• Journal of the Korean Electrochemical Society
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• v.6 no.1
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• pp.59-64
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• 2003

We fabricated mixed ionic-electronic conducting membranes, $CH_4\;Using\;{0.7}Sr_{0.3}Ga_{0.6}Fe_{0.4}O_{3-\delta}$, by solid state reaction method for solid oxide fuel cell. The membranes consisted of single perovskite phase and exhibited high relative density, $>95\%$. We coated $La_{0.6}Sr_{0.4}CoO_{3-\delta}$ layer using screen printing method in order to improve surface reactivity of the $La_{0.7}Sr_{0.3}Ga_{0.6}Fe_{0.4}O_{3-\delta}$. As a result, the oxygen permeation flux of the coated $La_{0.7}Sr_{0.3}Ga_{0.6}Fe_{0.4}O_{3-\delta}$ showed higher value, $0.5ml/min{\cdot}cm^2\;at\;950^{\circ}C$ than the uncoated one. Higher oxygen permeation was observed in the porously coated Lao $La_{0.7}Sr_{0.3}Ga_{0.6}Fe_{0.4}O_{3-\delta}$membranes with larger grain sizes. Syngas, $CO+H_2$, was successfully obtained from methane gas, $CH_4$, using the $La_{0.6}Sr_{0.4}CoO_{3-\delta}$ coated $La_{0.7}Sr_{0.3}Ga_{0.6}Fe_{0.4}O_{3-\delta}$, with over $40\%\;of\;CH_4$ conversion and syngas yield. $La_{0.7}Sr_{0.3}Ga_{0.6}Fe_{0.4}O_{3-\delta}$ membrane was stable even when it was exposed to the reducing environment, methane, for 600 hrs at $950^{\circ}C$.

• Journal of the Korean Electrochemical Society
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• v.10 no.4
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• pp.283-287
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• 2007

KIER has been developing the anode-supported flat tubular solid oxide fuel cell unit bundle for the intermediate temperature($700{\sim}800^{\circ}C$) operation. Anode-supported flat tubular cells have Ni/YSZ cermet anode support, 8 moi.% $Y_2O_3$ stabilized $ZrO_2(YSZ)$ thin electrolyte, and cathode multi-layer composed of Sr-doped $LaSrMnO_3(LSM)$, LSM-YSZ composite, and $LaSrCoFeO_3(LSCF)$. The prepared anode-supported flat tubular cell was joined with ferritic stainless steel cap by induction brazing process. Current collection for the cathode was achieved by winding Ag wire and $La_{0.6}Sr_{0.4}CoO_3(LSCo)$ paste, while current collection for the anode was achieved by using Ni wire and felt. For making stack, the prepared anode-supported flat tubular cells with effective electrode area of $90\;cm^2$ connected in series with 12 unit bundles, in which unit bundle consists of two cells connected in parallel. The performance of unit bundle in 3% humidified $H_2$ and air at $800^{\circ}C$ shows maximum power density of $0.39\;W/cm^2$ (@ 0.7V). Through these experiments, we obtained basic technology of the anode-supported flat tubular cell and established the proprietary concept of the anode-supported flat tubular cell unit bundle.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.31 no.1
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• pp.8-15
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• 2021

TiO2 has been used in various fields such as solar cells, dental implants, and photocatalysis, because it has high physical and chemical stability and is harmless to the body. TiO2 nanofibers which have a large specific surface area also show a good reactivity in bio-friendly products and excellent photocatalysis in air and water purification. To fabricate TiO2 nanofibers, an electrospinning method was used. To observe the diameter of TiO2 nanofibers with fabrication variables, the fabrication variables was divided into precursor composition variables and process variables and microstructure was analyzed. The concentrations of PVP (Polyvinylpyrrolidone) and TTIP (Titanium(IV) isopropoxide) were selected as precursor composition variables, and inflow velocity and voltage were also selected as process variables. Microstructure and crystal structure of TiO2 nanofibers were analyzed using FE-SEM (Field emission scanning electron microscope) and XRD (X-ray diffraction), respectively. As-spun TiO2 nanofibers with an average diameter of about 0.27 ㎛ to 1.31 ㎛ were transformed to anatase TiO2 nanofibers with an average diameter of about 0.22 ㎛ to 0.78 ㎛ after heat treatment of 3 hours at 450℃. Anatase TiO2 nanofibers with an average diameter of 0.22 ㎛ can be expected to improve the photocatalytic properties by increasing the specific surface area. To change the average diameter of TiO2 nanofibers, the control of precursor composition variables such as concentrations of PVP and TTIP is more efficient than the control of electrospinning process variables such as inflow velocity and voltage.

• Korean Journal of Ecology and Environment
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• v.55 no.1
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• pp.60-75
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• 2022

The Bayesian algorithm model is a model algorithm that calculates probabilities based on input data and is mainly used for complex disasters, water quality management, the ecological structure between living things or living-non-living factors. In this study, we analyzed the main factors affected Korean Estuary Trophic Diatom Index (KETDI) change based on the Bayesian network analysis using the diatom community and physicochemical factors in the domestic estuarine aquatic ecosystem. For Bayesian analysis, estuarine diatom habitat data and estuarine aquatic diatom health (2008~2019) data were used. Data were classified into habitat, physical, chemical, and biological factors. Each data was input to the Bayesian network model (GeNIE model) and performed estuary aquatic network analysis along with the nationwide and each coast. From 2008 to 2019, a total of 625 taxa of diatoms were identified, consisting of 2 orders, 5 suborders, 18 families, 141 genera, 595 species, 29 varieties, and 1 species. Nitzschia inconspicua had the highest cumulative cell density, followed by Nitzschia palea, Pseudostaurosira elliptica and Achnanthidium minutissimum. As a result of analyzing the ecological network of diatom health assessment in the estuary ecosystem using the Bayesian network model, the biological factor was the most sensitive factor influencing the health assessment score was. In contrast, the habitat and physicochemical factors had relatively low sensitivity. The most sensitive taxa of diatoms to the assessment of estuarine aquatic health were Nitzschia inconspicua, N. fonticola, Achnanthes convergens, and Pseudostaurosira elliptica. In addition, the ratio of industrial area and cattle shed near the habitat was sensitively linked to the health assessment. The major taxa sensitive to diatom health evaluation differed according to coast. Bayesian network analysis was useful to identify major variables including diatom taxa affecting aquatic health even in complex ecological structures such as estuary ecosystems. In addition, it is possible to identify the restoration target accurately when restoring the consequently damaged estuary aquatic ecosystem.