953 resultados para Materials Science, Composites


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Carbon nanotubes (CNT) could serve as potential reinforcement for metal matrix composites for improved mechanical properties. However dispersion of carbon nanotubes (CNT) in the matrix has been a longstanding problem, since they tend to form clusters to minimize their surface area. The aim of this study was to use plasma and cold spraying techniques to synthesize CNT reinforced aluminum composite with improved dispersion and to quantify the degree of CNT dispersion as it influences the mechanical properties. Novel method of spray drying was used to disperse CNTs in Al-12 wt.% Si prealloyed powder, which was used as feedstock for plasma and cold spraying. A new method for quantification of CNT distribution was developed. Two parameters for CNT dispersion quantification, namely Dispersion parameter (DP) and Clustering Parameter (CP) have been proposed based on the image analysis and distance between the centers of CNTs. Nanomechanical properties were correlated with the dispersion of CNTs in the microstructure. Coating microstructure evolution has been discussed in terms of splat formation, deformation and damage of CNTs and CNT/matrix interface. Effect of Si and CNT content on the reaction at CNT/matrix interface was thermodynamically and kinetically studied. A pseudo phase diagram was computed which predicts the interfacial carbide for reaction between CNT and Al-Si alloy at processing temperature. Kinetic aspects showed that Al4C3 forms with Al-12 wt.% Si alloy while SiC forms with Al-23wt.% Si alloy. Mechanical properties at nano, micro and macro-scale were evaluated using nanoindentation and nanoscratch, microindentation and bulk tensile testing respectively. Nano and micro-scale mechanical properties (elastic modulus, hardness and yield strength) displayed improvement whereas macro-scale mechanical properties were poor. The inversion of the mechanical properties at different scale length was attributed to the porosity, CNT clustering, CNT-splat adhesion and Al 4C3 formation at the CNT/matrix interface. The Dispersion parameter (DP) was more sensitive than Clustering parameter (CP) in measuring degree of CNT distribution in the matrix.

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Hydroxyapatite (HA) has received wide attention in orthopedics, due to its biocompatibility and osseointegration ability. Despite these advantages, the brittle nature and low fracture toughness of HA often results in rapid wear and premature fracture of implant. Hence, there is a need to improve the fracture toughness and wear resistance of HA without compromising its biocompatibility. ^ The aim of the current research is to explore the potential of nanotubes as reinforcement to HA for orthopedic implants. HA- 4 wt.% carbon nanotube (CNT) composites and coatings are synthesized by spark plasma sintering and plasma spraying respectively, and investigated for their mechanical, tribological and biological behavior. CNT reinforcement improves the fracture toughness (>90%) and wear resistance (>66%) of HA for coating and free standing composites. CNTs have demonstrated a positive influence on the proliferation, differentiation and matrix mineralization activities of osteoblasts, during in-vitro biocompatibility studies. In-vivo exposure of HA-CNT coated titanium implant in animal model (rat) shows excellent histocompatibility and neobone integration on the implant surface. The improved osseointegration due to presence of CNTs in HA is quantified by the adhesion strength measurement of single osteoblast using nano-scratch technique. ^ Considering the ongoing debate about cytotoxicity of CNTs in the literature, the present study also suggests boron nitride nanotube (BNNT) as an alternative reinforcement. BNNT with the similar elastic modulus and strength as CNT, were added to HA. The resulting composite having 4 wt.% BNNTs improved the fracture toughness (∼85%) and wear resistance (∼75%) of HA in the similar range as HA-CNT composites. BNNTs were found to be non-cytotoxic for osteoblasts and macrophages. In-vitro evaluation shows positive role of BNNT in osteoblast proliferation and viability. Apatite formability of BNNT surface in ∼4 days establishes its osseointegration ability.^

