High-Spin Molecules: Synthesis, X-ray Characterization, and Magnetic Behavior of Two New Cyano-Bridged Ni II 9 Mo V 6 and Ni II 9 W V 6 Clusters with a S = 12 Ground State

The preparations, X-ray structures, and magnetic characterizations are presented for two new pentadecanuclear cluster compounds:  [NiII{NiII(MeOH)3}8(μ-CN)30{MV(CN)3}6]·xMeOH·yH2O (MV = MoV (1) with x = 17, y = 1; MV = WV (2) with x = 15, y = 0). Both compounds crystallize in the monoclinic space group C2/c, with cell dimensions of a = 28.4957(18) Å, b = 19.2583(10) Å, c = 32.4279(17) Å, β = 113.155(6)°, and Z = 4 for 1 and a = 28.5278(16) Å, b = 19.2008(18) Å, c = 32.4072(17) Å, β = 113.727(6)°, and Z = 4 for 2. The structures of 1 and 2 consist of neutral cluster complexes comprising 15 metal ions, 9 NiII and 6 MV, all linked by μ-cyano ligands. Magnetic susceptibilities and magnetization measurements of compounds 1 and 2 in the crystalline and dissolved state indicate that these clusters have a S = 12 ground state, originating from intracluster ferromagnetic exchange interactions between the μ-cyano-bridged metal ions of the type NiII−NC−MV. Indeed, these data show clearly that the cluster molecules stay intact in solution. Ac magnetic susceptibility measurements reveal that the cluster compounds exhibit magnetic susceptibility relaxation phenomena at low temperatures since, with nonzero dc fields, χ‘ ‘M has a nonzero value that is frequency dependent. However, there appears no out-of-phase (χ‘ ‘M) signal in zero dc field down to 1.8 K, which excludes the expected signature for a single molecule magnet. This finding is confirmed with the small uniaxial magnetic anisotropy value for D of 0.015 cm-1, deduced from the high-field, high-frequency EPR measurement, which distinctly reveals a positive sign in D. Obviously, the overall magnetic anisotropy of the compounds is too low, and this may be a consequence of a small single ion magnetic anisotropy combined with the highly symmetric arrangement of the metal ions in the cluster molecule.

Influence of quantized massive matter fields on the Casimir effect

Charged massive matter fields of spin-0 and spin- 1/2 are quantized in the presence of an external uniform magnetic field in a spatial region bounded by two parallel plates. The most general set of boundary conditions at the plates, that is required by mathematical consistency and the self-adjointness of the Hamiltonian operator, is employed. The vacuum fluctuations of the matter field in the case of the magnetic field orthogonal to the plates are analyzed, and it is shown that the pressure from the vacuum onto the plates is positive and independent of the boundary condition, as well as of the distance between the plates. Possibilities of the detection of this new-type Casimir effect are discussed. Read More: http://www.worldscientific.com/doi/10.1142/S0217732315500996

Casimir effect with quantized charged spinor matter in background magnetic field

We study the influence of a background uniform magnetic field and boundary conditions on the vacuum of a quantized charged spinor matter field confined between two parallel neutral plates; the magnetic field is directed orthogonally to the plates. The admissible set of boundary conditions at the plates is determined by the requirement that the Dirac Hamiltonian operator be self-adjoint. It is shown that, in the case of a sufficiently strong magnetic field and a sufficiently large separation of the plates, the generalized Casimir force is repulsive, being independent of the choice of a boundary condition, as well as of the distance between the plates. The detection of this effect seems to be feasible in the foreseeable future.

A dual resonance, image -guided, volume localization technique for magnetic resonance spectroscopy

