal state prediction of complex problems. Recent studies showed that the use of metaheuristic algorithms improve the prediction accuracy of ANN. GEO is the most advanced methaheurstic algorithm inspired by golden eagles and their intelligence for hunting by tuning their speed according to spiral trajectory. From application point of view, this study is a very first attempt where GEO is applied along with ANN to improve the training process of ANN for any textiles and composites application. Furthermore, the proposed algorithm ANN with GEO (ANN-GEO) was applied to map out the complex input-output conditions for optimal results. Coated amount of ZnO NPs, fabric mass and fabric thickness were selected as input variables and comfort properties were evaluated as output results. The obtained results reveal that ANN-GEO model provides high performance accuracy than standard ANN model, ANN models trained with latest metaheuristic algorithms including particle swarm optimizer and crow search optimizer, and conventional multiple linear regression.

Use of an Artificial Neural Network for Tensile Strength Prediction of Nano Titanium Dioxide Coated Cotton.

In this study, an artificial neural network (ANN) is used for the prediction of tensile strength of nano titanium dioxide (TiO2) coated cotton. The coating process was performed by ultraviolet (UV) radiations. Later on, a backpropagation ANN algorithm trained with Bayesian regularization was applied to predict the tensile strength. For a comparative study, ANN results were compared with traditional methods including multiple linear regression (MLR) and polynomial regression analysis (PRA). The input conditions for the experiment were dosage of TiO2, UV irradiation time and temperature of the system. Simulation results elucidated that ANN model provides high performance accuracy than MLR and PRA. In addition, statistical analysis was also performed to check the significance of this study. The results show a strong correlation between predicted and measured tensile strength of nano TiO2-coated cotton with small error values.

3D Woven Textile Structural Polymer Composites: Effect of Resin Processing Parameters on Mechanical Performance.

This work presents the manufacture of polymer composites using 3D woven structures (orthogonal, angle interlock and warp interlock) with glass multifilament tows and epoxy as the resin. The mechanical properties were analyzed by varying the processing parameters, namely, add-on percentage, amount of hardener, curing time, curing temperature and molding pressure, at four different levels during the composite fabrication for three different 3D woven structures. The mechanical properties of composites are affected by resin infusion or resin impregnation. Resin infusion depends on many processing conditions (temperature, pressure, viscosity and molding time), the structure of the reinforcement and the compatibility of the resin with the reinforcement. The samples were tested for tensile strength, tensile modulus, impact resistance and flexural strength. Optimal process parameters were identified for different 3D-woven-structure-based composites for obtaining optimal results for tensile strength, tensile modulus, impact resistance and flexural strength. The tensile strength, elongation at break and tensile modulus were found to be at a maximum for the angle interlock structure among the various 3D woven composites. A composition of 55% matrix (including 12% of hardener added) and 45% fiber were found to be optimal for the tensile and impact performance of 3D woven glass-epoxy composites. A curing temperature of about 140 °C seemed to be optimal for glass-epoxy composites. Increasing the molding pressure up to 12 bar helped with better penetration of the resin, resulting in higher tensile strength, modulus and impact performance. The optimal conditions for the best flexural performance in 3D woven glass-epoxy composites were 12% hardener, 140 °C curing temperature, 900 s curing time and 12 bar molding pressure.

Finite Element Analysis of the Ballistic Impact on Auxetic Sandwich Composite Human Body Armor.

In this study, the ballistic impact behavior of auxetic sandwich composite human body armor was analyzed using finite element analysis. The auxetic core of the armor was composed of discrete re-entrant unit cells. The sandwich armor structure consisted of a front panel of aluminum alloy (Al 7075-T6), UHMWPE (sandwich core), and a back facet of silicon carbide (SiC) bonded together with epoxy resin. Numerical simulations were run on Explicit Dynamics/Autodyne 3-D code. Various projectile velocities with the same boundary conditions were used to predict the auxetic armor response. These results were compared with those of conventional monolithic body armor. The results showed improved indentation resistance with the auxetic armor. Deformation in auxetic armor was observed greater for each of the cases when compared to the monolithic armor, due to higher energy absorption. The elastic energy dissipation results in the lower indentation in an auxetic armor. The armor can be used safely up to 400 m/s; being used at higher velocities significantly reduced the threat level. Conversely, the conventional monolithic modal does not allow the projectile to pass through at a velocity below 300 m/s; however, the back face becomes severely damaged at 200 m/s. At a velocity of 400 m/s, the front facet of auxetic armor was destroyed; however, the back facet was completely safe, while the monolithic panel did not withstand this velocity and was completely damaged. The results are encouraging in terms of resistance offered by the newly adopted auxetic armor compared to conventional monolithic armor.

