• Journal of the Korean Crystal Growth and Crystal Technology
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• v.29 no.5
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• pp.187-191
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• 2019

Perovskite-type oxides have consistently attracted considerable attention for their applications in high-temperature electrochemical devices, such as electrolytes and electrodes of solid oxide fuel cells, oxygen permeating membranes and sensors etc. Among them, the electrical conductivity of 10 % Sr and 10 % Mg doped $LaAlO_3$ (LSAM9191) was measured using impedance spectroscopy and 4-probe d.c. method. Below $550^{\circ}C$, the grain boundary resistance mostly determined the overall conductivity; however, it nearly disappeared above $800^{\circ}C$. Using the defect model and curve fitting, the ionic and electronic conductivity contributions were also separated. In the temperature region where the sample resistance is mostly determined by the grain volume property, LSAM9191 was an oxygen ion conductor at low $Po_2$ and a mixed conductor at high $Po_2$. With increasing temperature, the ionic conduction region only slightly increased. Thus, LSAM9191 is a promising material as an oxygen ion conductor at high temperature and in low $Po_2$.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.7
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• pp.46-52
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• 2006

The effects of surface treatment on the hydrogen storage properties of a $Mg_2Ni$ alloy particle were investigated by the microvoltammetric technique, in which a carbon-filament microelectrode was manipulated to make electrical contact with the particle in a KOH aqueous solution. It was found that the hydrogen storage properties of $Mg_2Ni$ at room temperature were improved by the surface treatment with a nickel plating solution. The sodium salts(sodium phosphate and sodium dihydrogen citrate) contained in the nickel plating solution made the alloy form an amorphous-like state, resulting in an improved hydrogen charge/discharge capacity at room temperature as high as about 150[mAh/g] from the original value of 17[mAh/g]. Potential-step experiment was carried out to determine the apparent chemical diffusion coefficient of hydrogen atom($D_{app}$) in the alloy. Since the alloy particle we used here was a dense, conductive sphere, the spherical diffusion model was employed for data analysis. $D_{app}$ was found to vary the order between $10^{-8}{\sim}10^{-9}[cm^2/s]$ over the course of hydrogenation and dehydrogenation process.

• Journal of the Korean Institute of Gas
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• v.25 no.2
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• pp.64-71
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• 2021

Research on polymer matrix composites with excellent molding processability and mechanical properties in the automotive field including hydrogen fuel cell electric vehicles is expanding to Computer-Aided Engineering (CAE) to support the design of materials with specific mechanical properties. CAE automation requires the prediction of the mechanical properties and behavior of materials. Unlike single materials, the mechanical properties prediction of polymer matrix composites is difficult to explain with formulas because the mechanical behavior is complicated to be explained only by the relationship between the matrix and the filler. In this study, the stress-strain curve according to the composition of polymer matrix composites, which was difficult to predict due to its sensitivity to large plastic deformation and composition, was predicted based on machine learning of the test data. The developed model finds a complex correlation between matrix and filler types and compositions, and predicts the total stress-strain curve meaningfully even in the absence of learned test data. It is expected that the material design AI system can be completed in the future based on the developed model that predicts the mechanical properties of polymer matrix composites even for the combination and composition that have not been learned.

• Journal of the Korean Institute of Gas
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• v.27 no.3
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• pp.123-133
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• 2023

Commercial hydrogen fuel cell vehicles are charged by compressing gaseous hydrogen to high pressure and storing it in a storage tank in the vehicle. This process causes the temperature of the gas to rise, to ensure the safety to storage tanks, the temperature is limited. Therefore, a heat transfer model is needed to explain this temperature rise. The heat transfer model includes the convective heat transfer phenomenon, and accurate estimation is required. In this study, the convective heat transfer coefficient in the hydrogen fueling process was calculated and compared using various correlation equations considering physical phenomena. The hydrogen fueling process was classified into the fueling line from the dispenser to the tank inlet and the storage tank in the vehicle, and the convective heat transfer coefficients were estimated according to process parameters such as mass flow rate, diameter, temperature and pressure. As a result, in the case of the inside of the filling line, the convective heat transfer coefficient was about 1000 times larger than that of the inside of the storage tank, and in the case of the outside of the filling line, the convective heat transfer coefficient was about 3 times larger than that of the outside of the storage tank. Finally, as a result of a comprehensive analysis of convective heat transfer coefficients in each process, it was found that outside the storage tank was lowest in the entire hydrogen fueling process, thus dominated the heat transfer phenomenon.