773 resultados para conjugated polymer


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Supported Cu(II) polymer catalysts were used for the catalytic oxidation of phenol at 30 degrees C and atmospheric pressure using air and H(2)O(2) as oxidants. Heterogenisation of homogeneous Cu(II) catalysts was achieved by adsorption of Cu(II) salts onto polymeric matrices (poly(4-vinylpyridine), Chitosan). The catalytic active sites were represented by Cu(II) ions and showed to conserve their oxidative activity in heterogeneous catalysis as well as in homogeneous systems. The catalytic deactivation was evaluated by quantifying released Cu(II) ions in solution during oxidation, from where Cu-PVP(25) showed the best leaching levels no more than 5 mg L(-1). Results also indicated that Cu-PVP(25) had a catalytic activity (56% of phenol conversion when initial Cu(II) catalytic content was 200 mg L(Reaction)(-1)) comparable to that of commercial catalysts (59% of phenol conversion). Finally, the balance between activity and copper leaching was better represented by Cu-PVP(25) due to the heterogeneous catalytic activity had 86% performance in the heterogeneous phase, and the rest on the homogeneous phase, while Cu-PVP(2) had 59% and CuO/gamma-Al(2)O(3) 68%.

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Polymer electrolyte fuel cell (PEMFC) is promising source of clean power in many applications ranging from portable electronics to automotive and land-based power generation. However, widespread commercialization of PEMFC is primarily challenged by degradation. The mechanisms of fuel cell degradation are not well understood. Even though the numbers of installed units around the world continue to increase and dominate the pre-markets, the present lifetime requirements for fuel cells cannot be guarantee, creating the need for a more comprehensive knowledge of material’s ageing mechanism. The objective of this project is to conduct experiments on membrane electrode assembly (MEA) components of PEMFC to study structural, mechanical, electrical and chemical changes during ageing and understanding failure/degradation mechanism. The first part of this project was devoted to surface roughness analysis on catalyst layer (CL) and gas diffusion layer (GDL) using surface mapping microscopy. This study was motivated by the need to have a quantitative understanding of the GDL and CL surface morphology at the submicron level to predict interfacial contact resistance. Nanoindentation studies using atomic force microscope (AFM) were introduced to investigate the effect of degradation on mechanical properties of CL. The elastic modulus was decreased by 45 % in end of life (EOL) CL as compare to beginning of life (BOL) CL. In another set of experiment, conductive AFM (cAFM) was used to probe the local electric current in CL. The conductivity drops by 62 % in EOL CL. The future task will include characterization of MEA degradation using Raman and Fourier transform infrared (FTIR) spectroscopy. Raman spectroscopy will help to detect degree of structural disorder in CL during degradation. FTIR will help to study the effect of CO in CL. XRD will be used to determine Pt particle size and its crystallinity. In-situ conductive AFM studies using electrochemical cell on CL to correlate its structure with oxygen reduction reaction (ORR) reactivity

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Single-screw extrusion is one of the widely used processing methods in plastics industry, which was the third largest manufacturing industry in the United States in 2007 [5]. In order to optimize the single-screw extrusion process, tremendous efforts have been devoted for development of accurate models in the last fifty years, especially for polymer melting in screw extruders. This has led to a good qualitative understanding of the melting process; however, quantitative predictions of melting from various models often have a large error in comparison to the experimental data. Thus, even nowadays, process parameters and the geometry of the extruder channel for the single-screw extrusion are determined by trial and error. Since new polymers are developed frequently, finding the optimum parameters to extrude these polymers by trial and error is costly and time consuming. In order to reduce the time and experimental work required for optimizing the process parameters and the geometry of the extruder channel for a given polymer, the main goal of this research was to perform a coordinated experimental and numerical investigation of melting in screw extrusion. In this work, a full three-dimensional finite element simulation of the two-phase flow in the melting and metering zones of a single-screw extruder was performed by solving the conservation equations for mass, momentum, and energy. The only attempt for such a three-dimensional simulation of melting in screw extruder was more than twenty years back. However, that work had only a limited success because of the capability of computers and mathematical algorithms available at that time. The dramatic improvement of computational power and mathematical knowledge now make it possible to run full 3-D simulations of two-phase flow in single-screw extruders on a desktop PC. In order to verify the numerical predictions from the full 3-D simulations of two-phase flow in single-screw extruders, a detailed experimental study was performed. This experimental study included Maddock screw-freezing experiments, Screw Simulator experiments and material characterization experiments. Maddock screw-freezing experiments were performed in order to visualize the melting profile along the single-screw extruder channel with different screw geometry configurations. These melting profiles were compared with the simulation results. Screw Simulator experiments were performed to collect the shear stress and melting flux data for various polymers. Cone and plate viscometer experiments were performed to obtain the shear viscosity data which is needed in the simulations. An optimization code was developed to optimize two screw geometry parameters, namely, screw lead (pitch) and depth in the metering section of a single-screw extruder, such that the output rate of the extruder was maximized without exceeding the maximum temperature value specified at the exit of the extruder. This optimization code used a mesh partitioning technique in order to obtain the flow domain. The simulations in this flow domain was performed using the code developed to simulate the two-phase flow in single-screw extruders.

