983 resultados para 0904 Chemical Engineering


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Many industrial solids processes require the production of disperse particles. In industries such as food, personal care, and pharmaceuticals, particle formation is widely used to produce solid products or to separate substances in intermediate process steps. The most important characteristics known to impact the effectiveness of a solid product are purity, size, internal structure, and morphology. These characteristics are essential to maintain optimal operation of subsequent process steps and for obtaining the desired high quality product. This thesis aims to aid in the advancement of particle production technology by (1) investigating the use of a vibrating orifice aerosol generator (VOAG) for collecting data to predict particle attributes including morphology, size, and internal structure as a function of processing parameters such as solvent, solution concentration, air flow rate, and initial droplet size, as well as to (2) determine the extent to which uniform droplet evaporation can be a tool to achieve novel particle morphologies, controlled sizes, or internal structures (crystallinity and crystal form). Experimental results for succinic acid, L-serine, and L-glutamic acid suggest that particles of controlled characteristics can indeed be produced by this method. Analysis by scanning electron microscopy (SEM), nanoindentation, and X-ray diffraction (XRD) shows that various sizes, internal structures, and morphologies can be obtained using the VOAG. Furthermore, unique morphologies and unexpected internal structures were able to be achieved for succinic acid, providing an added benefit to particle formation by this method.

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The Jing Ltd. miniature combustion aerosol standard (Mini-CAST) soot generator is a portable, commercially available burner that is widely used for laboratory measurements of soot processes. While many studies have used the Mini-CAST to generate soot with known size, concentration, and organic carbon fraction under a single or few conditions, there has been no systematic study of the burner operation over a wide range of operating conditions. Here, we present a comprehensive characterization of the microphysical, chemical, morphological, and hygroscopic properties of Mini-CAST soot over the full range of oxidation air and mixing N-2 flow rates. Very fuel-rich and fuel-lean flame conditions are found to produce organic-dominated soot with mode diameters of 10-60nm, and the highest particle number concentrations are produced under fuel-rich conditions. The lowest organic fraction and largest diameter soot (70-130nm) occur under slightly fuel-lean conditions. Moving from fuel-rich to fuel-lean conditions also increases the O:C ratio of the soot coatings from similar to 0.05 to similar to 0.25, which causes a small fraction of the particles to act as cloud condensation nuclei near the Kelvin limit (kappa similar to 0-10(-3)). Comparison of these property ranges to those reported in the literature for aircraft and diesel engine soots indicates that the Mini-CAST soot is similar to real-world primary soot particles, which lends itself to a variety of process-based soot studies. The trends in soot properties uncovered here will guide selection of burner operating conditions to achieve optimum soot properties that are most relevant to such studies.

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Drug release from a fluid-contacting biomaterial is simulated using a microfluidic device with a channel defined by solute-loaded hydrogel; as water is pumped through the channel, solute transfers from the hydrogel into the water. Optical analysis of in-situ hydrogels, characterization of the microfluidic device effluent, and NMR methods were used to find diffusion coefficients of several dyes (model drugs) in poly( ethylene glycol) diacrylate (PEG-DA) hydrogels. Diffusion coefficients for methylene blue and sulforhodamine 101 in PEG-DA calculated using the three methods are in good agreement; both dyes are mobile in the hydrogel and elute from the hydrogel at the aqueous channel interface. However, the dye acid blue 22 deviates from typical diffusion behavior and does not release as expected from the hydrogel. Importantly, only the microfluidic method is capable of detecting this behavior. Characterizing solute diffusion with a combination of NMR, optical and effluent methods offer greater insight into molecular diffusion in hydrogels than employing each technique individually. The NMR method made precise measurements for solute diffusion in all cases. The microfluidic optical method was effective for visualizing diffusion of the optically active solutes. The optical and effluent methods show potential to be used to screen solutes to determine if they elute from a hydrogel in contact with flowing fluid. Our data suggest that when designing a drug delivery device, analyzing the diffusion from the molecular level to the device level is important to establish a complete picture of drug elution, and microfluidic methods to study such diffusion can play a key role. (C) 2013 Elsevier B.V. All rights reserved.

