994 resultados para Magnetic circuit


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Total Artificial Hearts are mechanical pumps which can be used to replace the failing natural heart. This novel study developed a means of controlling a new design of pump to reproduce physiological flow bringing closer the realisation of a practical artificial heart. Using a mathematical model of the device, an optimisation algorithm was used to determine the best configuration for the magnetic levitation system of the pump. The prototype device was constructed and tested in a mock circulation loop. A physiological controller was designed to replicate the Frank-Starling like balancing behaviour of the natural heart. The device and controller provided sufficient support for a human patient while also demonstrating good response to various physiological conditions and events. This novel work brings the design of a practical artificial heart closer to realisation.

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Zinc oxide (ZnO) that contains non-magnetic ionic dopants, such as nitrogen (N)-doped zinc oxide (ZnO:N), has been observed to exhibit ferromagnetism. Ferromagnetism is proposed to arise from the Coulomb excitation in the localized states that is induced by the oxygen vacancy, V O. A model based on the Coulomb excitation that is associated with the electron–phonon interaction theoretically explains the ferromagnetic mechanism of ZnO:N. This study reveals that the ferromagnetism will be induced by either deep localized states with a small V O concentration or shallow localized states with a high V O concentration. Additionally, electron–phonon coupling either suppresses the ferromagnetism that is induced by the deep donor states of V O or enhances the ferromagnetism that is induced by the shallow donor states of V O.

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Numerical simulations of thermomagnetic convection of paramagnetic fluids placed in a micro-gravity condition (g ≈ 0) and under a uniform vertical gradient magnetic field in an open ended square enclosure with ramp heating temperature condition applied on a vertical wall is investigated in this study. In presence of the strong magnetic gradient field thermal convection of the paramagnetic fluid might take place even in a zero-gravity environment as a direct consequence of temperature differences occurring within the fluid. The thermal boundary layer develops adjacent to the hot wall as soon as the ramp temperature condition is applied on it. There are two scenarios can be observed based on the ramp heating time. The steady state of the thermal boundary layer can be reached before the ramp time is finished or vice versa. If the ramp time is larger than the quasi-steady time then the thermal boundary layer is in a quasi-steady mode with convection balancing conduction after the quasi-steady time. Further increase of the heat input simply accelerates the flow to maintain the proper thermal balance. Finally, the boundary layer becomes completely steady state when the ramp time is finished. Effects of magnetic Rayleigh number, Prandtl number and paramagnetic fluid parameter on the flow pattern and heat transfer are presented.

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In recent years, interest in tissue engineering and its solutions has increased considerably. In particular, scaffolds have become fundamental tools in bone graft substitution and are used in combination with a variety of bio-agents. However, a long-standing problem in the use of these conventional scaffolds lies in the impossibility of re-loading the scaffold with the bio-agents after implantation. This work introduces the magnetic scaffold as a conceptually new solution. The magnetic scaffold is able, via magnetic driving, to attract and take up in vivo growth factors, stem cells or other bio-agents bound to magnetic particles. The authors succeeded in developing a simple and inexpensive technique able to transform standard commercial scaffolds made of hydroxyapatite and collagen in magnetic scaffolds. This innovative process involves dip-coating of the scaffolds in aqueous ferrofluids containing iron oxide nanoparticles coated with various biopolymers. After dip-coating, the nanoparticles are integrated into the structure of the scaffolds, providing the latter with magnetization values as high as 15 emu g�1 at 10 kOe. These values are suitable for generating magnetic gradients, enabling magnetic guiding in the vicinity and inside the scaffold. The magnetic scaffolds do not suffer from any structural damage during the process, maintaining their specific porosity and shape. Moreover, they do not release magnetic particles under a constant flow of simulated body fluids over a period of 8 days. Finally, preliminary studies indicate the ability of the magnetic scaffolds to support adhesion and proliferation of human bone marrow stem cells in vitro. Hence, this new type of scaffold is a valuable candidate for tissue engineering applications, featuring a novel magnetic guiding option.