An interleaved, dual resonance, volume localization technique for $\sp1$H/$\sp{31}$P magnetic resonance spectroscopy has been designed, implemented on a 2 T imager/spectrometer, and verified with phantom studies.^ Localization techniques, including several single voxel techniques and spectroscopic imaging, were implemented, and studies were performed to compare the efficiency of each sequence of $\sp1$H/$\sp{31}$P spectral acquisitions. The sequence chosen was a hybrid of the stimulated echo single voxel technique and the spectroscopic imaging technique.^ Water suppression during the $\sp1$H spectral acquisitions was accomplished by the use of three narrow bandwidth RF saturation pulses in combination with three spoiler gradients. The spoiler gradient amplitudes were selected on the basis of a numerical solution of the Bloch equations. A post-acquisition water suppression algorithm was used to minimize any residual water signal.^ For interleaved $\sp1$H/$\sp{31}$P acquisitions, a dual resonance RF coil was constructed and interfaced to the existing RF detection system via a custom-designed dual resonance transcoupler and switching system. Programmable attenuators were incorporated to allow for changes in receiver and transmitter attenuation "on the fly".^ To provide the rapidly switched gradient fields required for the $\sp1$H/$\sp{31}$P acquisitions, an actively screened gradient coil system was designed and implemented. With this system, gradient field rise times on the order of 100 $\mu$s were obtained. These rapid switching times were necessary for minimizing intrasequence delays and for improving localization quality and water suppression efficiency.^ The interleaved $\sp1$H/$\sp{31}$P volume localization technique was tested using a two-compartment phantom. Analysis of the data showed that the spectral contamination was less than three percent. One-to-one spatial correspondence of the $\sp1$H and $\sp{31}$P spectra was verified and allowed for direct correlation of the spectral data with a standard magnetic resonance image. ^

Magnetic viscosity and paleomagnetism of the basement complex at DSDP Hole 77-538A

The basement at Catoche Knoll consists of Paleozoic gneiss and amphibolite intruded by several generations of early Jurassic diabase dikes. Upon exposure to a 1-oersted field for 9 days, the diabase and amphibolite acquire a viscous remanent magnetization (VRM) which ranges from 42 to 2047% of their natural remanent magnetization (NRM). A magnetic field of similar intensity is observed in the paleomagnetic facility of the Glomar Challenger, and it is therefore doubtful if accurate measurements of magnetic moments in such rocks can be made on board unless the facility is magnetically shielded. The significant VRM also indicates the futility of attempting to discern magnetic lineations from an ocean floor composed of such rocks. No strong correlation exists between the Königsberger ratio, which is usually less than 1, and the tendency to acquire a VRM. The VRM decay is typical of a Richter aftereffect, but the relaxation times vary widely among the samples studied. A stable remanence is observed after alternating field demagnetization to 200 Oe. The range of magnetic inclinations in the diabase dikes is consistent with 40Ar/39Ar dates of 190 and 160 Ma. The inclinations suggest that the Catoche Knoll block tilted more than 20° to the north after the final dike intrusion.

Magnetic properties of ODP Hole 116-717C

Dark gray and black mud turbidites cored on ODP Leg 116 commonly yielded large magnetic susceptibility peaks. What is more, these peaks displayed different shapes suggesting variations in sedimentological processes. Consequently, a detailed study of the magnetic properties of two of these turbidites was undertaken to better understand the source of their unusual magnetism. Physical properties were measured as was the demagnetization behavior of sample natural remanent magnetizations (NRMs). Subsequently, an anhysteretic remanent magnetization (ARM) and saturation isothermal remanent magnetization (SIRM) were imparted to the samples, demagnetized, and various grain size tests based on the behavior of these remanences were applied. Finally, magnetic concentrates from two samples were examined with a scanning electron microscope with the capability to do energy dispersive X-ray (EDX) analysis. The turbidites stand out from surrounding layers because of their high susceptibilities, NRMs, ARMs, SIRMs, and ratios of ARM and SIRM to susceptibility. Their alternating field and thermal demagnetization properties and IRM acquisition curves are consistent with titanomagnetite grains as the primary magnetic mineral with some amount of hematite present. These properties are very similar to those published for samples from the Deccan flood basalts and suggest this formation as a possible source of the magnetic grains. Magnetic granulometry tests implied that the magnetic particles behave dominantly as single-domain and pseudo-single-domain grains. Moreover, they also implied that the large variation in susceptibility observed in the black mud turbidites results from a tenfold increase in the concentration of titanomagnetite grains. Electron microscope, EDX, and SIRM analyses revealed detrital titanomagnetites with typical sizes around 8-10 µm, but as large as 20-25 µm. These are probably the dominant magnetic grains in the black mud turbidites; however, ARM and susceptibility frequency-dependence suggested that there may also be a submicrometer fraction present. Most of the observed titanomagnetite grains are tabular and some display exsolution lamellae, accounting for the pseudo-single-domain behavior despite their moderate sizes. We hypothesize that the magnetic mineral concentration variations are brought about by sedimentological factors. The heavier magnetic minerals may tend to sink to the bottom of a turbidite; however, sometimes turbidite turbulence may act to keep these tabular, medium-size grains in suspension longer than some other larger or more equidimensional grains. Consequently, the susceptibility peak shape may reflect the turbidite current velocities as well as other sedimentological factors.

