990 resultados para carbon black filler


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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.

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"June 19, 1953."

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In this paper, we investigate the effect of the solid surface on the fluid-fluid intermolecular potential energy. This modified fluid-fluid interaction energy due to the inducement of a solid surface is used in the grand canonical Monte Carlo (GCMC) simulation of various noble gases, nitrogen, and methane on graphitized thermal carbon black. This effect is such that the effective interaction potential energy between two particles close to surface is less than the potential energy if the solid substrate is not present. With this modification the GCMC simulation results agree extremely well with the experimental data over a wide range of pressures while the simulation results with the unmodified potential energy give rise to a shoulder near the neighborhood of monolayer coverage and the significant overprediction of the second and higher layer coverages. In particular the unmodified GCMC results exhibit very sharp change in those higher layers while the experimental data have a much gradual change in the uptake. We will illustrate this theory with adsorption data of argon, xenon, neon, nitrogen, and methane on graphitized thermal carbon black.

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We model nongraphitized carbon black surfaces and investigate adsorption of argon on these surfaces by using the grand canonical Monte Carlo simulation. In this model, the nongraphitized surface is modeled as a stack of graphene layers with some carbon atoms of the top graphene layer being randomly removed. The percentage of the surface carbon atoms being removed and the effective size of the defect ( created by the removal) are the key parameters to characterize the nongraphitized surface. The patterns of adsorption isotherm and isosteric heat are particularly studied, as a function of these surface parameters as well as pressure and temperature. It is shown that the adsorption isotherm shows a steplike behavior on a perfect graphite surface and becomes smoother on nongraphitized surfaces. Regarding the isosteric heat versus loading, we observe for the case of graphitized thermal carbon black the increase of heat in the submonolayer coverage and then a sharp decline in the heat when the second layer is starting to form, beyond which it increases slightly. On the other hand, the isosteric heat versus loading for a highly nongraphitized surface shows a general decline with respect to loading, which is due to the energetic heterogeneity of the surface. It is only when the fluid-fluid interaction is greater than the surface energetic factor that we see a minimum-maximum in the isosteric heat versus loading. These simulation results of isosteric heat agree well with the experimental results of graphitization of Spheron 6 (Polley, M. H.; Schaeffer, W. D.; Smith, W. R. J. Phys. Chem. 1953, 57, 469; Beebe, R. A.; Young, D. M. J. Phys. Chem. 1954, 58, 93). Adsorption isotherms and isosteric heat in pores whose walls have defects are also studied from the simulation, and the pattern of isotherm and isosteric heat could be used to identify the fingerprint of the surface.

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Grand canonical Monte Carlo simulations were applied to the adsorption of SPCE model water in finite graphitic pores with different configurations of carbonyl functional groups on only one surface and several pore sizes. It was found that almost all finite pores studied exhibit capillary condensation behaviour preceded by adsorption around the functional groups. Desorption showed the reverse transitions from a filled to a near empty pore resulting in a clear hysteresis loop in all pores except for some of the configurations of the 1.0nm pore. Carbonyl configurations had a strong effect on the filling pressure of all pores except, in some cases, in 1.0nm pores. A decrease in carbonyl neighbour density would result in a higher filling pressure. The emptying pressure was negligibly affected by the configuration of functional groups. Both the filling and emptying pressures increased with increasing pore size but the effect on the emptying pressure was much less. At pressures lower than the pore filling pressure, the adsorption of water was shown to have an extremely strong dependence on the neighbour density with adsorption changing from Type IV to Type III to linear as the neighbour density decreased. The isosteric heat was also calculated for these configurations to reveal its strong dependence on the neighbour density. These results were compared with literature experimental results for water and carbon black and found to qualitatively agree.

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A study has been made of the effect of single extensions and continuous fatigue on the structures of various natural rubber networks. The change in network structure of a conventional vulcanisate on a single extension manifests itself as permanent set. The change in network structure has been assessed by the use of the chemical probes, propan-2-thiol/piperidine, hexane-thiol/piperidine and triphenyl phosphine, which determine the polysulphide and disulphide crosslink densities and main chain modification respectively. The permanent set induced on a single extension of a conventional sulphur vulcanisate has been shown to result from the destruction and reformation of polysulphide crosslinks. The magnitude of the effect was dependent upon the degree of extension and showed a maximum at extensions corresponding to the onset of stress-induced crystallisation. The incorporation of a reinforcing filler, HAF-carbon black, magnified the effect. Vulcanisates that possessed only mono and disulphide crosslinks did not show any significant permanent set. The continuous changes in network structure during fatigue have also been determined, and the effects of carbon black and antioxidants on these changes and the fatigue life have been assessed. During fatigue the overall crosslink density increased slightly, which resulted from the destruction of polysulphide crosslinks. and their replacement by principally disulphide crosslinks. Antioxidants reduced the rate of destruction of polysulphide crosslinks and increased the fatigue life of the rubber network. The fatigue life of the network also depended upon the concentration of free chain ends. These chain ends were incorporated into the network by masticating rubber under nitrogen in the presence of bis (diisopropyl)thiophosphoryl disulphide, which improved the fatigue resistance by up to 9%.