Hybrid Prepreg Tapes for Composite Manufacturing: A Case Study.

The aim of this research was the preparation and characterization of hybrid prepreg tapes from glass multifilament roving (circular cross-section). The fiber, roving, and tape strength distribution was characterized by exploratory data analysis tools (especially quantile-quantile plot) and modeled by the three parameters' Weibull distribution. For estimation of Weibull model parameters, the noniterative technique based on the so-called Weibull moments was used. It was shown that the prepared hybrid prepreg tapes prepared by controlled mechanical spreading technology developed by the authors improved mechanical tensile properties and can be used for the preparation of composites of complicated forms by robotic winding.

Lightweight Glass Fiber-Reinforced Polymer Composite for Automotive Bumper Applications: A Review.

The enhancement of fuel economy and the emission of greenhouse gases are the key growing challenges around the globe that drive automobile manufacturers to produce lightweight vehicles. Additionally, the reduction in the weight of the vehicle could contribute to its recyclability and performance (for example crashworthiness and impact resistance). One of the strategies is to develop high-performance lightweight materials by the replacement of conventional materials such as steel and cast iron with lightweight materials. The lightweight composite which is commonly referred to as fiber-reinforced plastics (FRP) composite is one of the lightweight materials to achieve fuel efficiency and the reduction of CO2 emission. However, the damage of FRP composite under impact loading is one of the critical factors which affects its structural application. The bumper beam plays a key role in bearing sudden impact during a collision. Polymer composite materials have been abundantly used in a variety of applications such as transportation industries. The main thrust of the present paper deals with the use of high-strength glass fibers as the reinforcing member in the polymer composite to develop a car bumper beam. The mechanical performance and manufacturing techniques are discussed. Based on the literature studies, glass fiber-reinforced composite (GRP) provides more promise in the automotive industry compared to conventional materials such as car bumper beams.

Effect of Chemically Treated Kenaf Fibre on Mechanical and Thermal Properties of PLA Composites Prepared through Fused Deposition Modeling (FDM).

Natural fibre as a reinforcing agent has been widely used in many industries in this era. However, the reinforcing agent devotes a better strength when embedded with a polymer matrix. Nevertheless, the characteristic of natural fibre and polymer matrix are in contrast, as natural fibre is hydrophilic, while polymer is hydrophobic in nature. Natural fibre is highly hydrophilic due to the presence of a hydroxyl group (-OH), while polymer matrix has an inherent hydrophobic characteristic which repels water. This issue has been fixed by modifying the natural fibre's surface using a chemical treatment combining an alkaline treatment and a silane coupling agent. This modifying process of natural fibre might reduce the attraction of water and moisture content and increase natural fibre surface roughness, which improves the interfacial bonding between these two phases. In this paper, the effect of alkaline and silane treatment has been proven by performing the mechanical test, Scanning Electron Micrograph (SEM), and Fourier Transform Infrared spectrometry (FTIR) to observe the surface structure. The chemical compositions and thermal properties of the composites have been obtained by performing Differential Scanning Calorimetry (DSC) and Thermogravimetric Analysis (TGA) tests. 1.0% silane treatment displayed better strength performance as compared to other composites, which was proven by performing Scanning Electron Micrograph (SEM). The assumption is that by enduring chemical treatment, kenaf fibre composites could develop high performance in industry applications.

Heat insulation effect in solar radiation of polyurethane powder coating nanocomposite.

This study aims to improve polyurethane-based coating by modified zirconium oxide and aluminum oxide nanoparticles for preparing thin polymeric heat insulation coatings. In the first step, the nanoparticles were chemically modified with the silane coupling agent. Then, three different weight percent of modified nanoparticles (1, 3, and 5% w/w) were mixed with polyurethane, to prepare the nanocomposites, which were coated on metallic plate samples. Then, these plates are used to measure the radiation heat transfer coefficients, absorption coefficient in a region of short wavelengths (UV/VIS/NIR), the emissivity coefficient, and thermography of the samples in a region of long wavelengths (IR). Results showed that by adding the modified nanoparticles to the polyurethane matrix, absorption was decreased and the emissivity coefficient was increased. According to the thermography results, it was observed that the surface temperature of both samples with 3% w/w of nanoparticles had the minimum temperature compare to others. Minimum heat surface observed for 3% w/w of modified nano zirconium oxide.

Excellent UV-Light Triggered Photocatalytic Performance of ZnO.SiO2 Nanocomposite for Water Pollutant Compound Methyl Orange Dye.