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Recent advances in the electric & hybrid electric vehicles and rapid developments in the electronic devices have increased the demand for high power and high energy density lithium ion batteries. Graphite (theoretical specific capacity: 372 mAh/g) used in commercial anodes cannot meet these demands. Amorphous SnO2 anodes (theoretical specific capacity: 781 mAh/g) have been proposed as alternative anode materials. But these materials have poor conductivity, undergo a large volume change during charging and discharging, large irreversible capacity loss leading to poor cycle performances. To solve the issues related to SnO2 anodes, we propose to synthesize porous SnO2 composites using electrostatic spray deposition technique. First, porous SnO2/CNT composites were fabricated and the effects of the deposition temperature (200, 250, 300 °C) & CNT content (10, 20, 30, 40 wt %) on the electrochemical performance of the anodes were studied. Compared to pure SnO2 and pure CNT, the composite materials as anodes showed better discharge capacity and cyclability. 30 wt% CNT content and 250 °C deposition temperature were found to be the optimal conditions with regard to energy capacity whereas the sample with 20% CNT deposited at 250 °C exhibited good capacity retention. This can be ascribed to the porous nature of the anodes and the improvement in the conductivity by the addition of CNT. Electrochemical impedance spectroscopy studies were carried out to study in detail the change in the surface film resistance with cycling. By fitting EIS data to an equivalent circuit model, the values of the circuit components, which represent surface film resistance, were obtained. The higher the CNT content in the composite, lower the change in surface film resistance at certain voltage upon cycling. The surface resistance increased with the depth of discharge and decreased slightly at fully lithiated state. Graphene was also added to improve the performance of pure SnO2 anodes. The composites heated at 280 °C showed better energy capacity and energy density. The specific capacities of as deposited and post heat-treated samples were 534 and 737 mAh/g after 70 cycles. At the 70th cycle, the energy density of the composites at 195 °C and 280 °C were 1240 and 1760 Wh/kg, respectively, which are much higher than the commercially used graphite electrodes (37.2–74.4 Wh/kg). Both SnO2/CNTand SnO2/grapheme based composites with improved energy densities and capacities than pure SnO2 can make a significant impact on the development of new batteries for electric vehicles and portable electronics applications.

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Development of green composite from natural fibers has gained increasing interests due to the environmental and sustainable benefits when compared with petroleum based non-degradable materials. However, a big challenge of green composites is the diversity of fiber sources, because of the large variation in the properties and characteristics of the lignocellulosic renewable resource. The lignocellulosic fibers/natural fibers used to reinforce green composites are reviewed in this chapter. A classification of fiber types and sources, the properties of various natural fibers, including structure, composition, physical and chemical properties are focused; followed by the impacts of natural fibers on composite properties, with identification of the main pathways from the natural fibers to the green composite. Furthermore, the main challenges and future trend of natural fibers are highlighted.

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Green composites are important class of biocomposites widely explored due to their enhanced properties. The biodegradable polymeric material is reinforced with natural fibers to form a composite that is eco-friendly and environment sustainable. The green composites have potential to attract the traditional petroleum-based composites which are toxic and nonbiodegradable. The green composites eliminate the traditional materials such as steel and wood with biodegradable polymer composites. The degradable and environment-friendly green composites were prepared by various fabrication techniques. The various properties of different fiber composite were studied as reinforcement for fully biodegradable and environmental-friendly green composites.

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Botanically, green composites belong to an economically important seed plant family that includes maize, wheat, rice, and sorghum known as Saccharum offi cinarum. There are so many natural fibers available in the environment such as rice husk, hemp fibers, flax fibers, bamboo fibers, coconut fiber, coconut coir, grawia optiva and many others also. Life Cycle Assessment (LCA) is a process to estimate the environmental feature and potential impacts related to a product, by organizing a directory of pertinent inputs and outputs of a product system, assessing the potential environmental impacts related with the said inputs and outputs, explaining the results of the inventory analysis and impact evaluation phases in connection to the objectives of the study. Particularly Bagasse, an agricultural residue not only becomes a problem from the environmental point of view, but also affects the profitability of the sugarcane industries. This chapter discusses the properties, processing methods and various other aspects including economic and environmental aspects related to green composites.

