Theoretical and Experimental Studies of KLi6TaO6 as a Li-Ion Solid Electrolyte.

We study a hexagonal oxide KLi6TaO6 (KLTO), proposed as a Li-ion solid electrolyte, by using a recently developed screening method. First-principles calculations predict that KLTO presents a good Li-ion conductivity (σLi) and a low activation energy (Ea). Li migration is enhanced by the presence of excess Li ions in the interstitial region via a kick-out mechanism. Our experimental results demonstrate that Sn-doped KLTO presents a conductivity of 1 × 10-5 S cm-1, a σLi of 6 × 10-6 S cm-1, and a relatively low Ea of 36 kJ mol-1, which confirm the validity of the proposed screening method. Conversely, detailed analyses of the microstructure and X-ray diffraction patterns of KLTO samples indicate that a stable Li-excess condition is not achieved, therefore leaving potential improvement of the performance of KLTO as a Li-ion solid electrolyte by optimizing extrinsic doping and fabrication processes.

First-principles prediction of high oxygen-ion conductivity in trilanthanide gallates Ln3GaO6.

We systematically investigated trilanthanide gallates (Ln3GaO6) with the space group Cmc21 as oxygen-ion conductors using first-principles calculations. Six Ln3GaO6 (Ln = Nd, Gd, Tb, Ho, Dy, or Er) are both energetically and dynamically stable among 15 Ln3GaO6 compounds, which is consistent with previous experimental studies reporting successful syntheses of single phases. La3GaO6 and Lu3GaO6 may be metastable despite a slightly higher energy than those of competing reference states, as phonon calculations predict them to be dynamically stable. The formation and the migration barrier energies of an oxygen vacancy (V O) suggest that eight Ln3GaO6 (Ln = La, Nd, Gd, Tb, Ho, Dy, Er, or Lu) can act as oxygen-ion conductors based on V O. Ga plays a role of decreasing the distances between the oxygen sites of Ln3GaO6 compared with those of Ln2O3 so that a V O migrates easier with a reduced migration barrier energy. Larger oxygen-ion diffusivities and lower migration barrier energies of V O for the eight Ln3GaO6 are obtained for smaller atomic numbers of Ln having larger radii of Ln3+. Their oxygen-ion conductivities at 1000 K are predicted to have a similar order of magnitude to that of yttria-stabilized zirconia.

Adolescent binge drinking alters adult brain neurotransmitter gene expression, behavior, brain regional volumes, and neurochemistry in mice.

BACKGROUND: Binge drinking is common in human adolescents. The adolescent brain is undergoing structural maturation and has a unique sensitivity to alcohol neurotoxicity. Therefore, adolescent binge ethanol may have long-term effects on the adult brain that alter brain structure and behaviors that are relevant to alcohol-use disorders. METHODS: To determine whether adolescent ethanol (AE) binge drinking alters the adult brain, male C57BL/6 mice were treated with either water or ethanol during adolescence (5 g/kg/d, i.g., postnatal days P28 to P37) and assessed during adulthood (P60 to P88). An array of neurotransmitter-specific genes, behavioral tests (i.e., reversal learning, prepulse inhibition, and open field), and postmortem brain structure using magnetic resonance imaging (MRI) and immunohistochemistry, were employed to assess persistent alterations in adult brain. RESULTS: At P38, 24 hours after AE binge, many neurotransmitter genes, particularly cholinergic and dopaminergic, were reduced by ethanol treatment. Interestingly, dopamine receptor type 4 mRNA was reduced and confirmed using immunohistochemistry. Normal control maturation (P38 to P88) resulted in decreased neurotransmitter mRNA, e.g., an average decrease of 56%. Following AE treatment, adults showed greater gene expression reductions than controls, averaging 73%. Adult spatial learning assessed in the Morris water maze was not changed by AE treatment, but reversal learning experiments revealed deficits. Assessment of adult brain region volumes using MRI indicated that the olfactory bulb and basal forebrain were smaller in adults following AE. Immunohistochemical analyses found reduced basal forebrain area and fewer basal forebrain cholinergic neurons. CONCLUSIONS: Adolescent binge ethanol treatment reduces adult neurotransmitter gene expression, particularly cholinergic genes, reduces basal forebrain and olfactory bulb volumes, and causes a reduction in the density of basal forebrain acetylcholine neurons. Loss of cholinergic neurons and forebrain structure could underlie adult reversal learning deficits following adolescent binge drinking.