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Adding conductive carbon fillers to insulating thermoplastic resins increases composite electrical and thermal conductivity. Often, as much of a single type of carbon filler is added to achieve the desired conductivity, while still allowing the material to be molded into a bipolar plate for a fuel cell. In this study, varying amounts of three different carbons (carbon black, synthetic graphite particles, and carbon fiber) were added to Vectra A950RX Liquid Crystal Polymer. The in-plane thermal conductivity of the resulting single filler composites were tested. The results showed that adding synthetic graphite particles caused the largest increase in the in-plane thermal conductivity of the composite. The composites were modeled using ellipsoidal inclusion problems to predict the effective in-plane thermal conductivities at varying volume fractions with only physical property data of constituents. The synthetic graphite and carbon black were modeled using the average field approximation with ellipsoidal inclusions and the model showed good agreement with the experimental data. The carbon fiber polymer composite was modeled using an assemblage of coated ellipsoids and the model showed good agreement with the experimental data.

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Due to their high thermal efficiency, diesel engines have excellent fuel economy and have been widely used as a power source for many vehicles. Diesel engines emit less greenhouse gases (carbon dioxide) compared with gasoline engines. However, diesel engines emit large amounts of particulate matter (PM) which can imperil human health. The best way to reduce the particulate matter is by using the Diesel Particulate Filter (DPF) system which consists of a wall-flow monolith which can trap particulates, and the DPF can be periodically regenerated to remove the collected particulates. The estimation of the PM mass accumulated in the DPF and total pressure drop across the filter are very important in order to determine when to carry out the active regeneration for the DPF. In this project, by developing a filtration model and a pressure drop model, we can estimate the PM mass and the total pressure drop, then, these two models can be linked with a regeneration model which has been developed previously to predict when to regenerate the filter. There results of this project were: 1 Reproduce a filtration model and simulate the processes of filtration. By studying the deep bed filtration and cake filtration, stages and quantity of mass accumulated in the DPF can be estimated. It was found that the filtration efficiency increases faster during the deep-bed filtration than that during the cake filtration. A “unit collector” theory was used in our filtration model which can explain the mechanism of the filtration very well. 2 Perform a parametric study on the pressure drop model for changes in engine exhaust flow rate, deposit layer thickness, and inlet temperature. It was found that there are five primary variables impacting the pressure drop in the DPF which are temperature gradient along the channel, deposit layer thickness, deposit layer permeability, wall thickness, and wall permeability. 3 Link the filtration model and the pressure drop model with the regeneration model to determine the time to carry out the regeneration of the DPF. It was found that the regeneration should be initiated when the cake layer is at a certain thickness, since a cake layer with either too big or too small an amount of particulates will need more thermal energy to reach a higher regeneration efficiency. 4 Formulate diesel particulate trap regeneration strategies for real world driving conditions to find out the best desirable conditions for DPF regeneration. It was found that the regeneration should be initiated when the vehicle’s speed is high and during which there should not be any stops from the vehicle. Moreover, the regeneration duration is about 120 seconds and the inlet temperature for the regeneration is 710K.

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Electrospinning uses electrostatic forces to create nanofibers that are far smaller than conventional fiber spinning process. Nanofibers made with chitosan were created and techniques to control fibers diameter and were well developed. However, the adsorption of porcine parvovirus (PPV) was low. PPV is a small, nonenveloped virus that is difficult to remove due to its size, 18-26 nm in diameter, and its chemical stability. To improve virus adsorption, we functionalized the nanofibers with a quaternized amine, forming N-[(2-hydroxy-3-trimethylammonium) propyl] chitosan chloride (HTCC). This was blended with additives to increase the ability to form HTCC nanofibers. The additives changed the viscosity and conductivity of the electrospinning solution. We have successfully synthesized and functionalized HTCC nanofibers that absorb PPV. HTCC blend with graphene have the ability to remove a minimum of 99% of PPV present in solution.