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Magnetic resonance imaging (MRI) offers the opportunity to study biological tissues and processes in a non-disruptive manner. The technique shows promise for the study of the load-bearing performance (consolidation) of articular cartilage and changes in articular cartilage accompanying osteoarthritis. Consolidation of articular cartilage involves the recording of two transient characteristics: the change over time of strain and the hydrostatic excess pore pressure (HEPP). MRI study of cartilage consolidation under mechanical load is limited by difficulties in measuring the HEPP in the presence of the strong magnetic fields associated with the MRI technique. Here we describe the use of MRI to image and characterize bovine articular cartilage deforming under load in an MRI compatible consolidometer while monitoring pressure with a Fabry-Perot interferometer-based fiber-optic pressure transducer.

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Numerical simulations of thermomagnetic convection of paramagnetic fluids placed in a micro-gravity condition (g nearly 0) and under a uniform vertical gradient magnetic field in an open ended square enclosure with ramp heating temperature condition applied on a vertical wall is investigated in this study. In presence of the strong magnetic gradient field thermal convection of the paramagnetic fluid might take place even in a zero-gravity environment as a direct consequence of temperature differences occurring within the fluid. The thermal boundary layer develops adjacent to the hot wall as soon as the ramp temperature condition is applied on it. There are two scenario that can be observed based on the ramp heating time. The steady state of the thermal boundary layer can be reached before the ramp time is finished or vice versa. If the ramp time is larger than the quasi-steady time then the thermal boundary layer is in a quasi-steady mode with convection balancing conduction after the quasi-steady time. Further increase of the heat input simply accelerates the flow to maintain the proper thermal balance. Finally, the boundary layer becomes completely steady state when the ramp time is finished. Effects of magnetic Rayleigh number, Prandtl number and paramagnetic fluid parameter on the flow pattern and heat transfer are presented.

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Customized magnetic traps were developed to produce a domain of dense plasmas with a narrow ion beam directed to a particular area of the processed substrate. A planar magnetron coupled with an arc discharge source created the magnetic traps to confine the plasma electrons and generate the ion beam with the controlled ratio of ion-to-neutral fluxes. Images of the plasma jet patterns and numerical vizualizations help explaining the observed phenomena.

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The effect of a magnetic field of two magnetic coils on the ion current density distribution in the setup for low-temperature plasma deposition is investigated. The substrate of 400 mm diameter is placed at a distance of 325 mm from the plasma duct exit, with the two magnetic coils mounted symmetrically under the substrate at a distance of 140 mm relative to the substrate centre. A planar probe is used to measure the ion current density distribution along the plasma flux cross-sections at distances of 150, 230, and 325 mm from the plasma duct exit. It is shown that the magnetic field strongly affects the ion current density distribution. Transparent plastic films are used to investigate qualitatively the ion density distribution profiles and the effect of the magnetic field. A theoretical model is developed to describe the interaction of the ion fluxes with the negative space charge regions associated with the magnetic trapping of the plasmaelectrons. Theoretical results are compared with the experimental measurements, and a reasonable agreement is demonstrated.

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Characteristics of electrical breakdown of a planar magnetron enhanced with an electromagnet and a hollow-cathode structure, are studied experimentally and numerically. At lower pressures the breakdown voltage shows a dependence on the applied magnetic field, and the voltage necessary to achieve the self-sustained discharge regime can be significantly reduced. At higher pressures, the dependence is less sensitive to the magnetic field magnitude and shows a tendency of increased breakdown voltage at the stronger magnetic fields. A model of the magnetron discharge breakdown is developed with the background gas pressure and the magnetic field used as parameters. The model describes the motion of electrons, which gain energy by passing the electric field across the magnetic field and undergo collisions with neutrals, thus generating new bulk electrons. The electrons are in turn accelerated in the electric field and effectively ionize a sufficient amount of neutrals to enable the discharge self-sustainment regime. The model is based on the assumption about the combined classical and near-wall mechanisms of electron conductivity across the magnetic field, and is consistent with the experimental results. The obtained results represent a significant advance toward energy-efficient multipurpose magnetron discharges.

