Samples of 1/6Ba5Nb4O15·5/6BaNb2O6 along with the pure end members, Ba5Nb4O15 and BaNb2O6, were sintered under low oxygen partial pressure. The degradation mechanisms of dielectric loss in this reducing atmosphere have been studied. We found that the degradation occurred primarily due to the formation of oxygen vacancies caused by the reduction of Nb5+. This was determined by measuring the electrical conductivity, and through X-ray photoelectron spectroscopy. More importantly, the dielectric loss of 1/6Ba5Nb4O15·5/6BaNb2O6 samples with higher temperature stability was further decreased on sintering in a reducing atmosphere. This observation has been explained by considering the increased porosity and formation of a reduced second phase, Ba0.65NbO3. 相似文献
The univariant element, Q1P0, and the multivariant elements, QP0 and R P0, are compared for the numerical simulation of the flow in extrusion dies. The pressure distribution obtained by using the Q1P0 element was found to be afflicted with the checkerboard pressure mode. On the other hand, the multivariant elements, QP0 and RP0, gave accurate and physically reasonable velocity and pressure distributions. The computed values of the pressure drop across extrusion dies matched well with the pressure drop determined experimentally. 相似文献
Nitrogen molecules have been encapsulated into the central hollows of vertically aligned carbon nitride (CN) multiwalled nanofibers by dc plasma-enhanced chemical vapor deposition with C2H2, NH3, and N2 gases on a Ni/TiN/Si(1 0 0) substrate at 650 °C. X-ray photoelectron spectroscopy and near-edge X-ray absorption fine structure spectra showed the existence of nitrogen molecules in CN nanofibers. Elemental mapping images with electron energy loss spectroscopy of the CN nanofiber and catalyst metal, and optical emission spectroscopy spectra of the plasma showed the distribution of nitrogen atoms and molecules in the CN nanofiber, catalyst metal, and gaseous precursor, respectively. These studies showed that atomic nitrogen diffused into the catalytic metal particle because of the concentration gradient and then saturated at the bottom of the particle. Saturated nitrogen atom participated in the formation of the CN nanofiber wall but most of nitrogen was trapped in the central hollow of the nanofiber as molecules. 相似文献
Person re-identification (re-id) aims to identity the same person over multiple cameras; it has been successfully applied to various computer vision applications as a fundamental method. Owing to the development of deep learning, person re-id methods, which typically use triplet networks based on triplet loss, have demonstrated great success. However, the appearances of people are similar and hence difficult to distinguish in many cases. Therefore, we present a novel graph convolution network and enhances traditional triplet loss functions. Our method defines reference, positive, and negative features for triplet loss as three vertices of a graph, respectively, and adjusts their mutual distance through learning. The method adopts graph convolutions efficiently, thereby affording low computational costs. Experimental results demonstrate that our method is superior to the baseline on the Market-1501 dataset. The proposed GCN-based triplet loss considerably contributes to improve re-identification methods quantitatively and qualitatively.
Li metal anode is the “Holy Grail” material of advanced Lithium-ion-batteries (LIBs). However, it is plagued by uncontrollable dendrite growth resulting in poor cycling efficiency and short-circuiting of batteries. This has spurred a plethora of research to understand the underlying mechanism of dendrite formation. While experimental studies suggest that there are complex physical and chemical interactions between heterogeneous solid-electrolyte interphase (SEI) and dendrite growth, most of the studies do not reveal the mechanisms triggering these interactions. To deal with this knowledge gap, we propose a multiscale modeling framework which couples kinetic Monte Carlo and Molecular Dynamics simulations. Specifically, the model has been developed to account for (a) heterogeneous SEI, (b) dendrite-SEI interactions, and (c) effect of electrolyte on Li electrodeposition and potential dendrite formation. This allows the proposed computational model to be extended to various electrolytes and SEI species and generate results consistent with previous experimental studies. 相似文献
Two types of multi-walled carbon nanotube (MWNT)-based elastomer nanocomposites are used as a sensor material for the detection of gasoline spills by applying the interdigitated electrode (IDE) device. MWNT-g-polyisoprene (PI) and Si-MWNT/natural rubber (NR) are prepared by applying “grafting-from” and “grafting-to” process, respectively. When compared based on the identical condition of gasoline sensing test, the maximum response value to the exposure of gasoline is 17.5 for MWNT-g-PI sensor and 12.9 for Si-MWNT/NR sensor, which reach the maximum in less than 3 min. The MWNT-g-PI sensor selectively detects gasoline, and its response is completely reversible. It shows that the longer chain length of PI brings about the larger response of MWNT-g-PI sensor to gasoline. The sensitivity of MWNT-g-PI sensor highly depends on both how much gasoline is exposed to the sensor and what bias voltage is applied to the IDE device. The IDE sensor using MWNT-g-PI nanocomposites effectively detects gasoline spills. 相似文献