CO<Subscript>2</Subscript> decomposition using metal ferrites prepared by co-precipitation method

To catalytically decompose the greenhouse gas, CO₂, spinel structure M-ferrites (M=Co, Ni, Cu, Zn) were synthesized by chemical co-precipitation using metal salts and sodium hydroxide as starting materials. The crystallite size of the newly-prepared M-ferrites increased and the BET surface area decreased with increasing calcination temperature. A thermal analysis of the reduction and reoxidation of M-ferrites indicated that substitution of divalent transition metals (i.e., Cu, Ni and Co) into Fe₃O₄ improved the reduction kinetics in the order of Cu>Ni>Co. ZnFe₂O₄ was the most difficult compound to completely reduce due to its stable structure. Commercial samples of the reduced Fe₃O₄, CoFe₂O₄ and ZnFe₂O₄ showed an increase in mass through the reoxidation process, but it was much more difficult for oxygen atoms to enter the structure of the reduced samples of NiFe₂O₄ and CuFe₂O₄. The M-ferrites in a batch type reactor showed better efficiency than the commercial Fe₃O₄. Also found was that CoFe₂O₄ showed a high regeneration potential, although it required a higher critical reaction temperature. NiFe₂O₄ and CuFe₂O₄ were excellent candidate materials for CO₂ decomposition at lower temperatures.     

Optical and Electrical Properties of TixSi1‐xOy Films

Ti_xSi_1xO_y (TSO) thin films are fabricated using plasma‐enhanced atomic layer deposition. The Ti content in the TSO films is controlled by adjusting the sub‐cycle ratio of TiO₂ and SiO₂. The refractive indices of SiO₂ and TiO₂ are 1.4 and 2.4, respectively. Hence, tailoring of the refractivity indices from 1.4 to 2.4 is feasible. The controllability of the refractive index and film thickness enables application of an antireflection coating layer to TSO films for use as a thin film solar cell. The TSO coating layer on an Si wafer dramatically reduces reflectivity compared to a bare Si wafer. In the measurement of the current‐voltage characteristics, a nonlinear coefficient of 13.6 is obtained in the TSO films.     

An experimental investigation of heat transfer in forced convective boiling of R134a,R123 and R134a/R123 in a horizontal tube

This paper reports an experimental study on flow boiling of pure refrigerants R134a and R123 and their mixtures in a uniformly heated horizontal tube. The flow pattern was observed through tubular sight glasses with an internal diameter of 10 mm located at the inlet and outlet of the test section. Tests were run at a pressure of 0.6 MPa in the heat flux ranges of 5–50 kW/m², vapor quality 0–100 percent and mass velocity of 150–600 kg/m²s. Both in the nucleate boiling-dominant region at low quality and in the two-phase convective evaporation region at higher quality where nucleation is supposed to be fully suppressed, the heat transfer coefficient for the mixture was lower than that for an equivalent pure component with the same physical properties as the mixture. The reduction of the heat transfer coefficient in mixture is explained by such mechanisms as mass transfer resistance and non-linear variation in physical properties etc. In this study, the contribution of convective evaporation, which is obtained for pure refrigerants under the suppression of nucleate boiling, is multiplied by the composition factor by Singal et al. (1984). On the basis of Chen’s superposition model, a new correlation is presented for heat transfer coefficients of mixture.     

Sub-30 nm gate template fabrication for nanoimprint lithography using spacer patterning technology

In this study, we present a spacer patterning technology for sub-30 nm gate template which is used for nano-scale MOSFETs fabrication. A spacer patterning technology using a poly-silicon micro-feature and a chemical vapor deposition (CVD) SiO2 spacer has been developed, and the sub-30 nm structures by conventional dry etching and chemical mechanical polishing are demonstrated. The minimum-sized features are defined not by the photolithography but by the CVD film thickness. Therefore, this technology yields a large-area template with critical dimension of minimum-sized features much smaller than that achieved by optical lithography.     