Oxygen conduction mechanism in Ca3Fe2Ge3O12 garnet-type oxide.

We investigate the oxygen conduction mechanism in a garnet-type oxide, Ca3Fe2Ge3O12, for the first time in detail by first-principle calculations. The nudged elastic band results confirm that this oxide has a lower migration barrier energy (0.45 eV) for an oxygen interstitial (Oi) with the kick-out mechanism than that (0.76 eV) for an oxygen vacancy. The migration paths for Oi are delocalized and connected to the neighboring cells in three-dimensional space. This oxide does not have a very low formation energy of Oi when the Fermi level is near the lowest unoccupied molecular orbital at a high temperature, which implies the possibility of electron doping by high-valence cations. These theoretical results suggest that the doping of Ca3Fe2Ge3O12 for generation of excess Oi provides a good oxygen-ion conductivity, along with the electronic conductivity.

Highly efficient evaluation of diffusion networks in Li ionic conductors using a 3D-corrugation descriptor.

A highly efficient computational approach for the screening of Li ion conducting materials is presented and its performance is demonstrated for olivine-type oxides and thiophosphates. The approach is based on a topological analysis of the electrostatic (Coulomb) potential obtained from a single density functional theory calculation augmented by a Born-Mayer-type repulsive term between Li ions and the anions of the material. This 3D-corrugation descriptor enables the automatic determination of diffusion pathways in one, two, and three dimensions and reproduces migration barriers obtained from density functional theory calculations using nudged elastic band method within approximately 0.1 eV. Importantly, it correlates with Li ion conductivity. This approach thus offers an efficient tool for evaluating, ranking, and optimizing materials with high Li-ion conductivity.

Discovery of zirconium dioxides for the design of better oxygen-ion conductors using efficient algorithms beyond data mining.

It is important to find crystal structures with low formation (E v) and migration-barrier (E m) energies for oxygen vacancies for the development of fast oxygen-ion conductors. To identify crystal structures with lower E v and E m than those of ground-state ZrO2, we first reoptimize the crystal structures of various oxides reported in the database, and then directly construct them using an evolutionary algorithm. For efficient searching, we employ the linearized ridge regression model for E v using descriptors obtained from density functional theory calculations of the unit cells and apply the predicted E v as a fitness value in the evolutionary algorithm. We also find a correlation between the E v and E m for the crystal structures of ZrO2. On the basis of this correlation, we confirm that the newly constructed crystal structures, as well as certain reoptimized structures from the database, that possess low E v also have E m lower than that of ground-state ZrO2. Our successful strategy consisting of a combination of the evolutionary algorithm, first-principles calculations, and machine-learning techniques may be applicable to other oxide systems in finding crystal structures with low E v and E m.

Enhanced Cortical Thickness Measurements for Rodent Brains via Lagrangian-based RK4 Streamline Computation.

The cortical thickness of the mammalian brain is an important morphological characteristic that can be used to investigate and observe the brain's developmental changes that might be caused by biologically toxic substances such as ethanol or cocaine. Although various cortical thickness analysis methods have been proposed that are applicable for human brain and have developed into well-validated open-source software packages, cortical thickness analysis methods for rodent brains have not yet become as robust and accurate as those designed for human brains. Based on a previously proposed cortical thickness measurement pipeline for rodent brain analysis,1 we present an enhanced cortical thickness pipeline in terms of accuracy and anatomical consistency. First, we propose a Lagrangian-based computational approach in the thickness measurement step in order to minimize local truncation error using the fourth-order Runge-Kutta method. Second, by constructing a line object for each streamline of the thickness measurement, we can visualize the way the thickness is measured and achieve sub-voxel accuracy by performing geometric post-processing. Last, with emphasis on the importance of an anatomically consistent partial differential equation (PDE) boundary map, we propose an automatic PDE boundary map generation algorithm that is specific to rodent brain anatomy, which does not require manual labeling. The results show that the proposed cortical thickness pipeline can produce statistically significant regions that are not observed in the the previous cortical thickness analysis pipeline.

