Classical Limit of Demagnetization in a Field Gradient

We calculate the rate of decrease of the expectation value of the transverse component of spin for spin-1/2 particles in a magnetic field with a spatial gradient, to determine the conditions under which a previous classical description is valid. A density matrix treatment is required for two reasons. The first arises because the particles initially are not in a pure state due to thermal motion. The second reason is that each particle interacts with the magnetic field and the other particles, with the latter taken to be via a 2-body central force. The equations for the 1-body Wigner distribution functions are written in a general manner, and the places where quantum mechanical effects can play a role are identified. One that may not have been considered previously concerns the momentum associated with the magnetic field gradient, which is proportional to the time integral of the gradient. Its relative magnitude compared with the important momenta in the problem is a significant parameter, and if their ratio is not small some non-classical effects contribute to the solution. Assuming the field gradient is sufficiently small, and a number of other inequalities are satisfied involving the mean wavelength, range of the force, and the mean separation between particles, we solve the integro- partial differential equations for the Wigner functions to second order in the strength of the gradient. When the same reasoning is applied to a different problem with no field gradient, but having instead a gradient to the z-component of polarization, the connection with the diffusion coefficient is established, and we find agreement with the classical result for the rate of decrease of the transverse component of magnetization.Comment: 22 pages, no figure

Measuring surface-area-to-volume ratios in soft porous materials using laser-polarized xenon interphase exchange NMR

We demonstrate a minimally invasive nuclear magnetic resonance (NMR) technique that enables determination of the surface-area-to-volume ratio (S/V) of soft porous materials from measurements of the diffusive exchange of laser-polarized 129Xe between gas in the pore space and 129Xe dissolved in the solid phase. We apply this NMR technique to porous polymer samples and find approximate agreement with destructive stereological measurements of S/V obtained with optical confocal microscopy. Potential applications of laser-polarized xenon interphase exchange NMR include measurements of in vivo lung function in humans and characterization of gas chromatography columns.Comment: 14 pages of text, 4 figure

NMR quantum computation with indirectly coupled gates

An NMR realization of a two-qubit quantum gate which processes quantum information indirectly via couplings to a spectator qubit is presented in the context of the Deutsch-Jozsa algorithm. This enables a successful comprehensive NMR implementation of the Deutsch-Jozsa algorithm for functions with three argument bits and demonstrates a technique essential for multi-qubit quantum computation.Comment: 9 pages, 2 figures. 10 additional figures illustrating output spectr

Influence of the Water Content on the Diffusion Coefficients of Li⁺ and Water across Naphthalenic Based Copolyimide Cation-Exchange Membranes

The transport of lithium ions in cation-exchange membranes based on sulfonated copolyimide membranes is reported. Diffusion coefficients of lithium are estimated as a function of the water content in membranes by using pulsed field gradient (PFG) NMR and electrical conductivity techniques. It is found that the lithium transport slightly decreases with the diminution of water for membranes with water content lying in the range 14 < λ < 26.5, where λ is the number of molecules of water per fixed sulfonate group. For λ < 14, the value of the diffusion coefficient of lithium experiences a sharp decay with the reduction of water in the membranes. The dependence of the diffusion of lithium on the humidity of the membranes calculated from conductivity data using Nernst–Planck type equations follows a trend similar to that observed by NMR. The possible explanation of the fact that the Haven ratio is higher than the unit is discussed. The diffusion of water estimated by 1H PFG-NMR in membranes neutralized with lithium decreases as λ decreases, but the drop is sharper in the region where the decrease of the diffusion of protons of water also undergoes considerable reduction. The diffusion of lithium ions computed by full molecular dynamics is similar to that estimated by NMR. However, for membranes with medium and low concentration of water, steady state conditions are not reached in the computations and the diffusion coefficients obtained by MD simulation techniques are overestimated. The curves depicting the variation of the diffusion coefficient of water estimated by NMR and full dynamics follow parallel trends, though the values of the diffusion coefficient in the latter case are somewhat higher. The WAXS diffractograms of fully hydrated membranes exhibit the ionomer peak at q = 2.8 nm⁻1, the peak being shifted to higher q as the water content of the membranes decreases. The diffractograms present additional peaks at higher q, common to wet and dry membranes, but the peaks are better resolved in the wet membranes. The ionomer peak is not detected in the diffractograms of dry membranes.The authors acknowledge financial support provided by the DGICYT (Dirección General de Investigación Cientifíca y Tecnológica) through Grant MAT2011-29174-C02-02

Validation of diffusion tensor MRI measurements of cardiac microstructure with structure tensor synchrotron radiation imaging.

Background Diffusion tensor imaging (DTI) is widely used to assess tissue microstructure non-invasively. Cardiac DTI enables inference of cell and sheetlet orientations, which are altered under pathological conditions. However, DTI is affected by many factors, therefore robust validation is critical. Existing histological validation is intrinsically flawed, since it requires further tissue processing leading to sample distortion, is routinely limited in field-of-view and requires reconstruction of three-dimensional volumes from two-dimensional images. In contrast, synchrotron radiation imaging (SRI) data enables imaging of the heart in 3D without further preparation following DTI. The objective of the study was to validate DTI measurements based on structure tensor analysis of SRI data. Methods One isolated, fixed rat heart was imaged ex vivo with DTI and X-ray phase contrast SRI, and reconstructed at 100 μm and 3.6 μm isotropic resolution respectively. Structure tensors were determined from the SRI data and registered to the DTI data. Results Excellent agreement in helix angles (HA) and transverse angles (TA) was observed between the DTI and structure tensor synchrotron radiation imaging (STSRI) data, where HADTI-STSRI = −1.4° ± 23.2° and TADTI-STSRI = −1.4° ± 35.0° (mean ± 1.96 standard deviation across all voxels in the left ventricle). STSRI confirmed that the primary eigenvector of the diffusion tensor corresponds with the cardiomyocyte long-axis across the whole myocardium. Conclusions We have used STSRI as a novel and high-resolution gold standard for the validation of DTI, allowing like-with-like comparison of three-dimensional tissue structures in the same intact heart free of distortion. This represents a critical step forward in independently verifying the structural basis and informing the interpretation of cardiac DTI data, thereby supporting the further development and adoption of DTI in structure-based electro-mechanical modelling and routine clinical applications

Mapping Human Whole-Brain Structural Networks with Diffusion MRI

Understanding the large-scale structural network formed by neurons is a major challenge in system neuroscience. A detailed connectivity map covering the entire brain would therefore be of great value. Based on diffusion MRI, we propose an efficient methodology to generate large, comprehensive and individual white matter connectional datasets of the living or dead, human or animal brain. This non-invasive tool enables us to study the basic and potentially complex network properties of the entire brain. For two human subjects we find that their individual brain networks have an exponential node degree distribution and that their global organization is in the form of a small world