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Electrically conductive elastomeric fibres prepared using a wet-spinning process are promising materials for intelligent textiles, in particular as a strain sensing component of the fabric. However, these fibres, when reinforced with conducting fillers, typically result in a compromise between mechanical and electrical properties and, ultimately, in the strain sensing functionality. Here we investigate the wet-spinning of polyurethane (PU) fibres with a range of conducting fillers such as carbon black (CB), single-walled carbon nanotubes (SWCNTs), and chemically converted graphene. We show that the electrical and mechanical properties of the composite fibres were strongly dependent on the aspect ratio of the filler and the interaction between the filler and the elastomer. The high aspect ratio SWCNT filler resulted in fibres with the highest electrical properties and reinforcement, while the fibres produced from the low aspect ratio CB had the highest stretchability. Furthermore, PU/SWCNT fibres presented the largest sensing range (up to 60% applied strain) and the most consistent and stable cyclic sensing behaviour. This work provides an understanding of the important factors that influence the production of conductive elastomer fibres by wet-spinning, which can be woven or knitted into textiles for the development of wearable strain sensors.

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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 Carbons’ 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.

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Porous complex oxides are produced by reacting metal oxide precursors in the presence of a pore-forming material to provide pore sizes in the range of 7-250 nm, followed by removal of the pore-forming material under conditions preserving the structure and compn. of the formed oxides. The pore-forming material are carbon black particles having a particle size of 10-100 nm. The carbon particles are removed from the formed oxide by heating at 100-300°. A surfactant can be added to the reaction mixt. [on SciFinder(R)]

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An environmentally benign, highly conductive, and mechanically strong binder system can overcome the dilemma of low conductivity and insufficient mechanical stability of the electrodes to achieve high performance lithium ion batteries (LIBs) at a low cost and in a sustainable way. In this work, the naturally occurring binder sodium alginate (SA) is functionalized with 3,4-propylenedioxythiophene-2,5-dicarboxylic acid (ProDOT) via a one-step esterification reaction in a cyclohexane/dodecyl benzenesulfonic acid (DBSA)/water microemulsion system, resulting in a multifunctional polymer binder, that is, SA-PProDOT. With the synergetic effects of the functional groups (e.g., carboxyl, hydroxyl, and ester groups), the resultant SA-PProDOT polymer not only maintains the outstanding binding capabilities of sodium alginate but also enhances the mechanical integrity and lithium ion diffusion coefficient in the LiFePO4 (LFP) electrode during the operation of the batteries. Because of the conjugated network of the PProDOT and the lithium doping under the battery environment, the SA-PProDOT becomes conductive and matches the conductivity needed for LiFePO4 LIBs. Without the need of conductive additives such as carbon black, the resultant batteries have achieved the theoretical specific capacity of LiFePO4 cathode (ca. 170 mAh/g) at C/10 and ca. 120 mAh/g at 1C for more than 400 cycles.

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2 V/40 Ah valve-regulated lead-acid (VRLA) cells have been constructed with negative plates employing carbon black as well as an admixture of carbon black fumed silica as additives in negative active material for partial-state-of-charge (PSoC) applications. Electrical performance of such cells is compared with conventional 2 V/40 Ah VRLA cells for PSoC operation. Active material utilization has been found to be higher for carbon-black fumed-silica mixed negative plates while formation is faster for cells with carbon-black mixed negative plates. Both faradaic efficiency and percentage capacity delivered have been found to be higher for cells with carbon-black + fumed-silica mixed negative plates. However, a high self-discharge rate is observed for cells with carbon-black + fumed-silica mixed negative plates.

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Ethylene gas is burnt to generate soot which is collected thermophoretically from different locations of the flame. Tribological performance of the collected soot in hexadecane suspension is compared with that of carbon black and diesel soot. The soots are analysed to yield a range of mechanical properties, physical structures and chemistry. The paper correlates these property variations with the corresponding variations in friction and wear when the soot suspended in hexadecane is used to lubricate a steel on steel sliding interaction. The particles are dispersed in hexadecane by a non-ionic surfactant, poly-isobutylene succinimide (PIBS), which is mono-functional with no free amine group. The grafting of the surfactant on the soot particles is found to have a profound effect on the dispersion of the soot, in general, while, between the different soot types, the tribology is differentiated by the physical structure and chemistry.