Multi-Object Model-based Multi-Atlas Segmentation for Rodent Brains using Dense Discrete Correspondences.

The delineation of rodent brain structures is challenging due to low-contrast multiple cortical and subcortical organs that are closely interfacing to each other. Atlas-based segmentation has been widely employed due to its ability to delineate multiple organs at the same time via image registration. The use of multiple atlases and subsequent label fusion techniques has further improved the robustness and accuracy of atlas-based segmentation. However, the accuracy of atlas-based segmentation is still prone to registration errors; for example, the segmentation of in vivo MR images can be less accurate and robust against image artifacts than the segmentation of post mortem images. In order to improve the accuracy and robustness of atlas-based segmentation, we propose a multi-object, model-based, multi-atlas segmentation method. We first establish spatial correspondences across atlases using a set of dense pseudo-landmark particles. We build a multi-object point distribution model using those particles in order to capture inter- and intra-subject variation among brain structures. The segmentation is obtained by fitting the model into a subject image, followed by label fusion process. Our result shows that the proposed method resulted in greater accuracy than comparable segmentation methods, including a widely used ANTs registration tool.

Free-electron creation at the 60° twin boundary in Bi2Te3.

Interfaces, such as grain boundaries in a solid material, are excellent regions to explore novel properties that emerge as the result of local symmetry-breaking. For instance, at the interface of a layered-chalcogenide material, the potential reconfiguration of the atoms at the boundaries can lead to a significant modification of the electronic properties because of their complex atomic bonding structure. Here, we report the experimental observation of an electron source at 60° twin boundaries in Bi2Te3, a representative layered-chalcogenide material. First-principles calculations reveal that the modification of the interatomic distance at the 60° twin boundary to accommodate structural misfits can alter the electronic structure of Bi2Te3. The change in the electronic structure generates occupied states within the original bandgap in a favourable condition to create carriers and enlarges the density-of-states near the conduction band minimum. The present work provides insight into the various transport behaviours of thermoelectrics and topological insulators.

Growth, Quantitative Growth Analysis, and Applications of Graphene on γ-Al2O3 catalysts.

The possibilities offered by catalytic γ-Al2O3 substrates are explored, and the mechanism governing graphene formation thereon is elucidated using both numerical simulations and experiments. The growth scheme offers metal-free synthesis at low temperature, grain-size customization, large-area uniformity of electrical properties, single-step preparation of graphene/dielectric structures, and readily detachable graphene. We quantify based on thermodynamic principles the activation energies associated with graphene nucleation/growth on γ-Al2O3, verifying the low physical and chemical barriers. Importantly, we derive a universal equation governing the adsorption-based synthesis of graphene over a wide range of temperatures in both catalytic and spontaneous growth regimes. Experimental results support the equation, highlighting the catalytic function of γ-Al2O3 at low temperatures. The synthesized graphene is manually incorporated as a 'graphene sticker' into an ultrafast mode-locked laser.

Multi-atlas segmentation with particle-based group-wise image registration.

We propose a novel multi-atlas segmentation method that employs a group-wise image registration method for the brain segmentation on rodent magnetic resonance (MR) images. The core element of the proposed segmentation is the use of a particle-guided image registration method that extends the concept of particle correspondence into the volumetric image domain. The registration method performs a group-wise image registration that simultaneously registers a set of images toward the space defined by the average of particles. The particle-guided image registration method is robust with low signal-to-noise ratio images as well as differing sizes and shapes observed in the developing rodent brain. Also, the use of an implicit common reference frame can prevent potential bias induced by the use of a single template in the segmentation process. We show that the use of a particle guided-image registration method can be naturally extended to a novel multi-atlas segmentation method and improves the registration method to explicitly use the provided template labels as an additional constraint. In the experiment, we show that our segmentation algorithm provides more accuracy with multi-atlas label fusion and stability against pair-wise image registration. The comparison with previous group-wise registration method is provided as well.

Particle-guided image registration.