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Phosphomolybdic acid (H3PMo12O40) along with niobium,pyridine and niobium exchanged phosphomolybdic acid catalysts were prepared. Ammonia adsorption microcalorimetry and methanol oxidation studies were carried out to investigate the acid sites strength acid/base/redox properties of each catalyst. The addition of niobium, pyridine or both increased the ammonia heat of adsorption and the total uptake. The catalyst with both niobium and pyridine demonstrated the largest number of strong sites. For the parent H3PMo12O40 catalyst, methanol oxidation favors the redox product. Incorporation of niobium results in similar selectivity to redox products but also results in no catalyst deactivation. Incorporation of pyridine instead changes to the selectivity to favor the acidic product. Finally, the inclusion of both niobium and pyridine results in strong selectivity to the acidic product while also showing no catalyst deactivation. Thus the presence of pyridine appears to enhance the acid property of the catalyst while niobium appears to stabilize the active site.

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Polymers are typically electrically and thermally insulating materials. The electrical and thermal conductivities of polymers can be increased by the addition conductive fillers such as carbons. Once the polymer composites have been made electrically and thermally conductive, they can be used in applications where these conductivities are desired such as electromagnetic shielding and static dissipation. In this project, three carbon nanomaterials are added to polycarbonate to enhance the electrical and thermal conductivity of the resulting composite. Hyperion Catalysis FIBRILs carbon nanotubes were added to a maximum loading of 8 wt%. Ketjenblack EC-600 JD carbon black was added to a maximum loading of 10 wt%. XG Sciences xGnP™ graphene nanoplatelets were added to a maximum loading of 15 wt%. These three materials have drastically different morphologies and will have varying effects on the various properties of polycarbonate composites. It was determined that carbon nanotubes have the largest effect on electrical conductivity with an 8 wt% carbon nanotube in polycarbonate composite having an electrical conductivity of 0.128 S/cm (from a pure polycarbonate value of 10-17 S/cm). Carbon black has the next largest effect with an 8 wt% carbon black in polycarbonate composite having an electrical conductivity of 0.008 S/cm. Graphene nanoplatelets have the least effect with an 8 wt% graphene nanoplatelet in polycarbonate having an electrical conductivity of 2.53 x 10-8 S/cm. Graphene nanoplatelets show a significantly higher effect on increasing thermal conductivity than either carbon nanotubes or carbon black. Mechanically, all three materials have similar effects with graphene nanoplatelets being somewhat more effective at increasing the tensile modulus of the composite than the other fillers. Carbon black and graphene nanoplatelets show standard carbon-filler rheology where the addition of filler increases the viscosity of the resulting composite. Carbon nanotubes, on the other hand, show an unexpected rheology. As carbon nanotubes are added to polycarbonate the viscosity of the composite is reduced below that of the original polycarbonate. It was seen that the addition of carbon nanotubes offsets the increased viscosity from a second filler, such as carbon black or graphene nanoplatelets.