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An organic molecule-o-phenylene diamine (OPD)-is selected as an aldehyde sensing material. It is studied for selectivity to aldehyde vapours both by experiment and simulation. A chemiresistor based sensor for detection of aldehyde vapours is fabricated. An o-phenylene diamine-carbon black composite is used as the sensing element. The amine groups in the OPD would interact with the carbonyl groups of the aldehydes. The selectivity and cross-sensitivity of the OPD-CB sensor to VOCs aldehyde, ketone and alcohol-are studied. The sensor shows good response to aldehydes compared to other VOCs. The higher response for aldehydes is attributed to the interaction of the carbonyl oxygen of aldehydes with-NH2 groups of OPD. The surface morphology of the sensing element is studied by scanning electron microscopy. The OPD-CB sensor is responsive to 10 ppm of formaldehyde. The interaction of the VOCs with the OPD-CB nanocomposite is investigated by molecular dynamics studies. The interaction energies of the analyte with the OPD-CB nanocomposite were calculated. It is observed that the interaction energies for aldehydes are higher than those for other analytes. Thus the OPD-CB sensor shows selectivity to aldehydes. The simulated radial distribution function is calculated for the O-H pair of analyte and OPD which further supports the finding that the amine groups are involved in the interaction. These results suggest that it is important and easy to identify appropriate sensing materials based on the understanding of analyte interaction properties.

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In Pt-transition metal (TM) alloy catalysts, the electron transfer from the TM to Pt is retarded owing to the inevitable oxidation of the TM surface by oxygen. In addition, acidic electrolytes such as those employed in fuel cells accelerate the dissolution of the surface TM oxide, which leads to catalyst degradation. Herein, we propose a novel synthesis strategy that selectively modifies the electronic structure of surface Co atoms with N-containing polymers, resulting in highly active and durable PtCo nanoparticle catalysts useful for the oxygen reduction reaction (ORR). The polymer, which is functionalized on carbon black, selectively interacts with the Co precursor, resulting in Co-N bond formation on the PtCo nanoparticle surface. Electron transfer from Co to Pt in the PtCo nanoparticles modified by the polymer is enhanced by the increase in the difference in electronegativity between Pt and Co compared with that in bare PtCo nanoparticles with the TM surface oxides. In addition, the dissolution of Co and Pt is prevented by the selective passivation of surface Co atoms and the decrease in the O-binding energy of surface Pt atoms. As a result, the catalytic activity and durability of PtCo nanoparticles for the ORR are significantly improved by the electronic ensemble effects. The proposed organic/inorganic hybrid concept will provide new insights into the tuning of nanomaterials consisting of heterogeneous metallic elements for various electrochemical and chemical applications.

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Humans are able of distinguishing more than 5000 visual categories even in complex environments using a variety of different visual systems all working in tandem. We seem to be capable of distinguishing thousands of different odors as well. In the machine learning community, many commonly used multi-class classifiers do not scale well to such large numbers of categories. This thesis demonstrates a method of automatically creating application-specific taxonomies to aid in scaling classification algorithms to more than 100 cate- gories using both visual and olfactory data. The visual data consists of images collected online and pollen slides scanned under a microscope. The olfactory data was acquired by constructing a small portable sniffing apparatus which draws air over 10 carbon black polymer composite sensors. We investigate performance when classifying 256 visual categories, 8 or more species of pollen and 130 olfactory categories sampled from common household items and a standardized scratch-and-sniff test. Taxonomies are employed in a divide-and-conquer classification framework which improves classification time while allowing the end user to trade performance for specificity as needed. Before classification can even take place, the pollen counter and electronic nose must filter out a high volume of background “clutter” to detect the categories of interest. In the case of pollen this is done with an efficient cascade of classifiers that rule out most non-pollen before invoking slower multi-class classifiers. In the case of the electronic nose, much of the extraneous noise encountered in outdoor environments can be filtered using a sniffing strategy which preferentially samples the visensor response at frequencies that are relatively immune to background contributions from ambient water vapor. This combination of efficient background rejection with scalable classification algorithms is tested in detail for three separate projects: 1) the Caltech-256 Image Dataset, 2) the Caltech Automated Pollen Identification and Counting System (CAPICS) and 3) a portable electronic nose specially constructed for outdoor use.