Process development for the removal of copper from wastewater using ferric/limestone treatment

The removal of copper from wastewater by ferric/limestone coagulation followed by screen filtration was carried out at a laboratory scale. The optimum coagulant (FeCl₃) dose and working pH were 50 mg// of Fe(m) and pH 7.5, respectively, through jar tests. For the efficient removal of copper from wastewater, we developed a novel process including the co-precipitation of copper with FeCl₃, alkalization in a limestone aeration bed, and separation of precipitates in a sedimentation tank coupled with internal stainless steel screen filter. The performance results showed that removal of copper from the solution was over 99.5%. The pH was effectively maintained over 7.5 in limestone bed during the whole process. Ferric hydroxide/copper aggregates were removed over 99% by stainless steel screen filter of 1,450 mesh. Periodic air backwashing alleviated fouling of the filter surface.     

Robust person re-identification via graph convolution networks

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.

     

Software Agent with Reinforcement Learning Approach for Medical Image Segmentation

Many image segmentation solutions are problem-based. Medical images have very similar grey level and texture among the interested objects. Therefore, medical image segmentation requires improvements although there have been researches done since the last few decades. We design a self-learning framework to extract several objects of interest simultaneously from Computed Tomography (CT) images. Our segmentation method has a learning phase that is based on reinforcement learning (RL) system. Each RL agent works on a particular sub-image of an input image to find a suitable value for each object in it. The RL system is define by state, action and reward. We defined some actions for each state in the sub-image. A reward function computes reward for each action of the RL agent. Finally, the valuable information, from discovering all states of the interest objects, will be stored in a Q-matrix and the final result can be applied in segmentation of similar images. The experimental results for cranial CT images demonstrated segmentation accuracy above 95%.     

Efficiency enhancement in large-area organic photovoltaic module using theoretical power loss model

For efficiency enhancement of a large-area monolithic organic photovoltaic (OPV) module, we studied the influence of the OPV cell geometry parameters using theoretical and experimental methods. For this work, a unit OPV cell as a reference device and four types of monolithic OPV module with different active cell lengths were fabricated together on a glass substrate. The characteristics of the fabricated unit OPV cell were measured and the voltage (V_mp) and current density (J_mp) at the maximum power point were extracted. The parasitic power losses were calculated from the extracted parameters and the material parameters using a theoretical power loss model, taking into consideration the series resistance, contact resistance, and shading (or dead area) losses at the calculated maximum power of the monolithic OPV module. To analyze the influence of OPV cell layout on efficiency of the large-area monolithic OPV module, the power conversion efficiency of the four type monolithic OPV modules with different active cell lengths was measured and compared with the calculated power conversion efficiency. The calculated PCE ratio of the monolithic OPV module with three cells was approximately 78%, and the measured PCE ratio of the fabricated monolithic OPV module with three cells was also approximately 78%. The measured PCE ratio of fabricated monolithic OPV modules with two, four, and five cells also exhibited this tendency for the calculated PCE ratio. Thus, a large-area monolithic OPV module with optimum electrical power loss and an appropriate number of OPV cells can be designed by extracting the parameters of the unit OPV cell and calculating the electrical power loss using the proposed theoretical power loss model.     

Numerical investigation on the water saturation of proton exchange membrane fuel cells with channel geometry variation

Many factors, such as mole fractions of oxygen and hydrogen, help improve the performance of proton exchange membrane fuel cells. The variation of mole fractions can be achieved by changing the operating pressure and relative humidity of the fuel cells. The changes in operating conditions are directly related to the electrochemical reaction and water generation of the fuel cells. The geometrical shape of the fuel cells also should be considered a factor in predicting performance because this affects the species' reaction speed and distribution. The current study considers four geometrical cell shapes with varied lengths and electrode and gas channel numbers. The variation in inlet pressure is considered in analyzing the current density distribution of the fuel cells and, subsequently, of liquid water generation. A serpentine gas flow channel is assumed, and its two‐dimensional arrangement is considered in the different gas channel numbers and its length. Four inlet pressure variations and four geometrical shape variations also are considered in analyzing the fuel cells' current density and water generation distributions. The results obtained from this research can be utilized in identifying the fuel cells' optimal operating pressure and designing their gas channel number and arrangement. Copyright © 2011 John Wiley & Sons, Ltd.     

Effect of weld geometry on fatigue performance of 6061-T6 aluminum GMAW: part 3. T-fillet joint

Journal of Mechanical Science and Technology - The effects of various weld geometries on the fatigue performance of T-fillet joint aluminum arc welding were investigated by conducting gas metal arc...