Suppression of the intrinsic stochastic pinning of domain walls in magnetic nanostripes

Nanofabrication has allowed the development of new concepts such as magnetic logic and race-track memory, both of which are based on the displacement of magnetic domain walls on magnetic nanostripes. One of the issues that has to be solved before devices can meet the market demands is the stochastic behaviour of the domain wall movement in magnetic nanostripes. Here we show that the stochastic nature of the domain wall motion in permalloy nanostripes can be suppressed at very low fields (0.6-2.7 Oe). We also find different field regimes for this stochastic motion that match well with the domain wall propagation modes. The highest pinning probability is found around the precessional mode and, interestingly, it does not depend on the external field in this regime. These results constitute an experimental evidence of the intrinsic nature of the stochastic pinning of domain walls in soft magnetic nanostripes

Theory of a probe in a strong magnetic field

An asymptotic analysis of the Langmuir-probe problem in a quiescent, fully ionized plasma in a strong magnetic field is performed, for electron cyclotron radius and Debye length much smaller than probe radius, and this not larger than either ion cyclotron radius or mean free path. It is found that the electric potential, which is not confined to a sheath, controls the diffusion far from the probe; inside the magnetic tube bounded by the probe cross section the potential overshoots to a large value before decaying to its value in the body of the plasma. The electron current is independent of the shape of the body along the field and increases with ion temperature; due to the overshoot in the potential, (1) the current at negative voltages does not vary exponentially, (2) its magnitude is strongly reduced by the field, and (3) the usual sharp knee at space potential, disappears. In the regions of the C-V diagram studied the ion current is negligible or unaffected by the field. Some numerical results are presented.The theory, which fails beyond certain positive voltage, fields useful results for weak fields, too.

Evaluation of the Magnetic Field Generated by the Inverter of an Electric Vehicle

In hybrid and electric vehicles, passengers sit very close to an electric system of significant power, which means that they may be subjected to high electromagnetic fields. The hazards of long-term exposure to these fields must be taken into account when designing electric vehicles and their components. Among all the electric devices present in the power train, the electronic converter is the most difficult to analyze, given that it works with different frequencies. In this paper, a methodology to evaluate the magnetic field created by a power electronics converter is proposed. After a brief overview of the recommendations of electromagnetic fields exposure, the magnetic field produced by an inverter is analyzed using finite element techniques. The results obtained are compared to laboratory measurements, taken from a real inverter, in order to validate the model. Finally, results are used to draw some conclusions regarding vehicle design criteria and magnetic shielding efficiency.

Automated detection and classification of brain injury lesions on structural magnetic resonance imaging

