1000 resultados para Magnetic Levitation


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The ab initio cluster model approach has been used to study the electronic structure and magnetic coupling of KCuF3 and K2CuF4 in their various ordered polytype crystal forms. Due to a cooperative Jahn-Teller distortion these systems exhibit strong anisotropies. In particular, the magnetic properties strongly differ from those of isomorphic compounds. Hence, KCuF3 is a quasi-one-dimensional (1D) nearest neighbor Heisenberg antiferromagnet whereas K2CuF4 is the only ferromagnet among the K2MF4 series of compounds (M=Mn, Fe, Co, Ni, and Cu) behaving all as quasi-2D nearest neighbor Heisenberg systems. Different ab initio techniques are used to explore the magnetic coupling in these systems. All methods, including unrestricted Hartree-Fock, are able to explain the magnetic ordering. However, quantitative agreement with experiment is reached only when using a state-of-the-art configuration interaction approach. Finally, an analysis of the dependence of the magnetic coupling constant with respect to distortion parameters is presented.

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The results are presented of a combined periodic and cluster model approach to the electronic structure and magnetic interactions in the spin-chain compounds Ca2CuO3 and Sr2CuO3. An extended t-J model is presented that includes in-chain and interchain hopping and magnetic interaction processes with parameters extracted from ab initio calculations. For both compounds, the in-chain magnetic interaction is found to be around -240 meV, larger than in any of the other cuprates reported in the literature. The interchain magnetic coupling is found to be weakly antiferromagnetic, -1 meV. The effective in-chain hopping parameters are estimated to be ~650 meV for both compounds, whereas the value of the interchain hopping parameter is 30 meV for Sr2CuO3 and 40 meV for Ca2CuO3, in line with the larger interchain distance in the former compound. These effective parameters are shown to be consistent with expressions recently suggested for the Néel temperature and the magnetic moments, and with relations that emerge from the t-J model Hamiltonian. Next, we investigate the physical nature of the band gap. Periodic calculations indicate that an interpretation in terms of a charge-transfer insulator is the most appropriate one, in contrast to the suggestion of a covalent correlated insulator recently reported in the literature.

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The magnetic structure of the edge-sharing cuprate compound Li2CuO2 has been investigated with highly correlated ab initio electronic structure calculations. The first- and second-neighbor in-chain magnetic interactions are calculated to be 142 and -22 K, respectively. The ratio between the two parameters is smaller than suggested previously in the literature. The interchain interactions are antiferromagnetic in nature and of the order of a few K only. Monte Carlo simulations using the ab initio parameters to define the spin model Hamiltonian result in a Nel temperature in good agreement with experiment. Spin population analysis situates the magnetic moment on the copper and oxygen ions between the completely localized picture derived from experiment and the more delocalized picture based on local-density calculations.

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The electronic and magnetic structures of the LaMnO3 compound have been studied by means of periodic calculations within the framework of spin polarized hybrid density-functional theory. In order to quantify the role of approximations to electronic exchange and correlation three different hybrid functionals have been used which mix nonlocal Fock and local Dirac-Slater exchange. Periodic Hartree-Fock results are also reported for comparative purposes. The A-antiferromagnetic ground state is properly predicted by all methods including Hartree-Fock exchange. In general, the different hybrid methods provide a rather accurate description of the band gap and of the two magnetic coupling constants, strongly suggesting that the corresponding description of the electronic structure is also accurate. An important conclusion emerging from this study is that the nature of the occupied states near the Fermi level is intermediate between the Hartree-Fock and local density approximation descriptions with a comparable participation of both Mn and O states.

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The development of new materials has been the hall mark of human civilization. The quest for making new devices and new materials has prompted humanity to pursue new methods and techniques that eventually has given birth to modern science and technology. With the advent of nanoscience and nanotechnology, scientists are trying hard to tailor materials by varying their size and shape rather than playing with the composition of the material. This, along with the discovery of new and sophisticated imaging tools, has led to the discovery of several new classes of materials like (3D) Graphite, (2D) graphene, (1D) carbon nanotubes, (0D) fullerenes etc. Magnetic materials are in the forefront of applications and have beencontributing their share to remove obsolescence and bring in new devices based on magnetism and magnetic materials. They find applications in various devices such as electromagnets, read heads, sensors, antennas, lubricants etc. Ferromagnetic as well as ferrimagnetic materials have been in use in the form of various devices. Among the ferromagnetic materials iron, cobalt and nickel occupy an important position while various ferrites finds applications in devices ranging from magnetic cores to sensors.

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Magnetic Resonance Imaging (MRI) is a multi sequence medical imaging technique in which stacks of images are acquired with different tissue contrasts. Simultaneous observation and quantitative analysis of normal brain tissues and small abnormalities from these large numbers of different sequences is a great challenge in clinical applications. Multispectral MRI analysis can simplify the job considerably by combining unlimited number of available co-registered sequences in a single suite. However, poor performance of the multispectral system with conventional image classification and segmentation methods makes it inappropriate for clinical analysis. Recent works in multispectral brain MRI analysis attempted to resolve this issue by improved feature extraction approaches, such as transform based methods, fuzzy approaches, algebraic techniques and so forth. Transform based feature extraction methods like Independent Component Analysis (ICA) and its extensions have been effectively used in recent studies to improve the performance of multispectral brain MRI analysis. However, these global transforms were found to be inefficient and inconsistent in identifying less frequently occurred features like small lesions, from large amount of MR data. The present thesis focuses on the improvement in ICA based feature extraction techniques to enhance the performance of multispectral brain MRI analysis. Methods using spectral clustering and wavelet transforms are proposed to resolve the inefficiency of ICA in identifying small abnormalities, and problems due to ICA over-completeness. Effectiveness of the new methods in brain tissue classification and segmentation is confirmed by a detailed quantitative and qualitative analysis with synthetic and clinical, normal and abnormal, data. In comparison to conventional classification techniques, proposed algorithms provide better performance in classification of normal brain tissues and significant small abnormalities.

