Robust ferromagnetic insulating and large exchange bias in LaMnO3:CoO composite thin films

Ferromagnetic insulators have received widespread attention for applications in novel low power consumption spintronic devices. Further optimizing the robust ferromagnetic insulating and developing multifunctional ferromagnetic insulator by integrating other magnetic property can not only ease or pave the way for actual application, but also provide an additional freedom degree for device designing. In this work, by introducing antiferromagnetic CoO into ferromagnetic insulator LaMnO3, we have constructed (1-x)LaMnO3:xCoO composite thin films. The films simultaneously show robust ferromagnetic insulator characteristics and large exchange bias. For x = 0.5 sample, the resistivity is 120 Ω·cm at 250 K while the magnetization is 100 emu/cm3 and the exchange bias field is -2200 Oe at 10 K. Especially, the blocking temperature is up to 140 K. Synchrotron radiation x-ray absorption spectroscopy reveals the coexistence of Mn3+, Mn2+, Co2+ and Co3+, arising from interfacial charge transfer and space charge/defect trapping, should be responsible for the enhanced and integrated multifunctional magnetic properties.

Simulation on formation process of field-reversed configuration

Collisional-merging is a way to form high-performance field-reversed configuration (FRC) plasma. An experiment device named HUST-FRC (HFRC) is under construction in Huazhong University of Science and Technology, which will be used to investigate the FRC formation through collisional-merging. In this research, a magnetohydrodynamics (MHD) simulation software called USim is used to study the effect of the initial density of plasma, the amplitude of the bias magnetic field, the configuration of the bias field, the rise time of the main field and the magnetic field ripple on the plasma parameters to facilitate the designing and operations of HFRC. Preliminary simulation results show that cusp configuration, lower ripple, higher initial density, an initial bias field of -0.15 T or -0.2 T, and a rise time of 4 μs are conducive to the formation of high-performance FRC plasma in HFRC device.

The Effect of the Thermal Annealing Process to the Sensing Performance of Magnetoelastic Ribbon Materials

The magnetoelastic materials find many practical applications in everyday life like transformer cores, anti-theft tags, and sensors. The sensors should be very sensitive so as to be able to detect minute quantities of miscellaneous environmental parameters, which are very critical for sustainability such as pollution, air quality, corrosion, etc. Concerning the sensing sensitivity, the magnetoelastic material can be improved, even after its production, by either thermal annealing, as this method relaxes the internal stresses caused during manufacturing, or by applying an external DC magnetic bias field during the sensing operation. In the current work, we performed a systematic study on the optimum thermal annealing parameters of magnetoelastic materials and the Metglas alloy 2826 MB3 in particular. The study showed that a 100% signal enhancement can be achieved, without the presence of the bias field, just by annealing between 350 and 450 °C for at least half an hour. A smaller signal enhancement of 15% can be achieved with a bias field but only at much lower temperatures of 450 °C for a shorter time of 20 min. The magnetic hysteresis measurements show that during the annealing process, the material reorganizes itself, changing both its anisotropy energy and magnetostatic energy but in such a way such that the total material energy is approximately conserved.

Development of 3D MRI-Based Anatomically Realistic Models of Breast Tissues and Tumours for Microwave Imaging Diagnosis

Breast cancer diagnosis using radar-based medical MicroWave Imaging (MWI) has been studied in recent years. Realistic numerical and physical models of the breast are needed for simulation and experimental testing of MWI prototypes. We aim to provide the scientific community with an online repository of multiple accurate realistic breast tissue models derived from Magnetic Resonance Imaging (MRI), including benign and malignant tumours. Such models are suitable for 3D printing, leveraging experimental MWI testing. We propose a pre-processing pipeline, which includes image registration, bias field correction, data normalisation, background subtraction, and median filtering. We segmented the fat tissue with the region growing algorithm in fat-weighted Dixon images. Skin, fibroglandular tissue, and the chest wall boundary were segmented from water-weighted Dixon images. Then, we applied a 3D region growing and Hoshen-Kopelman algorithms for tumour segmentation. The developed semi-automatic segmentation procedure is suitable to segment tissues with a varying level of heterogeneity regarding voxel intensity. Two accurate breast models with benign and malignant tumours, with dielectric properties at 3, 6, and 9 GHz frequencies have been made available to the research community. These are suitable for microwave diagnosis, i.e., imaging and classification, and can be easily adapted to other imaging modalities.

Widespread Cortical Demyelination in Geriatric Cases of Mild Traumatic Brain Injury and in Alzheimer’s Disease

Cortical demyelination is related to neurodegeneration after mild traumatic brain injury (mTBI) and Alzheimer’s disease (AD). The ratio R of T1-to-T2-weighted magnetic resonance image (MRI) intensities is proportional to myelin content, and allows myelin changes to be mapped in vivo. T1 and T2 MRIs were acquired from mTBI patients (N = 97, age μ = 41 y; σ = 19 y, range: 21-79) both acutely and chronically (~1 week and ~6 months post-injury, respectively), from AD patients (N = 80, age μ = 76 y; σ = 8 y, range: 55-88), and from cognitively normal (CN) adults (N = 78, age μ = 75 y; σ = 5 y, range: 12-90). AD and CN subjects’ data were acquired less than a year apart. MRIs were analyzed using 3DSlicer’s BRAINSfit (registration), FreeSurfer (segmentation), SPM12 (bias field correction) and custom MATLAB scripts to calculate myelin content and demyelination. The null hypothesis of no myelin change was tested at each cortical location for each pair of groups (α = 0.05), after accounting for age, sex and interscan interval. Compared to HCs, AD subjects featured significantly greater myelin loss in dorsolateral prefrontal cortex, lateral and medial temporal lobes (~52% of the cortex, p < 0.05). mTBI participants experienced significantly greater myelin loss across ~96% of the cortex (p < 0.05), suggesting that mTBI has dramatic impact upon cortical myelin content. Myelin loss magnitude was comparable across mTBI and AD, particularly within temporal lobes. Future research should study whether post-traumatic demyelination increases the AD risk.