El daño cerebral adquirido (DCA) es un problema social y sanitario grave, de magnitud creciente y de una gran complejidad diagnóstica y terapéutica. Su elevada incidencia, junto con el aumento de la supervivencia de los pacientes, una vez superada la fase aguda, lo convierten también en un problema de alta prevalencia. En concreto, según la Organización Mundial de la Salud (OMS) el DCA estará entre las 10 causas más comunes de discapacidad en el año 2020. La neurorrehabilitación permite mejorar el déficit tanto cognitivo como funcional y aumentar la autonomía de las personas con DCA. Con la incorporación de nuevas soluciones tecnológicas al proceso de neurorrehabilitación se pretende alcanzar un nuevo paradigma donde se puedan diseñar tratamientos que sean intensivos, personalizados, monitorizados y basados en la evidencia. Ya que son estas cuatro características las que aseguran que los tratamientos son eficaces. A diferencia de la mayor parte de las disciplinas médicas, no existen asociaciones de síntomas y signos de la alteración cognitiva que faciliten la orientación terapéutica. Actualmente, los tratamientos de neurorrehabilitación se diseñan en base a los resultados obtenidos en una batería de evaluación neuropsicológica que evalúa el nivel de afectación de cada una de las funciones cognitivas (memoria, atención, funciones ejecutivas, etc.). La línea de investigación en la que se enmarca este trabajo de investigación pretende diseñar y desarrollar un perfil cognitivo basado no sólo en el resultado obtenido en esa batería de test, sino también en información teórica que engloba tanto estructuras anatómicas como relaciones funcionales e información anatómica obtenida de los estudios de imagen. De esta forma, el perfil cognitivo utilizado para diseñar los tratamientos integra información personalizada y basada en la evidencia. Las técnicas de neuroimagen representan una herramienta fundamental en la identificación de lesiones para la generación de estos perfiles cognitivos. La aproximación clásica utilizada en la identificación de lesiones consiste en delinear manualmente regiones anatómicas cerebrales. Esta aproximación presenta diversos problemas relacionados con inconsistencias de criterio entre distintos clínicos, reproducibilidad y tiempo. Por tanto, la automatización de este procedimiento es fundamental para asegurar una extracción objetiva de información. La delineación automática de regiones anatómicas se realiza mediante el registro tanto contra atlas como contra otros estudios de imagen de distintos sujetos. Sin embargo, los cambios patológicos asociados al DCA están siempre asociados a anormalidades de intensidad y/o cambios en la localización de las estructuras. Este hecho provoca que los algoritmos de registro tradicionales basados en intensidad no funcionen correctamente y requieran la intervención del clínico para seleccionar ciertos puntos (que en esta tesis hemos denominado puntos singulares). Además estos algoritmos tampoco permiten que se produzcan deformaciones grandes deslocalizadas. Hecho que también puede ocurrir ante la presencia de lesiones provocadas por un accidente cerebrovascular (ACV) o un traumatismo craneoencefálico (TCE). Esta tesis se centra en el diseño, desarrollo e implementación de una metodología para la detección automática de estructuras lesionadas que integra algoritmos cuyo objetivo principal es generar resultados que puedan ser reproducibles y objetivos. Esta metodología se divide en cuatro etapas: pre-procesado, identificación de puntos singulares, registro y detección de lesiones. Los trabajos y resultados alcanzados en esta tesis son los siguientes: Pre-procesado. En esta primera etapa el objetivo es homogeneizar todos los datos de entrada con el objetivo de poder extraer conclusiones válidas de los resultados obtenidos. Esta etapa, por tanto, tiene un gran impacto en los resultados finales. Se compone de tres operaciones: eliminación del cráneo, normalización en intensidad y normalización espacial. Identificación de puntos singulares. El objetivo de esta etapa es automatizar la identificación de puntos anatómicos (puntos singulares). Esta etapa equivale a la identificación manual de puntos anatómicos por parte del clínico, permitiendo: identificar un mayor número de puntos lo que se traduce en mayor información; eliminar el factor asociado a la variabilidad inter-sujeto, por tanto, los resultados son reproducibles y objetivos; y elimina el tiempo invertido en el marcado manual de puntos. Este trabajo de investigación propone un algoritmo de identificación de puntos singulares (descriptor) basado en una solución multi-detector y que contiene información multi-paramétrica: espacial y asociada a la intensidad. Este algoritmo ha sido contrastado con otros algoritmos similares encontrados en el estado del arte. Registro. En esta etapa se pretenden poner en concordancia espacial dos estudios de imagen de sujetos/pacientes distintos. El algoritmo propuesto en este trabajo de investigación está basado en descriptores y su principal objetivo es el cálculo de un campo vectorial que permita introducir deformaciones deslocalizadas en la imagen (en distintas regiones de la imagen) y tan grandes como indique el vector de deformación asociado. El algoritmo propuesto ha sido comparado con otros algoritmos de registro utilizados en aplicaciones de neuroimagen que se utilizan con estudios de sujetos control. Los resultados obtenidos son prometedores y representan un nuevo contexto para la identificación automática de estructuras. Identificación de lesiones. En esta última etapa se identifican aquellas estructuras cuyas características asociadas a la localización espacial y al área o volumen han sido modificadas con respecto a una situación de normalidad. Para ello se realiza un estudio estadístico del atlas que se vaya a utilizar y se establecen los parámetros estadísticos de normalidad asociados a la localización y al área. En función de las estructuras delineadas en el atlas, se podrán identificar más o menos estructuras anatómicas, siendo nuestra