• Applied Chemistry for Engineering
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• v.19 no.5
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• pp.477-483
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• 2008

$La_{0.7}Sr_{0.3}Co_{0.2}Fe_{0.8}O_{3-{\delta}$ oxide was synthesized by a citrate method and a typical dense membrane of perovskite oxide has been prepared using as-prepared powder by pressing and sintering at $1300^{\circ}C$. Precursor of $La_{0.7}Sr_{0.3}Co_{0.2}Fe_{0.8}O_{3-{\delta}$ prepared by citrate method was investigated by TGA and XRD. Metal-citrate complex in precursor was decomposed into perovskite oxide in the temperature range of $260{\sim}410^{\circ}C$ but XRD results showed $SrCO_3$ existed as impurity at less than $900^{\circ}C$. Electrical conductivity of membrane increased with increasing temperature but then decreased over $700^{\circ}C$ in air atmosphere ($Po_2=0.2atm$) and $600^{\circ}C$ in He atmosphere ($Po_2=0.01atm$) respectively due to oxygen loss from the crystal lattice. The oxygen permeation flux increased with increasing temperature and maximum oxygen permeation flux of $La_{0.7}Sr_{0.3}Co_{0.2}Fe_{0.8}O_{3-{\delta}$ membrane with 1.6 mm thickness was about $0.31cm^3/cm^2{\cdot}min$ at $950^{\circ}C$. The activation energy for oxygen permeation was 88.4 kJ/mol in the temperature range of $750{\sim}950^{\circ}C$. Perovskite structure of membrane was not changed after permeation test of 40 h and the membrane was stable without secondary phase change with 0.3 mol Sr addition.

• Applied Microscopy
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• v.38 no.4
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• pp.279-284
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• 2008

The phase change materials have been extensively used as an optical rewritable data storage media utilizing their phase change properties. Recently, the phase change materials have been spotlighted for the application of non-volatile memory device, such as the phase change random access memory. In this work, we have investigated the crystallization behavior and microstructure analysis of In-Sb-Te (IST) thin films deposited by RF magnetron sputtering. Transmission electron microscopy measurement was carried out after the annealing at $300^{\circ}C$, $350^{\circ}C$, $400^{\circ}C$ and $450^{\circ}C$ for 5 min. It was observed that InSb phases change into $In_3SbTe_2$ phases and InTe phases as the temperature increases. It was found that the thickness of thin films was decreased and the grain size was increased by the bright field transmission electron microscopy (BF TEM) images and the selected area electron diffraction (SAED) patterns. In a high resolution transmission electron microscopy (HRTEM) study, it shows that $350^{\circ}C$-annealed InSb phases have {111} facet because the surface energy of a {111} close-packed plane is the lowest in FCC crystals. When the film was heated up to $400^{\circ}C$, $In_3SbTe_2$ grains have coherent micro-twins with {111} mirror plane, and they are healed annealing at $450^{\circ}C$. From the HRTEM, InTe phase separation was occurred in this stage. It can be found that $In_3SbTe_2$ forms in the crystallization process as composition of the film near stoichiometric composition, while InTe phase separation may take place as the composition deviates from $In_3SbTe_2$.

• Solar Energy
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• v.20 no.2
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• pp.43-54
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• 2000

We prepared and characterized $Cu(In_{1-x}Ga_x)Se_2$(CIGS) films using a elemental co-evaporation method for absorbing layer of high efficiency thin film solar cells. The CIGS films deposited on a soda-lime glass exhibited low resistivity because of higher carrier concentration. Na was accumulated at the CIGS surface and the 0 and Se were also accumulated at the surface, suggesting that oxidation is a driving force of Na accumulation. The structure of CIGS film was modified or a secondary phase was formed in the Cu-poor CIGS bulk films probably due to the incorporation of Na into Cu vacancy sites. As the Ga/(In+Ga) ratio increased, the diffraction peaks of $Cu(In_{1-x}Ga_x)Se_2$ films were shifted to larger angle and splitted, and the grain size of $Cu_{0.91}(In_{1-x}Ga_x)Se_2$ films became smaller. All $Cu_{0.91}(In_{1-x}Ga_x)Se_2$ films showed the p-type conductivity regardless of the Ga/(In+Ga) ratio. Ag/n-ZnO/i-ZnO/CdS/$Cu_{0.91}(In_{0.7}Ga_{0.3})Se_2$/Mo solar cells were fabricated. The currently best efficiency in this study was 14.48% for $0.18cm^2$ area ($V_{oc}=581.5mV,\;J_{sc}=34.88mA$, F.F=0.714).