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Natural fibers can be used in rotational molding process to obtain parts with improved mechanical properties. Different approaches have been followed in order to produce formulations containing banana or abaca fiber at 5% weight, in two- and three-layer constructions. Chemically treated abaca fiber has also been studied, causing some problems in processability. Fibers used have been characterized by Fourier transform infrared (FTIR) spectroscopy, thermogravimetric analysis (TGA), optical microscopy, and single-fiber mechanical tests. Rotomolded parts have been tested for tensile, flexural, and impact properties, demonstrating that important increases in elastic modulus are achieved with these fibers, although impact properties are reduced. © 2013 Copyright Taylor and Francis Group, LLC.

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Combining intrinsically conducting polymers with carbon nanotubes (CNT) helps in creating composites with superior electrical and thermal characteristics. These composites are capable of replacing metals and semiconductors as they possess unique combination of electrical conductivity, flexibility, stretchability, softness and bio-compatibility. Their potential for use in various organic devices such as super capacitors, printable conductors, optoelectronic devices, sensors, actuators, electrochemical devices, electromagnetic interference shielding, field effect transistors, LEDs, thermoelectrics etc. makes them excellent substitutes for present day semiconductors.However, many of these potential applications have not been fully exploited because of various open–ended challenges. Composites meant for use in organic devices require highly stable conductivity for the longevity of the devices. CNT when incorporated at specific proportions, and with special methods contributes quite positively to this end.The increasing demand for energy and depleting fossil fuel reserves has broadened the scope for research into alternative energy sources. A unique and efficient method for harnessing energy is thermoelectric energy conversion method. Here, heat is converted directly into electricity using a class of materials known as thermoelectric materials. Though polymers have low electrical conductivity and thermo power, their low thermal conductivity favours use as a thermoelectric material. The thermally disconnected, but electrically connected carrier pathways in CNT/Polymer composites can satisfy the so-called “phonon-glass/electron-crystal” property required for thermoelectric materials. Strain sensing is commonly used for monitoring in engineering, medicine, space or ocean research. Polymeric composites are ideal candidates for the manufacture of strain sensors. Conducting elastomeric composites containing CNT are widely used for this application. These CNT/Polymer composites offer resistance change over a large strain range due to the low Young‟s modulus and higher elasticity. They are also capable of covering surfaces with arbitrary curvatures.Due to the high operating frequency and bandwidth of electronic equipments electromagnetic interference (EMI) has attained the tag of an „environmental pollutant‟, affecting other electronic devices as well as living organisms. Among the EMI shielding materials, polymer composites based on carbon nanotubes show great promise. High strength and stiffness, extremely high aspect ratio, and good electrical conductivity of CNT make it a filler of choice for shielding applications. A method for better dispersion, orientation and connectivity of the CNT in polymer matrix is required to enhance conductivity and EMI shielding. This thesis presents a detailed study on the synthesis of functionalised multiwalled carbon nanotube/polyaniline composites and their application in electronic devices. The major areas focused include DC conductivity retention at high temperature, thermoelectric, strain sensing and electromagnetic interference shielding properties, thermogravimetric, dynamic mechanical and tensile analysis in addition to structural and morphological studies.

