Three-dimensional simulation of a new cooling strategy for proton exchange membrane fuel cell stack using a non-isothermal multiphase model

In this study, a new cooling strategy for a proton exchange membrane (PEM) fuel cell stack is investigated using a three-dimensional (3D) multiphase non-isothermal model. The new cooling strategy follows that of the Honda's Clarity design and further extends to a cooling unit every five cells in stacks. The stack consists of 5 fuel cells sharing the inlet and outlet manifolds for reactant gas flows. Each cell has 7-path serpentine flow fields with a counter-flow configuration arranged for hydrogen and air streams. The coolant flow fields are set at the two sides of the stack and are simplified as the convective heat transfer thermal boundary conditions. This study also compares two thermal boundary conditions, namely limited and infinite coolant flow rates, and their impacts on the distributions of oxygen, liquid water, current density and membrane hydration. The difference of local temperature between these two cooling conditions is as much as 6.9 K in the 5-cell stack, while it is only 1.7 K in a single cell. In addition, the increased vapor concentration at high temperature (and hence water saturation pressure) dilutes the oxygen content in the air flow, reducing local oxygen concentration. The higher temperature in the stack also causes low membrane hydration, and consequently poor cell performance and non-uniform current density distribution, as disclosed by the simulation. The work indicates the new cooling strategy can be optimized by increasing the heat transfer coefficient between the stack and coolant to mitigate local overheating and cell performance reduction

Deep Multi-instance Networks with Sparse Label Assignment for Whole Mammogram Classification

Mammogram classification is directly related to computer-aided diagnosis of breast cancer. Traditional methods rely on regions of interest (ROIs) which require great efforts to annotate. Inspired by the success of using deep convolutional features for natural image analysis and multi-instance learning (MIL) for labeling a set of instances/patches, we propose end-to-end trained deep multi-instance networks for mass classification based on whole mammogram without the aforementioned ROIs. We explore three different schemes to construct deep multi-instance networks for whole mammogram classification. Experimental results on the INbreast dataset demonstrate the robustness of proposed networks compared to previous work using segmentation and detection annotations.Comment: MICCAI 2017 Camera Read

En-route to the fission-fusion reaction mechanism: a status update on laser-driven heavy ion acceleration

The fission-fusion reaction mechanism was proposed in order to generate extremely neutron-rich nuclei close to the waiting point N = 126 of the rapid neutron capture nucleosynthesis process (r-process). The production of such isotopes and the measurement of their nuclear properties would fundamentally help to increase the understanding of the nucleosynthesis of the heaviest elements in the universe. Major prerequisite for the realization of this new reaction scheme is the development of laser-based acceleration of ultra-dense heavy ion bunches in the mass range of A = 200 and above. In this paper, we review the status of laser-driven heavy ion acceleration in the light of the fission-fusion reaction mechanism. We present results from our latest experiment on heavy ion acceleration, including a new milestone with laser-accelerated heavy ion energies exceeding 5 MeV/u

Effects of Ru Substitution on Dimensionality and Electron Correlations in Ba(Fe_{1-x}Ru_x)_2As_2

We report a systematic angle-resolved photoemission spectroscopy study on Ba(Fe$_{1-x}$Ru$_x$)$_2$As$_2$ for a wide range of Ru concentrations (0.15 $\leq$ \emph{x} $\leq$ 0.74). We observed a crossover from two-dimension to three-dimension for some of the hole-like Fermi surfaces with Ru substitution and a large reduction in the mass renormalization close to optimal doping. These results suggest that isovalent Ru substitution has remarkable effects on the low-energy electron excitations, which are important for the evolution of superconductivity and antiferromagnetism in this system.Comment: 4 pages, 4 figure

Magnetic structure of superconducting Eu(Fe0.82Co0.18)2As2 as revealed by single-crystal neutron diffraction

The magnetic structure of superconducting Eu(Fe0.82Co0.18)2As2 is unambiguously determined by single-crystal neutron diffraction. A long-range ferromagnetic order of the Eu2+ moments along the c-direction is revealed below the magnetic phase transition temperature Tc = 17 K. In addition, the antiferromagnetism of the Fe2+ moments still survives and the tetragonal-to-orthorhombic structural phase transition is also observed, although the transition temperatures of the Fe-spin density wave (SDW) order and the structural phase transition are significantly suppressed to Tn = 70 K and Ts = 90 K, respectively, compared to the parent compound EuFe2As2.We present the microscopic evidences for the coexistence of the Eu-ferromagnetism (FM) and the Fe-SDW in the superconducting crystal. The superconductivity (SC) competes with the Fe-SDW in Eu(Fe0.82Co0.18)2As2.Moreover, the comparison between Eu(Fe1-xCox)2As2 and Ba(Fe1-xCox)2As2 indicates a considerable influence of the rare-earth element Eu on the magnetism of the Fe sublattice.Comment: 7 pages, 7 figures, accepted for publication in Physical Review