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Electrochemical capacitors (ECs), also known as supercapacitors or ultracapacitors, are energy storage devices with properties between batteries and conventional capacitors. EC have evolved through several generations. The trend in EC is to combine a double-layer electrode with a battery-type electrode in an asymmetric capacitor configuration. The double-layer electrode is usually an activated carbon (AC) since it has high surface area, good conductivity, and relatively low cost. The battery-type electrode usually consists of PbO2 or Ni(OH)2. In this research, a graphitic carbon foam was impregnated with Co-substituted Ni(OH)2 using electrochemical deposition to serve as the positive electrode in the asymmetric capacitor. The purpose was to reduce the cost and weight of the ECs while maintaining or increasing capacitance and gravimetric energy storage density. The XRD result indicated that the nickel-carbon foam electrode was a typical α-Ni(OH)2. The specific capacitance of the nickel-carbon foam electrode was 2641 F/g at 5 mA/cm2, higher than the previously reported value of 2080 F/g for a 7.5% Al-substituted α-Ni(OH)2 electrode. Three different ACs (RP-20, YP-50F, and Ketjenblack EC-600JD) were evaluated through their morphology and electrochemical performance to determine their suitability for use in ECs. The study indicated that YP-50F demonstrated the better overall performance because of the combination of micropore and mesopore structures. Therefore, YP-50F was chosen to combine with the nickel-carbon foam electrode for further evaluation. Six cells with different mass ratios of negative to positive active mass were fabricated to study the electrochemical performance. Among the different mass ratios, the asymmetric capacitor with the mass ratio of 3.71 gave the highest specific energy and specific power, 24.5 W.h/kg and 498 W/kg, respectively.

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The flammability zone boundaries are very important properties to prevent explosions in the process industries. Within the boundaries, a flame or explosion can occur so it is important to understand these boundaries to prevent fires and explosions. Very little work has been reported in the literature to model the flammability zone boundaries. Two boundaries are defined and studied: the upper flammability zone boundary and the lower flammability zone boundary. Three methods are presented to predict the upper and lower flammability zone boundaries: The linear model The extended linear model, and An empirical model The linear model is a thermodynamic model that uses the upper flammability limit (UFL) and lower flammability limit (LFL) to calculate two adiabatic flame temperatures. When the proper assumptions are applied, the linear model can be reduced to the well-known equation yLOC = zyLFL for estimation of the limiting oxygen concentration. The extended linear model attempts to account for the changes in the reactions along the UFL boundary. Finally, the empirical method fits the boundaries with linear equations between the UFL or LFL and the intercept with the oxygen axis. xx Comparison of the models to experimental data of the flammability zone shows that the best model for estimating the flammability zone boundaries is the empirical method. It is shown that is fits the limiting oxygen concentration (LOC), upper oxygen limit (UOL), and the lower oxygen limit (LOL) quite well. The regression coefficient values for the fits to the LOC, UOL, and LOL are 0.672, 0.968, and 0.959, respectively. This is better than the fit of the "zyLFL" method for the LOC in which the regression coefficient’s value is 0.416.

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Supercritical carbon dioxide is used to exfoliate graphite, producing a small, several-layer graphitic flake. The supercritical conditions of 2000, 2500, and 3000 psi and temperatures of 40°, 50°, and 60°C, have been used to study the effect of critical density on the sizes and zeta potentials of the treated flakes. Photon Correlation Spectroscopy (PCS), Brunauer-Emmett-Teller (BET) surface area measurement, field emission scanning electron microscopy (FE-SEM), and atomic force microscopy (AFM) are used to observe the features of the flakes. N-methyl-2-pyrrolidinone (NMP), dimethylformamide (DMF), and isopropanol are used as co-solvents to enhance the supercritical carbon dioxide treatment. As a result, the PCS results show that the flakes obtained from high critical density treatment (low temperature and high pressure) are more stable due to more negative charges of zeta potential, but have smaller sizes than those from low critical density (high temperature and low pressure). However, when an additional 1-hour sonication is applied, the size of the flakes from low critical density treatment becomes smaller than those from high critical density treatment. This is probably due to more CO2 molecules stacked between the layers of the graphitic flakes. The zeta potentials of the sonicated samples were slightly more negative than nonsonicated samples. NMP and DMF co-solvents maintain stability and prevented reaggregation of the flakes better than isopropanol. The flakes tend to be larger and more stable as the treatment time increases since larger flat area of graphite is exfoliated. In these experiments, the temperature has more impact on the flakes than pressure. The BET surface area resultsshow that CO2 penetrates the graphite layers more than N2. Moreover, the negative surface area of the treated graphite indicates that the CO2 molecules may be adsorbed between the graphite layers during supercritical treatment. The FE-SEM and AFM images show that the flakes have various shapes and sizes. The effects of surfactants can be observed on the FE-SEM images of the samples in one percent by weight solution of SDBS in water since the sodium dodecylbenzene sulfonate (SDBS) residue covers all of the remaining flakes. The AFM images show that the vertical thickness of the graphitic flakes can ranges from several nanometers (less than ten layers thick), to more than a hundred nanometers. In conclusion, supercritical carbon dioxide treatment is a promising step compared to mechanical and chemical exfoliation techniques in the large scale production of thin graphitic flake, breaking down the graphite flakes into flakes only a fewer graphene layers thick.