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The aim of this dissertation was to investigate flexible polymer-nanoparticle composites with unique magnetic and electrical properties. Toward this goal, two distinct projects were carried out. The first project explored the magneto-dielectric properties and morphology of flexible polymer-nanoparticle composites that possess high permeability (µ), high permittivity (ε) and minimal dielectric, and magnetic loss (tan δε, tan δµ). The main materials challenges were the synthesis of magnetic nanoparticle fillers displaying high saturation magnetization (Ms), limited coercivity, and their homogeneous dispersion in a polymeric matrix. Nanostructured magnetic fillers including polycrystalline iron core-shell nanoparticles, and constructively assembled superparamagnetic iron oxide nanoparticles were synthesized, and dispersed uniformly in an elastomer matrix to minimize conductive losses. The resulting composites have demonstrated promising permittivity (22.3), permeability (3), and sustained low dielectric (0.1), magnetic (0.4) loss for frequencies below 2 GHz. This study demonstrated nanocomposites with tunable magnetic resonance frequency, which can be used to develop compact and flexible radio frequency devices with high efficiency. The second project focused on fundamental research regarding methods for the design of highly conductive polymer-nanoparticle composites that can maintain high electrical conductivity under tensile strain exceeding 100%. We investigated a simple solution spraying method to fabricate stretchable conductors based on elastomeric block copolymer fibers and silver nanoparticles. Silver nanoparticles were assembled both in and around block copolymer fibers forming interconnected dual nanoparticle networks, resulting in both in-fiber conductive pathways and additional conductive pathways on the outer surface of the fibers. Stretchable composites with conductivity values reaching 9000 S/cm maintained 56% of their initial conductivity after 500 cycles at 100% strain. The developed manufacturing method in this research could pave the way towards direct deposition of flexible electronic devices on any shaped substrate. The electrical and electromechanical properties of these dual silver nanoparticle network composites make them promising materials for the future construction of stretchable circuitry for displays, solar cells, antennas, and strain and tactility sensors.

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The predictive capabilities of computational fire models have improved in recent years such that models have become an integral part of many research efforts. Models improve the understanding of the fire risk of materials and may decrease the number of expensive experiments required to assess the fire hazard of a specific material or designed space. A critical component of a predictive fire model is the pyrolysis sub-model that provides a mathematical representation of the rate of gaseous fuel production from condensed phase fuels given a heat flux incident to the material surface. The modern, comprehensive pyrolysis sub-models that are common today require the definition of many model parameters to accurately represent the physical description of materials that are ubiquitous in the built environment. Coupled with the increase in the number of parameters required to accurately represent the pyrolysis of materials is the increasing prevalence in the built environment of engineered composite materials that have never been measured or modeled. The motivation behind this project is to develop a systematic, generalized methodology to determine the requisite parameters to generate pyrolysis models with predictive capabilities for layered composite materials that are common in industrial and commercial applications. This methodology has been applied to four common composites in this work that exhibit a range of material structures and component materials. The methodology utilizes a multi-scale experimental approach in which each test is designed to isolate and determine a specific subset of the parameters required to define a material in the model. Data collected in simultaneous thermogravimetry and differential scanning calorimetry experiments were analyzed to determine the reaction kinetics, thermodynamic properties, and energetics of decomposition for each component of the composite. Data collected in microscale combustion calorimetry experiments were analyzed to determine the heats of complete combustion of the volatiles produced in each reaction. Inverse analyses were conducted on sample temperature data collected in bench-scale tests to determine the thermal transport parameters of each component through degradation. Simulations of quasi-one-dimensional bench-scale gasification tests generated from the resultant models using the ThermaKin modeling environment were compared to experimental data to independently validate the models.

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In this work, the effects of indenter tip roundness oil the load-depth indentation curves were analyzed using finite element modeling. The tip roundness level was Studied based on the ratio between tip radius and maximum penetration depth (R/h(max)), which varied from 0.02 to 1. The proportional Curvature constant (C), the exponent of depth during loading (alpha), the initial unloading slope (S), the correction factor (beta), the level of piling-up or sinking-in (h(c)/h(max)), and the ratio h(max)/h(f) are shown to be strongly influenced by the ratio R/h(max). The hardness (H) was found to be independent of R/h(max) in the range studied. The Oliver and Pharr method was successful in following the variation of h(c)/h(max) with the ratio R/h(max) through the variation of S with the ratio R/h(max). However, this work confirmed the differences between the hardness values calculated using the Oliver-Pharr method and those obtained directly from finite element calculations; differences which derive from the error in area calculation that Occurs when given combinations of indented material properties are present. The ratio of plastic work to total work (W(p)/W(t)) was found to be independent of the ratio R/h(max), which demonstrates that the methods for the Calculation of mechanical properties based on the *indentation energy are potentially not Susceptible to errors caused by tip roundness.

