Microscopic Theory of Rashba Interaction in Magnetic Metal

Theory of Rashba spin-orbit coupling in magnetic metals is worked out from microscopic Hamiltonian describing d-orbitals. When structural inversion symmetry is broken, electron hopping between $d$-orbitals generates chiral ordering of orbital angular momentum, which combines with atomic spin-orbit coupling to result in the Rashba interaction. Rashba parameter characterizing the interaction is band-specific, even reversing its sign from band to band. Large enhancement of the Rashba parameter found in recent experiments is attributed to the orbital mixing of 3d magnetic atoms with non-magnetic heavy elements as we demonstrate by first-principles and tight-binding calculations.Comment: 5 pages, 2 figure

Dynamic Failure Properties of the Porcine Medial Collateral Ligament-Bone Complex for Predicting Injury in Automotive Collisions

The goal of this study was to model the dynamic failure properties of ligaments and their attachment sites to facilitate the development of more realistic dynamic finite element models of the human lower extremities for use in automotive collision simulations. Porcine medial collateral ligaments were chosen as a test model due to their similarities in size and geometry with human ligaments. Each porcine medial collateral ligament-bone complex (n = 12) was held in a custom test fixture placed in a drop tower to apply an axial impulsive impact load, applying strain rates ranging from 0.005 s-1 to 145 s-1. The data from the impact tests were analyzed using nonlinear regression to construct model equations for predicting the failure load of ligament-bone complexes subjected to specific strain rates as calculated from finite element knee, thigh, and hip impact simulations. The majority of the ligaments tested failed by tibial avulsion (75%) while the remaining ligaments failed via mid-substance tearing. The failure load ranged from 384 N to 1184 N and was found to increase with the applied strain rate and the product of ligament length and cross-sectional area. The findings of this study indicate the force required to rupture the porcine MCL increases with the applied bone-to-bone strain rate in the range expected from high speed frontal automotive collisions

Core-Shell Interface-Oriented Synthesis of Bowl-Structured Hollow Silica Nanospheres Using Self-Assembled ABC Triblock Copolymeric Micelles

© 2018 American Chemical Society. Hollow porous silica nanospheres (HSNs) are emerging classes of cutting-edge nanostructured materials. They have elicited much interest as carriers of active molecule delivery due to their amorphous chemical structure, nontoxic nature, and biocompatibility. Structural development with hierarchical morphology is mostly required to obtain the desired performance. In this context, large through-holes or pore openings on shells are desired so that the postsynthesis loading of active-molecule onto HSNs via a simple immersion method can be facilitated. This study reports the synthesis of HSNs with large through-holes or pore openings on shells, which are subsequently termed bowl-structured hollow porous silica nanospheres (BHSNs). The synthesis of BHSNs was mediated by the core-shell interfaces of the core-shell corona-structured micelles obtained from a commercially available ABC triblock copolymer (polystyrene-b-poly(2-vinylpyridine)-b-poly(ethylene oxide) (PS-P2VP-PEO)). In this synthesis process, polymer@SiO2 composite structure was formed because of the deposition of silica (SiO2) on the micelles' core. The P2VP block played a significant role in the hydrolysis and condensation of the silica precursor, i.e., tetraethylorthosilicate (TEOS) and then maintaining the shell's growth. The PS core of the micelles built the void spaces. Transmission electron microscopy (TEM) images revealed a spherical hollow structure with an average particle size of 41.87 ± 3.28 nm. The average diameter of void spaces was 21.71 ± 1.22 nm, and the shell thickness was 10.17 ± 1.68 nm. According to the TEM image analysis, the average large pore was determined to be 15.95 nm. Scanning electron microscopy (SEM) images further confirmed the presence of large single pores or openings in shells. These were formed as a result of the accumulated ethanol on the PS core acting to prevent the growth of silica

Dynamic Changes in LSM Nanoparticles on YSZ: A Model System for Non-Stationary SOFC Cathode Behavior