• Geophysics and Geophysical Exploration
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• v.12 no.1
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• pp.56-68
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• 2009

Ongoing and extensive urbanisation, which is frequently accompanied with careless construction works, may threaten important archaeological structures that are still buried in the urban areas. Ground Penetrating Radar (GPR) and Electrical Resistivity Tomography (ERT) methods are most promising alternatives for resolving buried archaeological structures in urban territories. In this work, three case studies are presented, each of which involves an integrated geophysical survey employing the surface three-dimensional (3D) ERT and GPR techniques, in order to archaeologically characterise the investigated areas. The test field sites are located at the historical centres of two of the most populated cities of the island of Crete, in Greece. The ERT and GPR data were collected along a dense network of parallel profiles. The subsurface resistivity structure was reconstructed by processing the apparent resistivity data with a 3D inversion algorithm. The GPR sections were processed with a systematic way, applying specific filters to the data in order to enhance their information content. Finally, horizontal depth slices representing the 3D variation of the physical properties were created. The GPR and ERT images significantly contributed in reconstructing the complex subsurface properties in these urban areas. Strong GPR reflections and highresistivity anomalies were correlated with possible archaeological structures. Subsequent excavations in specific places at both sites verified the geophysical results. The specific case studies demonstrated the applicability of ERT and GPR techniques during the design and construction stages of urban infrastructure works, indicating areas of archaeological significance and guiding archaeological excavations before construction work.

• Korean Journal of Mineralogy and Petrology
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• v.35 no.1
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• pp.41-50
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• 2022

To study the properties of Sr²⁺ exchange into zeolite A with increasing the molar concentration of Na⁺ in given exchange solution, four single crystals of fully dehydrated Sr²⁺- and Na⁺- exchanged zeolite A were prepared by the bath method using mixed ion-exchange solutions. The Sr(NO₃)₂:NaNO₃ molar rations of the ion exchange solution were 1:1(crystal 1), 1:100(crystal 2), 1:250(crystal 3), and 1:500 (crystal 4), respectively, with a total concentration of 0.05 M. The single-crystals were then vacuum dehydration at 623 K and 1×10^-4 Pa for 2 days. Their single-crystal structures were determined by single-crystal synchrotron X-ray diffraction techniques in the cubic space group Pm3-m, at 100(1) K, and were then refined to the final error indices of R₁/wR₂=0.047/0.146, 0.048/0.142, 0.036/0.128, and 0.040/0.156 for crystals 1, 2, 3, and 4, respectively. In crystals 1 and 2, the 6 Sr²⁺ ions are found at three different crystallographic sites. In crystal 3, 1 Sr²⁺ and 10 Na⁺ ions are found in large cavity and sodalite unit. In crystal 4, only 12 Na⁺ ions occupy three equipoints. The degree of Sr²⁺ ion-exchange decreased sharply from 100 to 16.7 to 0% as the initial Na⁺ concentration increase and the Sr²⁺ concentration decrease. In addition, the unit cell constant of the zeolite framework decreased with this lower level of Sr²⁺ exchange.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1505-1514
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• 2022

Image matching is a crucial preprocessing step for effective utilization of multi-temporal and multi-sensor very high resolution (VHR) satellite images. Deep learning (DL) method which is attracting widespread interest has proven to be an efficient approach to measure the similarity between image pairs in quick and accurate manner by extracting complex and detailed features from satellite images. However, Image matching of VHR satellite images remains challenging due to limitations of DL models in which the results are depending on the quantity and quality of training dataset, as well as the difficulty of creating training dataset with VHR satellite images. Therefore, this study examines the feasibility of DL-based method in matching pair extraction which is the most time-consuming process during image registration. This paper also aims to analyze factors that affect the accuracy based on the configuration of training dataset, when developing training dataset from existing multi-sensor VHR image database with bias for DL-based image matching. For this purpose, the generated training dataset were composed of correct matching pairs and incorrect matching pairs by assigning true and false labels to image pairs extracted using a grid-based Scale Invariant Feature Transform (SIFT) algorithm for a total of 12 multi-temporal and multi-sensor VHR images. The Siamese convolutional neural network (SCNN), proposed for matching pair extraction on constructed training dataset, proceeds with model learning and measures similarities by passing two images in parallel to the two identical convolutional neural network structures. The results from this study confirm that data acquired from VHR satellite image database can be used as DL training dataset and indicate the potential to improve efficiency of the matching process by appropriate configuration of multi-sensor images. DL-based image matching techniques using multi-sensor VHR satellite images are expected to replace existing manual-based feature extraction methods based on its stable performance, thus further develop into an integrated DL-based image registration framework.