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In this work, the effects of conical indentation variables on the load-depth indentation curves were analyzed using finite element modeling and dimensional analysis. A factorial design 2(6) was used with the aim of quantifying the effects of the mechanical properties of the indented material and of the indenter geometry. Analysis was based on the input variables Y/E, R/h(max), n, theta, E, and h(max). The dimensional variables E and h(max) were used such that each value of dimensionless Y/E was obtained with two different values of E and each value of dimensionless R/h(max) was obtained with two different h(max) values. A set of dimensionless functions was defined to analyze the effect of the input variables: Pi(1) = P(1)/Eh(2), Pi(2) = h(c)/h, Pi(3) = H/Y, Pi(4) = S/Eh(max), Pi(6) = h(max)/h(f) and Pi(7) = W(P)/W(T). These six functions were found to depend only on the dimensionless variables studied (Y/E, R/h(max), n, theta). Another dimension less function, Pi(5) = beta, was not well defined for most of the dimensionless variables and the only variable that provided a significant effect on beta was theta. However, beta showed a strong dependence on the fraction of the data selected to fit the unloading curve, which means that beta is especially Susceptible to the error in the Calculation of the initial unloading slope.

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Medium density fiberboard (MDF) is an engineered wood product formed by breaking down selected lignin-cellulosic material residuals into fibers, combining it with wax and a resin binder, and then forming panels by applying high temperature and pressure. Because the raw material in the industrial process is ever-changing, the panel industry requires methods for monitoring the composition of their products. The aim of this study was to estimate the ratio of sugarcane (SC) bagasse to Eucalyptus wood in MDF panels using near infrared (NIR) spectroscopy. Principal component analysis (PCA) and partial least square (PLS) regressions were performed. MDF panels having different bagasse contents were easily distinguished from each other by the PCA of their NIR spectra with clearly different patterns of response. The PLS-R models for SC content of these MDF samples presented a strong coefficient of determination (0.96) between the NIR-predicted and Lab-determined values and a low standard error of prediction (similar to 1.5%) in the cross-validations. A key role of resins (adhesives), cellulose, and lignin for such PLS-R calibrations was shown. PLS-DA model correctly classified ninety-four percent of MDF samples by cross-validations and ninety-eight percent of the panels by independent test set. These NIR-based models can be useful to quickly estimate sugarcane bagasse vs. Eucalyptus wood content ratio in unknown MDF samples and to verify the quality of these engineered wood products in an online process.

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In this work we report the preparation of a new blue-emitting material based on the templated synthesis of mesoporous silica (MCM-41) using micellar solutions of the newly synthesized monocationic metallosurfactant complex bis[1-benzyl-4-(2,4-difluorophenyl)-1H-1,2,3-triazole](4,4'-diheptadecyl-2,2'- bipyridine)-iridium(III) chloride in hexadecyl-trimethyl-ammonium bromide (CTAB). Under ambient conditions, significant increases in excited state lifetime and quantum yield values (up to 45%), were obtained for the solid materials in comparison to the corresponding micellar solutions. Solid state (1)H and (19)F NMR spectroscopies were successfully employed for quantifying the luminophore content in terms of Ir-surfactant to CTAB and Ir-surfactant to silica ratios.

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Layer-by-layer (LBL) assembly was used to combine crystalline rod-like nanoparticles obtained from a vegetable source, cellulose nanowhiskers (CNWs), with collagen, the main component of skin and connective tissue found exclusively in animals. The film growth of the multilayered collagen/CNW was monitored by UV-Vis spectroscopy and ellipsometry measurements, whereas the film morphology and surface roughness were characterized by SEM and AFM. UV-Vis spectra showed the deposition of the same amount of collagen, 5 mg m(-2), in each dipping cycle. Ellipsometry data showed an increment in thickness with the number of layers, and the average thickness of each bilayer was found to be 8.6 nm. The multilayered bio-based nanocomposites were formed by single layers of densely packed CNWs adsorbed on top of each thin collagen layer where the hydrogen bonding between collagen amide groups and OH groups of the CNWs plays a mandatory role in the build-up of the thin films. The approach used in this work represents a potential strategy to mimic the characteristics of natural extracellular matrix (ECM) which can be used for applications in the biomedical field.