13C Nuclear magnetic resonance spectroscopic study of plasticization in solid polymer electrolytes

Preliminary results are presented on the correlation between enhanced solvent mobility and ionic conductivity in plasticized polyether–urethane solid polymer electrolytes using ¹³C nuclear magnetic resonance spectroscopic spin–lattice relaxation time measurements to probe polymer mobility.

A nuclear magnetic resonance study of 7Li dynamics in polyether-urethane based solid polymer electrolytes

Nuclear magnetic resonance (NMR) is a technique that allows the probing of the dynamics of specific magnetically active nuclei. In the present study a polyethylene glycol network containing varying concentrations of LiClO₄ have been studied using ⁷Li NMR relaxation techniques. A plasticiser, tetraglyme, has been added to several samples to improve the mobility of the polymer and thus of the ionic species. The effects of tetraglyme and salt concentration on the cationic mobility and environment have been investigated using T₁ and T₂ relaxation experiments, with the presence of two cationic species of differing relaxation times (and possibly mobility) reported. The results are discussed with relevance to conductivity measurements made on similar samples.

Visualisation of chemical processes during corrosion of zinc using magnetic resonance imaging

Compositional and structural changes within an electrolyte solution above an electrochemically active metal surface have been visualised using magnetic resonance imaging (MRI) for the first time. In these proof-of-concept experiments, zinc metal was galvanically corroded in a saturated lithium chloride solution. Magnetic resonance relaxation maps were taken during the corrosion process and spatial variations in both T₁ and T₂ relaxation times were observed to change with time. These changes were attributed to changes in the speciation of zinc ions in the electrolyte.

Analysis of dynamic strains in tibia during human locomotion based on flexible multibody approach integrated with magnetic resonance imaging technique

Bone is known to adapt to the prevalent strain environment while the variation in strains, e.g., due to mechanical loading, modulates bone remodeling, and modeling. Dynamic strains rather than static strains provide the primary stimulus of bone functional adaptation. The finite element method can be generally used for estimating bone strains, but it may be limited to the static analysis of bone strains since the dynamic analysis requires expensive computation. Direct in vivo strain measurement, in turn, is an invasive procedure, limited to certain superficial bone sites, and requires surgical implementation of strain gauges and thus involves risks (e.g., infection). Therefore, to overcome difficulties associated with the finite element method and the in vivo strain measurements, the flexible multibody simulation approach has been recently introduced as a feasible method to estimate dynamic bone strains during physical activity. The purpose of the present study is to further strengthen the idea of using the flexible multibody approach for the analysis of dynamic bone strains. Besides discussing the background theory, magnetic resonance imaging is integrated into the flexible multibody approach framework so that the actual bone geometry could be better accounted for and the accuracy of prediction improved.

Two-dimensional correlation localized surface plasmon resonance spectroscopy for analysis of the interaction between metal nanoparticles and bovine serum albumin

Time-resolved extinction spectra assisted with two-dimensional correlation spectroscopy (2DCOS) analysis and principal component analysis (PCA) were employed to investigate the interaction between bovine serum albumin (BSA) and metal nanoparticles (NPs). A series of localized surface plasmon resonance (LSPR) spectra of metal NPs were measured just after a small amount of BSA was added into metal colloids. Through 2DCOS analysis, remarkable changes in the intensities of the LSPR were observed. The interaction process was totally divided into three periods according to the PCA. Transmission electron microscopy, dynamic light scattering, and ζ-potential measurements were also employed to characterize the interaction between BSA and metal NPs. The addition of BSA brings silver NPs to aggregate through the electrostatic interaction between them, but it has less effect on gold NPs. In a gold and silver mixed system, gold NPs can affect the interaction of silver NPs and BSA, leading it to weaken. The combination of 2DCOS analysis and LSPR spectroscopy is powerful for exploring the LSPR spectra of the metal NP involved systems. This combined technique holds great potential in LSPR sensing through analysis of slight, slim spectral changes of metal colloids

Computer-aided detection of depression from magnetic resonance images

Magnetic resonance imaging (MRI) of the brain is used to detect depression disorder. However, a large number of MRI scans needs to be analyzed for such detection. Manual segmentation of the biomarkers in MRI scans by clinical experts can become time consuming and sometimes erroneous. This paper presents a study on computer-aided detection of depression from MRI scans. These systems have not yet been identified, categorized and compared in the literature. The paper covers fully automated to semi-automated detection systems. It also presents performance comparison for the considered systems.

Towards automated detection of depression from brain structural magnetic resonance images

Introduction : Depression is a major issue worldwide and is seen as a significant health problem. Stigma and patient denial, clinical experience, time limitations, and reliability of psychometrics are barriers to the clinical diagnoses of depression. Thus, the establishment of an automated system that could detect such abnormalities would assist medical experts in their decision-making process. This paper reviews existing methods for the automated detection of depression from brain structural magnetic resonance images (sMRI).Methods : Relevant sources were identified from various databases and online sites using a combination of keywords and terms including depression, major depressive disorder, detection, classification, and MRI databases. Reference lists of chosen articles were further reviewed for associated publications.Results : The paper introduces a generic structure for representing and describing the methods developed for the detection of depression from sMRI of the brain. It consists of a number of components including acquisition and preprocessing, feature extraction, feature selection, and classification.Conclusion : Automated sMRI-based detection methods have the potential to provide an objective measure of depression, hence improving the confidence level in the diagnosis and prognosis of depression.

Measuring miscible fluid displacement in porous media with magnetic resonance imaging

The development of new quantitative magnetic resonance imaging (MRI) technologies open new opportunities for measurements of mass transport in porous media. The current work examines a simple miscible displacement process of H2O and D2O in porous media samples. Laboratory measurements of dispersion in porous media traditionally monitor the effluent intensity of an injected tracer. We employ MRI to obtain quantitative water saturation profiles, and to measure dispersion in rock core plugs. The saturation profiles are modeled with PHREEQC, a fluid transport modeling program. We demonstrate how independent magnetic resonance measurements can be employed to estimate three important input parameters for PHREEQC, mobile porosity, immobile porosity, and dispersivity. Bulk Carr Purcell Meiboom Gill (CPMG) T2 distribution measurements were undertaken to estimate mobile and immobile porosity. Bulk alternating-pulsed-gradient-stimulated-echo (APGSTE) measurements were undertaken to measure dispersivity. The imaging method employed, T2 mapping Spin Echo Single Point Imaging (SE-SPI), also provides information about the pore size distributions in the rock cores, and how the fluid occupancy of the pores changes during the displacement process.