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An extrusion die is used to continuously produce parts with a constant cross section; such as sheets, pipes, tire components and more complex shapes such as window seals. The die is fed by a screw extruder when polymers are used. The extruder melts, mixes and pressures the material by the rotation of either a single or double screw. The polymer can then be continuously forced through the die producing a long part in the shape of the die outlet. The extruded section is then cut to the desired length. Generally, the primary target of a well designed die is to produce a uniform outlet velocity without excessively raising the pressure required to extrude the polymer through the die. Other properties such as temperature uniformity and residence time are also important but are not directly considered in this work. Designing dies for optimal outlet velocity variation using simple analytical equations are feasible for basic die geometries or simple channels. Due to the complexity of die geometry and of polymer material properties design of complex dies by analytical methods is difficult. For complex dies iterative methods must be used to optimize dies. An automated iterative method is desired for die optimization. To automate the design and optimization of an extrusion die two issues must be dealt with. The first is how to generate a new mesh for each iteration. In this work, this is approached by modifying a Parasolid file that describes a CAD part. This file is then used in a commercial meshing software. Skewing the initial mesh to produce a new geometry was also employed as a second option. The second issue is an optimization problem with the presence of noise stemming from variations in the mesh and cumulative truncation errors. In this work a simplex method and a modified trust region method were employed for automated optimization of die geometries. For the trust region a discreet derivative and a BFGS Hessian approximation were used. To deal with the noise in the function the trust region method was modified to automatically adjust the discreet derivative step size and the trust region based on changes in noise and function contour. Generally uniformity of velocity at exit of the extrusion die can be improved by increasing resistance across the die but this is limited by the pressure capabilities of the extruder. In optimization, a penalty factor that increases exponentially from the pressure limit is applied. This penalty can be applied in two different ways; the first only to the designs which exceed the pressure limit, the second to both designs above and below the pressure limit. Both of these methods were tested and compared in this work.

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Materials are inherently multi-scale in nature consisting of distinct characteristics at various length scales from atoms to bulk material. There are no widely accepted predictive multi-scale modeling techniques that span from atomic level to bulk relating the effects of the structure at the nanometer (10-9 meter) on macro-scale properties. Traditional engineering deals with treating matter as continuous with no internal structure. In contrast to engineers, physicists have dealt with matter in its discrete structure at small length scales to understand fundamental behavior of materials. Multiscale modeling is of great scientific and technical importance as it can aid in designing novel materials that will enable us to tailor properties specific to an application like multi-functional materials. Polymer nanocomposite materials have the potential to provide significant increases in mechanical properties relative to current polymers used for structural applications. The nanoscale reinforcements have the potential to increase the effective interface between the reinforcement and the matrix by orders of magnitude for a given reinforcement volume fraction as relative to traditional micro- or macro-scale reinforcements. To facilitate the development of polymer nanocomposite materials, constitutive relationships must be established that predict the bulk mechanical properties of the materials as a function of the molecular structure. A computational hierarchical multiscale modeling technique is developed to study the bulk-level constitutive behavior of polymeric materials as a function of its molecular chemistry. Various parameters and modeling techniques from computational chemistry to continuum mechanics are utilized for the current modeling method. The cause and effect relationship of the parameters are studied to establish an efficient modeling framework. The proposed methodology is applied to three different polymers and validated using experimental data available in literature.

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Cellulose-polymer composites have potential applications in aerospace and transportation areas where lightweight materials with high mechanical properties are needed. In addition, these economical and biodegradable composites have been shown to be useful as polymer electrolytes, packaging structures, optoelectronic devices, and medical implants such as wound dressing and bone scaffolds. In spite of the above mentioned advantages and potential applications, due to the difficulties associated with synthesis and processing techniques, application of cellulose crystals (micro and nano sized) for preparation of new composite systems is limited. Cellulose is hydrophilic and polar as opposed to most of common thermoplastics, which are non-polar. This results in complications in addition of cellulose crystals to polymer matrices, and as a result in achieving sufficient dispersion levels, which directly affects the mechanical properties of the composites. As in other composite materials, the properties of cellulose-polymer composites depend on the volume fraction and the properties of individual phases (the reinforcement and the polymer matrix), the dispersion quality of the reinforcement through the matrix and the interaction between CNCs themselves and CNC and the matrix (interphase). In order to develop economical cellulose-polymer composites with superior qualities, the properties of individual cellulose crystals, as well as the effect of dispersion of reinforcements and the interphase on the properties of the final composites should be understood. In this research, the mechanical properties of CNC polymer composites were characterized at the macro and nano scales. A direct correlation was made between: Dispersion quality and macro-mechanical properties Nanomechanical properties at the surface and tensile properties CNC diameter and interphase thickness Lastly, individual CNCs from different sources were characterized and for the first time size-scale effect on their nanomechanical properties were reported. Then the effect of CNC surface modification on the mechanical properties was studied and correlated to the crystalline structure of these materials.