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Thermally conductive resins are a class of material that show promise in many different applications. One growing field for their use is in the area of bipolar plate technology for fuel cell applications. In this work, a LCP was mixed with different types of carbon fillers to determine the effects of the individual carbon fillers on the thermal conductivity of the composite resin. In addition, mathematical modeling was performed on the thermal conductivity data with the goal of developing predictive models for the thermal conductivity of highly filled composite resins.

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In this project we developed conductive thermoplastic resins by adding varying amounts of three different carbon fillers: carbon black (CB), synthetic graphite (SG) and multi-walled carbon nanotubes (CNT) to a polypropylene matrix for application as fuel cell bipolar plates. This component of fuel cells provides mechanical support to the stack, circulates the gases that participate in the electrochemical reaction within the fuel cell and allows for removal of the excess heat from the system. The materials fabricated in this work were tested to determine their mechanical and thermal properties. These materials were produced by adding varying amounts of single carbon fillers to a polypropylene matrix (2.5 to 15 wt.% Ketjenblack EC-600 JD carbon black, 10 to 80 wt.% Asbury Carbon's Thermocarb TC-300 synthetic graphite, and 2.5 to 15 wt.% of Hyperion Catalysis International's FIBRILTM multi-walled carbon nanotubes) In addition, composite materials containing combinations of these three fillers were produced. The thermal conductivity results showed an increase in both through-plane and in-plane thermal conductivities, with the largest increase observed for synthetic graphite. The Department of Energy (DOE) had previously set a thermal conductivity goal of 20 W/m·K, which was surpassed by formulations containing 75 wt.% and 80 wt.% SG, yielding in-plane thermal conductivity values of 24.4 W/m·K and 33.6 W/m·K, respectively. In addition, composites containing 2.5 wt.% CB, 65 wt.% SG, and 6 wt.% CNT in PP had an in–plane thermal conductivity of 37 W/m·K. Flexural and tensile tests were conducted. All composite formulations exceeded the flexural strength target of 25 MPa set by DOE. The tensile and flexural modulus of the composites increased with higher concentration of carbon fillers. Carbon black and synthetic graphite caused a decrease in the tensile and flexural strengths of the composites. However, carbon nanotubes increased the composite tensile and flexural strengths. Mathematical models were applied to estimate through-plane and in-plane thermal conductivities of single and multiple filler formulations, and tensile modulus of single-filler formulations. For thermal conductivity, Nielsen's model yielded accurate thermal conductivity values when compared to experimental results obtained through the Flash method. For prediction of tensile modulus Nielsen's model yielded the smallest error between the predicted and experimental values. The second part of this project consisted of the development of a curriculum in Fuel Cell and Hydrogen Technologies to address different educational barriers identified by the Department of Energy. By the creation of new courses and enterprise programs in the areas of fuel cells and the use of hydrogen as an energy carrier, we introduced engineering students to the new technologies, policies and challenges present with this alternative energy. Feedback provided by students participating in these courses and enterprise programs indicate positive acceptance of the different educational tools. Results obtained from a survey applied to students after participating in these courses showed an increase in the knowledge and awareness of energy fundamentals, which indicates the modules developed in this project are effective in introducing students to alternative energy sources.