We present a novel image registration method based on B-spline free-form deformation that simultaneously optimizes particle correspondence and image similarity metrics. Different from previous B-spline based registration methods optimized w.r.t. the control points, the deformation in our method is estimated from a set of dense unstructured pair of points, which we refer as corresponding particles. As intensity values are matched on the corresponding location, the registration performance is iteratively improved. Moreover, the use of corresponding particles naturally extends our method to a group-wise registration by computing a mean of particles. Motivated by a surface-based group-wise particle correspondence method, we developed a novel system that takes such particles to the image domain, while keeping the spirit of the method similar. The core algorithm both minimizes an entropy based group-wise correspondence metric as well as maximizes the space sampling of the particles. We demonstrate the results of our method in an application of rodent brain structure segmentation and show that our method provides better accuracy in two structures compared to other registration methods.

Comparison of magnetic resonance imaging in live vs. post mortem rat brains.

Magnetic Resonance Imaging (MRI) is an increasingly popular technique for examining neurobiology in rodents because it is both noninvasive and nondestructive. MRI scans can be acquired from either live or post mortem specimens. In vivo scans have a key advantage in that subjects can be scanned at multiple time-points in longitudinal studies. However, repeated exposure to anesthesia and stress may confound studies. In contrast, post mortem scans offer improved image quality and increased signal-to-noise ratio (SNR) due to several key advantages: First, the images are not disrupted by motion and pulsation artifacts. Second, they allow the brain tissue to be perfused with contrast agents, enhancing tissue contrast. Third, they allow longer image acquisition times, yielding higher resolution and/or improved SNR. Fourth, they allow assessment of groups of animals at the same age without scheduling complications. Despite these advantages, researchers are often skeptical of post mortem MRI scans because of uncertainty about whether the fixation process alters the MRI measurements. To address these concerns, we present a thorough comparative study of in vivo and post mortem MRI scans in healthy male Wistar rats at three age points throughout adolescence (postnatal days 28 through 80). For each subject, an in vivo scan was acquired, followed by perfusion and two post mortem scans at two different MRI facilities. The goal was to assess robustness of measurements, to detect any changes in volumetric measurements after fixation, and to investigate any differential bias that may exist between image acquisition techniques. We present this volumetric analysis for comparison of 22 anatomical structures between in vivo and post mortem scans. No significant changes in volumetric measurements were detected; however, as hypothesized, the image quality is dramatically improved in post mortem scans. These findings illustrate the validity and utility of using post mortem scans in volumetric neurobiological studies.

Postnatal day 7 ethanol treatment causes persistent reductions in adult mouse brain volume and cortical neurons with sex specific effects on neurogenesis.

Ethanol treatment on postnatal day seven (P7) causes robust brain cell death and is a model of late gestational alcohol exposure (Ikonomidou et al., 2000). To investigate the long-term effects of P7 ethanol treatment on adult brain, mice received either two doses of saline or ethanol on P7 (2.5 g/kg, s.c., 2 h apart) and were assessed as adults (P82) for brain volume (using postmortem MRI) and cellular architecture (using immunohistochemistry). Adult mice that received P7 ethanol had reduced MRI total brain volume (4%) with multiple brain regions being reduced in both males and females. Immunohistochemistry indicated reduced frontal cortical parvalbumin immunoreactive (PV + IR) interneurons (18-33%) and reduced Cux1+IR layer II pyramidal neurons (15%) in both sexes. Interestingly, markers of adult hippocampal neurogenesis differed between sexes, with only ethanol treated males showing increased doublecortin and Ki67 expression (52 and 57% respectively) in the dentate gyrus, consistent with increased neurogenesis compared to controls. These findings suggest that P7 ethanol treatment causes persistent reductions in adult brain volume and frontal cortical neurons in both males and females. Increased adult neurogenesis in males, but not females, is consistent with differential adaptive responses to P7 ethanol toxicity between the sexes. One day of ethanol exposure, e.g. P7, causes persistent adult brain dysmorphology.

Synergy of image analysis for animal and human neuroimaging supports translational research on drug abuse.