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The unique properties of graphene and carbon nanotubes made them the most promising nanomaterials attracting enormous attention, due to the prospects for applications in various nanodevices, from nanoelectronics to sensors and energy conversion devices. Here we report on a novel deterministic, single-step approach to simultaneous production and magnetic separation of graphene flakes and carbon nanotubes in an arc discharge by splitting the high-temperature growth and low-temperature separation zones using a non-uniform magnetic field and tailor-designed catalyst alloy, and depositing nanotubes and graphene in different areas. Our results are very relevant to the development of commercially-viable, single-step production of bulk amounts of high-quality graphene.

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The ability to control the properties of single-wall nanotubes (SWNTs) produced in the arc discharge is important for many practical applications. Our experiments suggest that the length of SWNTs significantly increases (up to 4000 nm), along with the purity of the carbon deposit, when the magnetic field is applied to arc discharge. Scanning electron microscopy and transmission electron microscopy analyses have demonstrated that the carbon deposit produced in the magnetic-field-enhanced arc mainly consists of the isolated and bunched SWNTs. A model of a carbon nanotube interaction and growth in the thermal plasma was developed, which considers several important effects such as anode ablation that supplies the carbon plasma in an anodic arc discharge technique, and the momentum, charge, and energy transfer processes between nanotube and plasma. It is shown that the nanotube charge with respect to the plasma as well as nanotube length depend on plasma density and electric field in the interelectrode gap. For instance, nanotube charge changes from negative to positive value with an electron density decrease. The numerical simulations based on the Monte Carlo technique were performed, which explain an increase in the nanotubes produced in the magnetic-field-enhanced arc discharge. © 2008 American Institute of Physics.

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A comparative study involving both experimental and numerical investigations was made to resolve a long-standing problem of understanding electron conductivity mechanism across magnetic field in low-temperature plasmas. We have calculated the plasma parameters from experimentally obtained electric field distribution, and then made a 'back' comparison with the distributions of electron energy and plasma density obtained in the experiment. This approach significantly reduces an influence of the assumption about particular phenomenology of the electron conductivity in plasma. The results of the experiment and calculations made by this technique have showed that the classical conductivity is not capable of providing realistic total current and electron energy, whereas the phenomenological anomalous Bohm mobility has demonstrated a very good agreement with the experiment. These results provide an evidence in favor of the Bohm conductivity, thus making it possible to clarify this pressing long-living question about the main driving mechanism responsible for the electron transport in low-temperature plasmas.

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An effective control of the ion current distribution over large-area (up to 103 cm2) substrates with the magnetic fields of a complex structure by using two additional magnetic coils installed under the substrate exposed to vacuum arc plasmas is demonstrated. When the magnetic field generated by the additional coils is aligned with the direction of the magnetic field generated by the guiding and focusing coils of the vacuum arc source, a narrow ion density distribution with the maximum current density 117 A m-2 is achieved. When one of the additional coils is set to generate the magnetic field of the opposite direction, an area almost uniform over the substrate of 103 cm2 ion current distribution with the mean value of 45 A m-2 is achieved. Our findings suggest that the system with the vacuum arc source and two additional magnetic coils can be effectively used for the effective, high throughput, and highly controllable plasma processing.

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Brain decoding of functional Magnetic Resonance Imaging data is a pattern analysis task that links brain activity patterns to the experimental conditions. Classifiers predict the neural states from the spatial and temporal pattern of brain activity extracted from multiple voxels in the functional images in a certain period of time. The prediction results offer insight into the nature of neural representations and cognitive mechanisms and the classification accuracy determines our confidence in understanding the relationship between brain activity and stimuli. In this paper, we compared the efficacy of three machine learning algorithms: neural network, support vector machines, and conditional random field to decode the visual stimuli or neural cognitive states from functional Magnetic Resonance data. Leave-one-out cross validation was performed to quantify the generalization accuracy of each algorithm on unseen data. The results indicated support vector machine and conditional random field have comparable performance and the potential of the latter is worthy of further investigation.