The photocatalytic activity of eco-friendly zinc oxide doped silica nanocomposites, synthesized via a co-precipitation method followed by heat-treatment at 300, 600, and 900 °C is investigated. The samples have been characterized by employing X-ray diffraction method, and further analyzed using the Rietveld Refinement method. The samples show a space group P63mc with hexagonal structure. The prepared composites are tested for their photocatalytic activities for the degradation of methyl orange-based water pollutants under ultra-violet (UV) irradiation using a 125 W mercury lamp. A systematic analysis of parameters such as the irradiation time, pH value, annealing temperatures, and the concentration of sodium hydroxide impacting the degradation of the methyl orange (MO) is carried out using UV-visible spectroscopy. The ZnO.SiO2 nanocomposite annealed at 300 °C at a pH value of seven shows a maximum photo-degradation ability (~98.1%) towards methyl orange, while the photo-degradation ability of ZnO.SiO2 nanocomposites decreases with annealing temperature (i.e., for 600 and 900 °C) due to the aspect ratio. Moreover, it is seen that with increment in the concentration of the NaOH (i.e., from 1 to 3 g), the photo-degradation of the dye component is enhanced from 20.9 to 53.8%, whereas a reverse trend of degradation ability is observed for higher concentrations.

Separation of ctDNA by superparamagnetic bead particles in microfluidic platform for early cancer detection.

Introduction: Conventional biopsy, based on extraction from a tumor of a solid tissue specimen requiring needles, endoscopic devices, excision or surgery, is at risk of infection, internal bleeding or prolonged recovery. A non-invasive liquid biopsy is one of the greatest axiomatic consequences of the identification of circulating tumor DNA (ctDNA) as a replaceable surgical tumor bioQpsy technique. Most of the literature studies thus far presented ctDNA detection at almost final stage III or IV of cancer, where the treatment option or cancer management is nearly impossible for diagnosis. Objective: Hence, this paper aims to present a simulation study of extraction and separation of ctDNA from the blood plasma of cancer patients of stage I and II by superparamagnetic (SPM) bead particles in a microfluidic platform for early and effective cancer detection. Method: The extraction of ctDNA is based on microfiltration of particle size to filter some impurities and thrombocytes plasma, while the separation of ctDNA is based on magnetic manipulation to high yield that can be used for the upstream process. Result: Based on the simulation results, an average of 5.7 ng of ctDNA was separated efficiently for every 10 µL blood plasma input and this can be used for early analysis of cancer management. The particle tracing module from COMSOL Multiphysics traced ctDNA with 65.57% of sensitivity and 95.38% of specificity. Conclusion: The findings demonstrate the ease of use and versatility of a microfluidics platform and SPM bead particles in clinical research related to the preparation of biological samples. As a sample preparation stage for early analysis and cancer diagnosis, the extraction and separation of ctDNA is most important, so precision medicine can be administered.

Development and Characterization of Fenugreek Protein-Based Edible Film.

The present investigation studied the physicochemical, mechanical, structural, thermal, and morphological attributes of a novel edible film formed from fenugreek protein concentrate. Films were produced at different pH-9, 10, 11, and 12-and the effect of the pH on the films was studied. As the pH increased, tensile strength increased while water vapor absorption decreased, which is interrelated to the surface morphological properties; as the pH increased, the surface became smoother and compact without any cavities. The films produced were darker in color. Fenugreek protein films exhibited good thermal stability. Fourier transform infrared spectroscopy (FTIR) revealed the presence of strong bonding for the films made at alkaline pH. X-ray diffraction analysis (XRD) indicated the major structure of the film was amorphous. The study demonstrated that the fenugreek protein concentrate film has influential characteristics and can be used as an edible packaging film.

Prediction of Methylene Blue Removal by Nano TiO2 Using Deep Neural Network.

This paper deals with the prediction of methylene blue (MB) dye removal under the influence of titanium dioxide nanoparticles (TiO2 NPs) through deep neural network (DNN). In the first step, TiO2 NPs were prepared and their morphological properties were analysed by scanning electron microscopy. Later, the influence of as synthesized TiO2 NPs was tested against MB dye removal and in the final step, DNN was used for the prediction. DNN is an efficient machine learning tools and widely used model for the prediction of highly complex problems. However, it has never been used for the prediction of MB dye removal. Therefore, this paper investigates the prediction accuracy of MB dye removal under the influence of TiO2 NPs using DNN. Furthermore, the proposed DNN model was used to map out the complex input-output conditions for the prediction of optimal results. The amount of chemicals, i.e., amount of TiO2 NPs, amount of ehylene glycol and reaction time were chosen as input variables and MB dye removal percentage was evaluated as a response. DNN model provides significantly high performance accuracy for the prediction of MB dye removal and can be used as a powerful tool for the prediction of other functional properties of nanocomposites.