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The Brueckner-Hartree-Fock formalism is applied to study spin polarized neutron matter properties. Results of the total energy per particle as a function of the spin polarization and density are presented for two modern realistic nucleon-nucleon interactions, Nijmegen II and Reid93. We find that the dependence of the energy on the spin polarization is practically parabolic in the full range of polarizations. The magnetic susceptibility of the system is computed. Our results show no indication of a ferromagnetic transition which becomes even more difficult as the density increases.

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By using techniques of unitarized chiral perturbation theory, where the Lamda(1405) and Lamda(1670) resonances are dynamically generated, we evaluate the magnetic moments of these resonances and their transition magnetic moment. The results obtained here differ appreciably from those obtained with existing quark models. The width for the Lamda(1670)->Lamda(1405)gamma transition is also evaluated, leading to a branching ratio of the order of 210-6.

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Cerebral glioma is the most prevalent primary brain tumor, which are classified broadly into low and high grades according to the degree of malignancy. High grade gliomas are highly malignant which possess a poor prognosis, and the patients survive less than eighteen months after diagnosis. Low grade gliomas are slow growing, least malignant and has better response to therapy. To date, histological grading is used as the standard technique for diagnosis, treatment planning and survival prediction. The main objective of this thesis is to propose novel methods for automatic extraction of low and high grade glioma and other brain tissues, grade detection techniques for glioma using conventional magnetic resonance imaging (MRI) modalities and 3D modelling of glioma from segmented tumor slices in order to assess the growth rate of tumors. Two new methods are developed for extracting tumor regions, of which the second method, named as Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA) can also extract white matter and grey matter from T1 FLAIR an T2 weighted images. The methods were validated with manual Ground truth images, which showed promising results. The developed methods were compared with widely used Fuzzy c-means clustering technique and the robustness of the algorithm with respect to noise is also checked for different noise levels. Image texture can provide significant information on the (ab)normality of tissue, and this thesis expands this idea to tumour texture grading and detection. Based on the thresholds of discriminant first order and gray level cooccurrence matrix based second order statistical features three feature sets were formulated and a decision system was developed for grade detection of glioma from conventional T2 weighted MRI modality.The quantitative performance analysis using ROC curve showed 99.03% accuracy for distinguishing between advanced (aggressive) and early stage (non-aggressive) malignant glioma. The developed brain texture analysis techniques can improve the physician’s ability to detect and analyse pathologies leading to a more reliable diagnosis and treatment of disease. The segmented tumors were also used for volumetric modelling of tumors which can provide an idea of the growth rate of tumor; this can be used for assessing response to therapy and patient prognosis.

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Ten new copper(II) complexes of five potential bisthiocarbohydrazone and biscarbohydrazone ligands were synthesized and physico-chemically characterized. The spectral and magnetic studies of compounds are consistent with the formation of asymmetric di-, tri- or tetranuclear copper(II) complexes of deprotonated forms of respective ligands. The variable temperature magnetic susceptibility measurements of all complexes showantiferromagnetic interactions between the Cu(II) centers, in agreement with very broad powder EPR spectra. However, frozen solution EPR spectral studies are found in contradiction with the solid-state magnetic studies and indicate that the complexes are not very stable in solutions; the possible fragmentations of complexes are found in agreement with MALDI MS results. The EPR spectral simulation of most of the compounds is in agreement with the presence of two uncoupled Cu(II) species in solution.

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Nanoparticles of nickel ferrite have been synthesized by the sol–gel method and the effect of grain size on its structural and magnetic properties have been studied in detail. X-ray diffraction (XRD) studies revealed that all the samples are single phasic possessing the inverse spinel structure. Grain size of the sol–gel synthesized powders has been determined from the XRD data and the strain graph. A grain size of 9 nm was observed for the as prepared powders of NiFe2O4 obtained through the sol–gel method. It was also observed that strain was induced during the firing process. Magnetization measurements have been carried out on all the samples prepared in the present series. It was found that the specific magnetization of the nanosized NiFe2O4 powders was lower than that of the corresponding coarse-grained counterparts and decreased with a decrease in grain size. The coercivity of the sol–gel synthesized NiFe2O4 nanoparticles attained a maximum value when the grain size was 15nm and then decreased as the grain size was increased further.

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Zinc ferrite belongs to the class of normal spinels where it is assumed to have a cation distribution of Zn2`(Fe3`)2(O2~)4, and it is purported to be showing zero net magnetisation. However, there have been recent reports suggesting that zinc ferrite exhibits anomaly in its magnetisation. Zinc ferrite samples have been prepared by two di¤erent routes and have been analysed using low energy ion scattering, Mo¬ ssbauer spectroscopy and magnetic measurements. The results indicate that zinc occupies octahedral sites, contrary to the earlier belief that zinc occupies only the tetrahedral sites in a normal spinel. The amount of zinc on the B site increases with decrease in particle size. The LEIS results together with the Mo¬ ssbauer results and the magnetic measurements lead to the conclusion that zinc occupies the B site and the magnetisation exhibited by ultraÞne particles of zinc is due to short range ordering