metodología independiente del atlas seleccionado. En general, esta tesis doctoral corrobora las hipótesis de investigación postuladas relativas a la identificación automática de lesiones utilizando estudios de imagen médica estructural, concretamente estudios de resonancia magnética. Basándose en estos cimientos, se han abrir nuevos campos de investigación que contribuyan a la mejora en la detección de lesiones. ABSTRACT Brain injury constitutes a serious social and health problem of increasing magnitude and of great diagnostic and therapeutic complexity. Its high incidence and survival rate, after the initial critical phases, makes it a prevalent problem that needs to be addressed. In particular, according to the World Health Organization (WHO), brain injury will be among the 10 most common causes of disability by 2020. Neurorehabilitation improves both cognitive and functional deficits and increases the autonomy of brain injury patients. The incorporation of new technologies to the neurorehabilitation tries to reach a new paradigm focused on designing intensive, personalized, monitored and evidence-based treatments. Since these four characteristics ensure the effectivity of treatments. Contrary to most medical disciplines, it is not possible to link symptoms and cognitive disorder syndromes, to assist the therapist. Currently, neurorehabilitation treatments are planned considering the results obtained from a neuropsychological assessment battery, which evaluates the functional impairment of each cognitive function (memory, attention, executive functions, etc.). The research line, on which this PhD falls under, aims to design and develop a cognitive profile based not only on the results obtained in the assessment battery, but also on theoretical information that includes both anatomical structures and functional relationships and anatomical information obtained from medical imaging studies, such as magnetic resonance. Therefore, the cognitive profile used to design these treatments integrates information personalized and evidence-based. Neuroimaging techniques represent an essential tool to identify lesions and generate this type of cognitive dysfunctional profiles. Manual delineation of brain anatomical regions is the classical approach to identify brain anatomical regions. Manual approaches present several problems related to inconsistencies across different clinicians, time and repeatability. Automated delineation is done by registering brains to one another or to a template. However, when imaging studies contain lesions, there are several intensity abnormalities and location alterations that reduce the performance of most of the registration algorithms based on intensity parameters. Thus, specialists may have to manually interact with imaging studies to select landmarks (called singular points in this PhD) or identify regions of interest. These two solutions have the same inconvenient than manual approaches, mentioned before. Moreover, these registration algorithms do not allow large and distributed deformations. This type of deformations may also appear when a stroke or a traumatic brain injury (TBI) occur. This PhD is focused on the design, development and implementation of a new methodology to automatically identify lesions in anatomical structures. This methodology integrates algorithms whose main objective is to generate objective and reproducible results. It is divided into four stages: pre-processing, singular points identification, registration and lesion detection. Pre-processing stage. In this first stage, the aim is to standardize all input data in order to be able to draw valid conclusions from the results. Therefore, this stage has a direct impact on the final results. It consists of three steps: skull-stripping, spatial and intensity normalization. Singular points identification. This stage aims to automatize the identification of anatomical points (singular points). It involves the manual identification of anatomical points by the clinician. This automatic identification allows to identify a greater number of points which results in more information; to remove the factor associated to inter-subject variability and thus, the results are reproducible and objective; and to eliminate the time spent on manual marking. This PhD proposed an algorithm to automatically identify singular points (descriptor) based on a multi-detector approach. This algorithm contains multi-parametric (spatial and intensity) information. This algorithm has been compared with other similar algorithms found on the state of the art. Registration. The goal of this stage is to put in spatial correspondence two imaging studies of different subjects/patients. The algorithm proposed in this PhD is based on descriptors. Its main objective is to compute a vector field to introduce distributed deformations (changes in different imaging regions), as large as the deformation vector indicates. The proposed algorithm has been compared with other registration algorithms used on different neuroimaging applications which are used with control subjects. The obtained results are promising and they represent a new context for the automatic identification of anatomical structures. Lesion identification. This final stage aims to identify those anatomical structures whose characteristics associated to spatial location and area or volume has been modified with respect to a normal state. A statistical study of the atlas to be used is performed to establish which are the statistical parameters associated to the normal state. The anatomical structures that may be identified depend on the selected anatomical structures identified on the atlas. The proposed methodology is independent from the selected atlas. Overall, this PhD corroborates the investigated research hypotheses regarding the automatic identification of lesions based on structural medical imaging studies (resonance magnetic studies). Based on these foundations, new research fields to improve the automatic identification of lesions in brain injury can be proposed.