The interaction between nanoparticles of strontium-doped lanthanum manganite (LSM) and single-crystal yttria-stabilized zirconia (YSZ) was investigated using atomic force microscopy, X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM)/energy-dispersive X-ray spectroscopy (EDX). Nanoparticles of LSM were deposited directly onto single-crystal YSZ (100) substrates using an ultrasonic spray nozzle. As samples were annealed from 850 to 1250 degrees C, nanoparticles gradually decreased in height and eventually disappeared completely. Subsequent reduction in H-2/H2O at 700 degrees C resulted in the reappearance of nanoparticles. Studies were carried out on identical regions of the sample, allowing the same nanoparticles to be characterized at different temperatures. Morphological changes indicate the formation of a thin layer of LSM, and XPS results support the observation by indicating an increase in signal from the La and Sr and a decrease in signal from the Y and Zr with increasing temperature. SEM/EDX was used to verify that the nanoparticles in the reduced sample contained La. The changes in the LSM/YSZ morphology may be important in explaining the nonstationary behavior observed in operating solid-oxide fuel cells (SOFCs). The thin layer of LSM initially results in poor cathode performance; reducing conditions then lead to film disruptions, indicating nano/microporosity, that increase oxygen ion diffusion and performance

Gauge coupling renormalization in orbifold field theories

We investigate the gauge coupling renormalization in orbifold field theories preserving 4-dimensional N=1 supersymmetry in the framework of 4-dimensional effective supergravity. As a concrete example, we consider the 5-dimensional Super-Yang-Mills theory on a slice of AdS_5. In our approach, one-loop gauge couplings can be determined by the loop-induced axion couplings and the tree level properties of 4-dimensional effective supergravity which are much easier to be computed.Comment: 18 pages, JHEP style; 1-loop corrections to gauge kinetic functions are fully computed, references are adde

Efficiency of Energy Transduction in a Molecular Chemical Engine

A simple model of the two-state ratchet type is proposed for molecular chemical engines that convert chemical free energy into mechanical work and vice versa. The engine works by catalyzing a chemical reaction and turning a rotor. Analytical expressions are obtained for the dependences of rotation and reaction rates on the concentrations of reactant and product molecules, from which the performance of the engine is analyzed. In particular, the efficiency of energy transduction is discussed in some detail.Comment: 4 pages, 4 fugures; title modified, figures 2 and 3 modified, content changed (pages 1 and 4, mainly), references adde

Gauge Threshold Corrections in Warped Geometry

We discuss the Kaluza-Klein threshold correction to low energy gauge couplings in theories with warped extra-dimension, which might be crucial for the gauge coupling unification when the warping is sizable. Explicit expressions of one-loop thresholds are derived for generic 5D gauge theory on a slice of AdS_5, where some of the bulk gauge symmetries are broken by orbifold boundary conditions and/or by bulk Higgs vacuum values. Effects of the mass mixing between the bulk fields with different orbifold parities are included as such mixing is required in some class of realistic warped unification models.Comment: 33 pages, 1 figure, 6 tables, invited contribution to New Journal of Physics Focus Issue on 'Extra Space Dimensions

Predicting ocean-induced ice-shelf melt rates using deep learning

Through their role in buttressing upstream ice flow, Antarctic ice shelves play an important part in regulating future sea-level change. Reduction in ice-shelf buttressing caused by increased ocean-induced melt along their undersides is now understood to be one of the key drivers of ice loss from the Antarctic ice sheet. However, despite the importance of this forcing mechanism, most ice-sheet simulations currently rely on simple melt parameterisations of this ocean-driven process since a fully coupled ice–ocean modelling framework is prohibitively computationally expensive. Here, we provide an alternative approach that is able to capture the greatly improved physical description of this process provided by large-scale ocean-circulation models over currently employed melt parameterisations but with trivial computational expense. This new method brings together deep learning and physical modelling to develop a deep neural network framework, MELTNET, that can emulate ocean model predictions of sub-ice-shelf melt rates. We train MELTNET on synthetic geometries, using the NEMO ocean model as a ground truth in lieu of observations to provide melt rates both for training and for evaluation of the performance of the trained network. We show that MELTNET can accurately predict melt rates for a wide range of complex synthetic geometries, with a normalised root mean squared error of 0.11 m yr−1 compared to the ocean model. MELTNET calculates melt rates several orders of magnitude faster than the ocean model and outperforms more traditional parameterisations for &gt; 96 % of geometries tested. Furthermore, we find MELTNET's melt rate estimates show sensitivity to established physical relationships such as changes in thermal forcing and ice-shelf slope. This study demonstrates the potential for a deep learning framework to calculate melt rates with almost no computational expense, which could in the future be used in conjunction with an ice sheet model to provide predictions for large-scale ice sheet models.</p