Brain MR Image Enhancement for Tumor Segmentation Using 3D U-Net

MRI images are visually inspected by domain experts for the analysis and quantification of the tumorous tissues. Due to the large volumetric data, manual reporting on the images is subjective, cumbersome, and error prone. To address these problems, automatic image analysis tools are employed for tumor segmentation and other subsequent statistical analysis. However, prior to the tumor analysis and quantification, an important challenge lies in the pre-processing. In the present study, permutations of different pre-processing methods are comprehensively investigated. In particular, the study focused on Gibbs ringing artifact removal, bias field correction, intensity normalization, and adaptive histogram equalization (AHE). The pre-processed MRI data is then passed onto 3D U-Net for automatic segmentation of brain tumors. The segmentation results demonstrated the best performance with the combination of two techniques, i.e., Gibbs ringing artifact removal and bias-field correction. The proposed technique achieved mean dice score metrics of 0.91, 0.86, and 0.70 for the whole tumor, tumor core, and enhancing tumor, respectively. The testing mean dice scores achieved by the system are 0.90, 0.83, and 0.71 for the whole tumor, core tumor, and enhancing tumor, respectively. The novelty of this work concerns a robust pre-processing sequence for improving the segmentation accuracy of MR images. The proposed method overcame the testing dice scores of the state-of-the-art methods. The results are benchmarked with the existing techniques used in the Brain Tumor Segmentation Challenge (BraTS) 2018 challenge.

The development of a passive, wireless sensor system

<p>This thesis describes the development of a prototype passive, wireless sensor system based on magnetoelastic sensor technology. The application of the sensor system is aimed at the measurement of humidity levels in sealed containers and structures, in particular the detection of moisture ingress in building structures. The system uses magnetoelastic sensor elements as is commonly used in commercial electronic article surveillance (EAS) systems for the prevention of shoplifting. Magnetoelastic Metglas® 2826MB material is evaluated and it is shown that the application of a magnetic bias field of the appropriate magnitude is critical for optimum sensor performance. The sensors can be activated for the detection of water vapour by the application of an appropriate chemical interface layer. A polyvinyl alcohol (PVA) layer was found to produce a resonant frequency response of approximately 50 Hz/RH(%). The design and construction of a portable electronic sensor reader is described and it is shown that the reader can successfully interrogate the sensor inside sealed spaces at practical distances. The construction of a practical humidity sensor using a PVA coating and the humidity response of the sensor system is then calibrated using a commercial humidity sensor. The system showed good response over the 0-100 % relative humidity range, with some non-linearity observed at high humidity levels. The completed sensor system was then evaluated for practical applications including measurements inside a sealed food container as well as inside a wall cavity. The results indicated that the constructed system was capable of measuring humidity with reasonable accuracy in such applications.</p>

The development of a passive, wireless sensor system

<p>This thesis describes the development of a prototype passive, wireless sensor system based on magnetoelastic sensor technology. The application of the sensor system is aimed at the measurement of humidity levels in sealed containers and structures, in particular the detection of moisture ingress in building structures. The system uses magnetoelastic sensor elements as is commonly used in commercial electronic article surveillance (EAS) systems for the prevention of shoplifting. Magnetoelastic Metglas® 2826MB material is evaluated and it is shown that the application of a magnetic bias field of the appropriate magnitude is critical for optimum sensor performance. The sensors can be activated for the detection of water vapour by the application of an appropriate chemical interface layer. A polyvinyl alcohol (PVA) layer was found to produce a resonant frequency response of approximately 50 Hz/RH(%). The design and construction of a portable electronic sensor reader is described and it is shown that the reader can successfully interrogate the sensor inside sealed spaces at practical distances. The construction of a practical humidity sensor using a PVA coating and the humidity response of the sensor system is then calibrated using a commercial humidity sensor. The system showed good response over the 0-100 % relative humidity range, with some non-linearity observed at high humidity levels. The completed sensor system was then evaluated for practical applications including measurements inside a sealed food container as well as inside a wall cavity. The results indicated that the constructed system was capable of measuring humidity with reasonable accuracy in such applications.</p>

Computer Simulation of Exchange Bias Field at the Ferromagnetic-Antiferromagnetic Boundary

This paper presents computer simulation results for a bilayer system with ferromagnetic and antiferromagnetic films. The dependence of the exchange bias field on the external magnetic field for this system is calculated. The Heisenberg model and the Wolf cluster algorithm are used for calculations. The reason for the appearance the bias field is the interaction between spins at the films interface. An increase the external magnetic field leads to a nonlinear increase the bias field. There are two reasons for nonlinearity. First, the external magnetic field suppresses antiferromagnetic ordering. Second, an external magnetic field-ordered ferromagnetic has an inverse effect on the antiferromagnetic film.