Effect of Nanofillers on Tribological Properties of Polymer Nanocomposites: A Review on Recent Development.

Polymer nanocomposites with enhanced performances are becoming a trend in the current research field, overcoming the limitations of bulk polymer and meeting the demands of market and society in tribological applications. Polytetrafluoroethylene, poly(ether ether ketone) and ultrahigh molecular weight polyethylene are the most popular polymers in recent research on tribology. Current work comprehensively reviews recent advancements of polymer nanocomposites in tribology. The influence of different types of nanofiller, such as carbon-based nanofiller, silicon-based nanofiller, metal oxide nanofiller and hybrid nanofiller, on the tribological performance of thermoplastic and thermoset nanocomposites is discussed. Since the tribological properties of polymer nanocomposites are not intrinsic but are dependent on sliding conditions, direct comparison between different types of nanofiller or the same nanofiller of different morphologies and structures is not feasible. Friction and wear rate are normalized to indicate relative improvement by different fillers. Emphasis is given to the effect of nanofiller content and surface modification of nanofillers on friction, wear resistance, wear mechanism and transfer film formation of its nanocomposites. Limitations from the previous works are addressed and future research on tribology of polymer nanocomposites is proposed.

Classification of Textile Polymer Composites: Recent Trends and Challenges.

Polymer based textile composites have gained much attention in recent years and gradually transformed the growth of industries especially automobiles, construction, aerospace and composites. The inclusion of natural polymeric fibres as reinforcement in carbon fibre reinforced composites manufacturing delineates an economic way, enhances their surface, structural and mechanical properties by providing better bonding conditions. Almost all textile-based products are associated with quality, price and consumer's satisfaction. Therefore, classification of textiles products and fibre reinforced polymer composites is a challenging task. This paper focuses on the classification of various problems in textile processes and fibre reinforced polymer composites by artificial neural networks, genetic algorithm and fuzzy logic. Moreover, their limitations associated with state-of-the-art processes and some relatively new and sequential classification methods are also proposed and discussed in detail in this paper.

Development and Characterization of Physical Modified Pearl Millet Starch-Based Films.

Pearl millet is an underutilized and drought-resistant crop that is mainly used for animal feed and fodder. Starch (70%) is the main constituent of the pearl millet grain; this starch may be a good substitute for major sources of starch such as corn, rice, potatoes, etc. Starch was isolated from pearl millet grains and modified with different physical treatments (heat-moisture (HMT), microwave (MT), and sonication treatment (ST)). The amylose content and swelling capacity of the starches decreased after HMT and MT, while the reverse was observed for ST. Transition temperatures (onset (To), peak of gelatinization (Tp), and conclusion (Tc)) of the starches ranged from 62.92-76.16 °C, 67.95-81.05 °C, and 73.78-84.50 °C, respectively. After modification (HMT, MT, and ST), an increase in the transition temperatures was observed. Peak-viscosity of the native starch was observed to be 995 mPa.s., which was higher than the starch modified with HMT and MT. Rheological characteristics (storage modulus (G') and loss modulus (G'')) of the native and modified starches differed from 1039 to 1730 Pa and 83 to 94 Pa; the largest value was found for starch treated with ST and HMT. SEM showed cracks and holes on granule surfaces after HMT as well as MT starch granules. Films were prepared using both native and modified starches. The modification of the starches with different treatments had a significant impact on the moisture, transmittance, and solubility of films. The findings of this study will provide a better understanding of the functional properties of pearl millet starch for its possible utilization in film formation.

Monolayer Twisted Graphene-Based Schottky Transistor.

The outstanding properties of graphene-based components, such as twisted graphene, motivates nanoelectronic researchers to focus on their applications in device technology. Twisted graphene as a new class of graphene structures is investigated in the platform of transistor application in this research study. Therefore, its geometry effect on Schottky transistor operation is analyzed and the relationship between the diameter of twist and number of twists are explored. A metal-semiconductor-metal twisted graphene-based junction as a Schottky transistor is considered. By employing the dispersion relation and quantum tunneling the variation of transistor performance under channel length, the diameter of twisted graphene, and the number of twists deviation are studied. The results show that twisted graphene with a smaller diameter affects the efficiency of twisted graphene-based Schottky transistors. Additionally, as another main characteristic, the ID-VGS is explored, which indicates that the threshold voltage is increased by diameter and number of twists in this type of transistor.