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Boron nitride nanotubes (BNNTs) are structurally similar to carbon nanotubes (CNTs), but exhibit completely different physical and chemical properties. Thus, BNNTs with various interesting properties may be complementary to CNTs and provide an alternative perspective to be useful in different applications. However, synthesis of high quality of BNNTs is still challenging. Hence, the major goals of this research work focus on the fundamental study of synthesis, characterizations, functionalization, and explorations of potential applications. In this work, we have established a new growth vapor trapping (GVT) approach to produce high quality and quantity BNNTs on a Si substrate, by using a conventional tube furnace. This chemical vapor deposition (CVD) approach was conducted at a growth temperature of 1200 °C. As compared to other known approaches, our GVT technique is much simpler in experimental setup and requires relatively lower growth temperatures. The as-grown BNNTs are fully characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), electron energy loss spectroscopy (EELS), Energy Filtered Mapping, Raman spectroscopy, Fourier Transform Infra Red spectroscopy (FTIR), UV-Visible (UV-vis) absorption spectroscopy, etc. Following this success, the growth of BNNTs is now as convenient as growing CNTs and ZnO nanowires. Some important parameters have been identified to produce high-quality BNNTs on Si substrates. Furthermore, we have identified a series of effective catalysts for patterned growth of BNNTs at desirable or pre-defined locations. This catalytic CVD technique is achieved based on our finding that MgO, Ni or Fe are the good catalysts for the growth of BNNTs. The success of patterned growth not only explains the role of catalysts in the formation of BNNTs, this technique will also become technologically important for future device fabrication of BNNTs. Following our success in controlled growth of BNNTs on substrates, we have discovered the superhydrophobic behavior of these partially vertically aligned BNNTs. Since BNNTs are chemically inert, resistive to oxidation up to ~1000°C, and transparent to UV-visible light, our discovery suggests that BNNTs could be useful as self-cleaning, insulating and protective coatings under rigorous chemical and thermal conditions. We have also established various approaches to functionalize BNNTs with polymeric molecules and carbon coatings. First, we showed that BNNTs can be functionalized by mPEG-DSPE (Polyethylene glycol-1,2-distearoyl-sn-glycero-3-phosphoethanolamine), a bio-compatible polymer that helps disperse and dissolve BNNTs in water solution. Furthermore, well-dispersed BNNTs in water can be cut from its original length of >10µm to(>20hrs). This success is an essential step to implement BNNTs in biomedical applications. On the other hand, we have also succeeded to functionalize BNNTs with various conjugated polymers. This success enables the dispersion of BNNTs in organic solvents instead of water. Our approaches are useful for applications of BNNTs in high-strength composites. In addition, we have also functionalized BNNTs with carbon decoration. This was performed by introducing methane (CH4) gas into the growth process of BNNT. Graphitic carbon coatings can be deposited on the side wall of BNNTs with thicknesses ranging from 2 to 5 nm. This success can modulate the conductivity of pure BNNTs from insulating to weakly electrically conductive. Finally, efforts were devoted to explore the application of the wide bandgap BNNTs in solar-blind deep UV (DUV) photo-detectors. We found that photoelectric current generated by the DUV light was dominated in the microelectrodes of our devices. The contribution of photocurrent from BNNTs is not significant if there is any. Implication from these preliminary experiments and potential future work are discussed.

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Polylactide (PLA) is a biodegradable polymer that has been used in particle form for drug release, due to its biocompatibility, tailorable degradation kinetics, and desirable mechanical properties. Active pharmaceutical ingredients (APIs) may be either dissolved or encapsulated within these biomaterials to create micro- or nanoparticles. Delivery of an AIP within fine particles may overcome solubility or stability issues that can result in early elimination or degradation of the AIP in a hostile biological environment. Furthermore, it is a promising method for controlling the rate of drug delivery and dosage. The goal of this project is to develop a simple and cost-effective device that allows us to produce monodisperse micro- and nanocapsules with controllable size and adjustable sheath thickness on demand. To achieve this goal, we have studied the dual-capillary electrospray and pulsed electrospray. Dual-capillary electrospray has received considerable attention in recent years due to its ability to create core-shell structures in a single-step. However, it also increases the difficulty of controlling the inner and outer particle morphology, since two simultaneous flows are required. Conventional electrospraying has been mainly conducted using direct-current (DC) voltage with little control over anything but the electrical potential. In contrast, control over the input voltage waveform (i.e. pulsing) in electrospraying offers greater control over the process variables. Poly(L-lactic acid) (PLLA) microspheres and microcapsules were successfully fabricated via pulsed-DC electrospray and dual-capillary electrospray, respectively. Core shell combinations produced include: Water/PLLA, PLLA/polyethylene glycol (PEG), and oleic Acid/PLLA. In this study, we designed a novel high-voltage pulse forming network and a set of new designs for coaxial electrospray nozzles. We also investigated the effect of the pulsed voltage characteristics (e.g. pulse frequency, pulse amplitude and pulse width) on the particle’s size and uniformity. We found that pulse frequency, pulse amplitude, pulse width, and the combinations of these factors had a statistically significant effect on the particle’s size. In addition, factors such as polymer concentration, solvent type, feed flow rate, collection method, temperature, and humidity can significantly affect the size and shape of the particles formed.