The use of structural magnetic resonance imaging (sMRI) and diffusion tensor imaging (DTI) in animal models of neuropathology is of increasing interest to the neuroscience community. In this work, we present our approach to create optimal translational studies that include both animal and human neuroimaging data within the frameworks of a study of post-natal neuro-development in intra-uterine cocaine-exposure. We propose the use of non-invasive neuroimaging to study developmental brain structural and white matter pathway abnormalities via sMRI and DTI, as advanced MR imaging technology is readily available and automated image analysis methodology have recently been transferred from the human to animal imaging setting. For this purpose, we developed a synergistic, parallel approach to imaging and image analysis for the human and the rodent branch of our study. We propose an equivalent design in both the selection of the developmental assessment stage and the neuroimaging setup. This approach brings significant advantages to study neurobiological features of early brain development that are common to animals and humans but also preserve analysis capabilities only possible in animal research. This paper presents the main framework and individual methods for the proposed cross-species study design, as well as preliminary DTI cross-species comparative results in the intra-uterine cocaine-exposure study.

Automatic Skull-stripping of Rat MRI/DTI Scans and Atlas Building.

3D Magnetic Resonance (MR) and Diffusion Tensor Imaging (DTI) have become important noninvasive tools for the study of animal models of brain development and neuropathologies. Fully automated analysis methods adapted to rodent scale for these images will allow high-throughput studies. A fundamental first step for most quantitative analysis algorithms is skull-stripping, which refers to the segmentation of the image into two tissue categories, brain and non-brain. In this manuscript, we present a fully automatic skull-stripping algorithm in an atlas-based manner. We also demonstrate how to either modify an external atlas or to build an atlas from the population itself to present a self-contained approach. We applied our method to three datasets of rat brain scans, at different ages (PND5, PND14 and adult), different study groups (control, ethanol exposed), as well as different image acquisition parameters. We validated our method by comparing the automated skull-strip results to manual delineations performed by our expert, which showed a discrepancy of less than a single voxel on average. We thus demonstrate that our algorithm can robustly and accurately perform the skull-stripping within one voxel of the manual delineation, and in a fraction of the time it takes a human expert.

Automatic cortical thickness analysis on rodent brain.

Localized difference in the cortex is one of the most useful morphometric traits in human and animal brain studies. There are many tools and methods already developed to automatically measure and analyze cortical thickness for the human brain. However, these tools cannot be directly applied to rodent brains due to the different scales; even adult rodent brains are 50 to 100 times smaller than humans. This paper describes an algorithm for automatically measuring the cortical thickness of mouse and rat brains. The algorithm consists of three steps: segmentation, thickness measurement, and statistical analysis among experimental groups. The segmentation step provides the neocortex separation from other brain structures and thus is a preprocessing step for the thickness measurement. In the thickness measurement step, the thickness is computed by solving a Laplacian PDE and a transport equation. The Laplacian PDE first creates streamlines as an analogy of cortical columns; the transport equation computes the length of the streamlines. The result is stored as a thickness map over the neocortex surface. For the statistical analysis, it is important to sample thickness at corresponding points. This is achieved by the particle correspondence algorithm which minimizes entropy between dynamically moving sample points called particles. Since the computational cost of the correspondence algorithm may limit the number of corresponding points, we use thin-plate spline based interpolation to increase the number of corresponding sample points. As a driving application, we measured the thickness difference to assess the effects of adolescent intermittent ethanol exposure that persist into adulthood and performed t-test between the control and exposed rat groups. We found significantly differing regions in both hemispheres.

Evaluation of Atlas based Mouse Brain Segmentation.

Magentic Reasonance Imaging for mouse phenotype study is one of the important tools to understand human diseases. In this paper, we present a fully automatic pipeline for the process of morphometric mouse brain analysis. The method is based on atlas-based tissue and regional segmentation, which was originally developed for the human brain. To evaluate our method, we conduct a qualitative and quantitative validation study as well as compare of b-spline and fluid registration methods as components in the pipeline. The validation study includes visual inspection, shape and volumetric measurements and stability of the registration methods against various parameter settings in the processing pipeline. The result shows both fluid and b-spline registration methods work well in murine settings, but the fluid registration is more stable. Additionally, we evaluated our segmentation methods by comparing volume differences between Fmr1 FXS in FVB background vs C57BL/6J mouse strains.