A new low magnetic field magnetar: the 2011 outburst of Swift J1822.3–1606

We report on the long-term X-ray monitoring with Swift, RXTE, Suzaku, Chandra, and XMM-Newton of the outburst of the newly discovered magnetar Swift J1822.3–1606 (SGR 1822–1606), from the first observations soon after the detection of the short X-ray bursts which led to its discovery, through the first stages of its outburst decay (covering the time span from 2011 July until the end of 2012 April). We also report on archival ROSAT observations which detected the source during its likely quiescent state, and on upper limits on Swift J1822.3–1606's radio-pulsed and optical emission during outburst, with the Green Bank Telescope and the Gran Telescopio Canarias, respectively. Our X-ray timing analysis finds the source rotating with a period of P = 8.43772016(2) s and a period derivative P = 8.3(2)×10−14 s s−1, which implies an inferred dipolar surface magnetic field of B sime 2.7 × 1013 G at the equator. This measurement makes Swift J1822.3–1606 the second lowest magnetic field magnetar (after SGR 0418+5729). Following the flux and spectral evolution from the beginning of the outburst, we find that the flux decreased by about an order of magnitude, with a subtle softening of the spectrum, both typical of the outburst decay of magnetars. By modeling the secular thermal evolution of Swift J1822.3–1606, we find that the observed timing properties of the source, as well as its quiescent X-ray luminosity, can be reproduced if it was born with a poloidal and crustal toroidal fields of Bp ~ 1.5 × 1014 G and B tor ~ 7 × 1014 G, respectively, and if its current age is ~550 kyr.

Crystal Structures, Magnetic Structures and Photophysics in Supramolecular Transition-Metal Oxalate Compounds

Polymeric two- and three-dimensional, homo- and heterometallic oxalatebridged coordination compounds offer exciting opportunities, mainly in the fields of molecular magnetism and photophysics. Given that a large variety of magnetic phenomena have been reported so far from these molecular magnets, very limited experience is gained from elastic neutron scattering experiments. Therefore, with two examples, we will address the topic of the elucidation of magnetic structures by means of the neutron scattering technique. In addition, due to the possibility of the variation of different metal ions in varying oxidation states, interesting photophysical processes can be observed within the extended three-dimensional host/guest systems.

Numerical modelling of thermal effects in rats due to high-field magnetic resonance imaging (0.5-1 GHz)

A finite-difference time-domain (FDTD) thermal model has been developed to compute the temperature elevation in the Sprague Dawley rat due to electromagnetic energy deposition in high-field magnetic resonance imaging (MRI). The field strengths examined ranged from 11.75-23.5 T (corresponding to H-1 resonances of 0.5-1 GHz) and an N-stub birdcage resonator was used to both transmit radio-frequency energy and receive the MRI signals. With an in-plane resolution of 1.95 mm, the inhomogeneous rat phantom forms a segmented model of 12 different tissue types, each having its electrical and thermal parameters assigned. The steady-state temperature distribution was calculated using a Pennes 'bioheat' approach. The numerical algorithm used to calculate the induced temperature distribution has been successfully validated against analytical solutions in the form of simplified spherical models with electrical and thermal properties of rat muscle. As well as assisting with the design of MRI experiments and apparatus, the numerical procedures developed in this study could help in future research and design of tumour-treating hyperthermia applicators to be used on rats in vivo.

Electromagnetic fields inside a lossy, multilayered spherical head phantom excited by MRI coils: models and methods

The precise evaluation of electromagnetic field (EMF) distributions inside biological samples is becoming an increasingly important design requirement for high field MRI systems. In evaluating the induced fields caused by magnetic field gradients and RF transmitter coils, a multilayered dielectric spherical head model is proposed to provide a better understanding of electromagnetic interactions when compared to a traditional homogeneous head phantom. This paper presents Debye potential (DP) and Dyadic Green's function (DGF)-based solutions of the EMFs inside a head-sized, stratified sphere with similar radial conductivity and permittivity profiles as a human head. The DP approach is formulated for the symmetric case in which the source is a circular loop carrying a harmonic-formed current over a wide frequency range. The DGF method is developed for generic cases in which the source may be any kind of RF coil whose current distribution can be evaluated using the method of moments. The calculated EMFs can then be used to deduce MRI imaging parameters. The proposed methods, while not representing the full complexity of a head model, offer advantages in rapid prototyping as the computation times are much lower than a full finite difference time domain calculation using a complex head model. Test examples demonstrate the capability of the proposed models/methods. It is anticipated that this model will be of particular value for high field MRI applications, especially the rapid evaluation of RF resonator (surface and volume coils) and high performance gradient set designs.