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Amorphous Lithium Lanthanum Titanate Solid Electrolyte Grown on LiCoO2 Cathode by Pulsed Laser Deposition for All-Solid-State Lithium Thin Film Microbattery (전고상 리튬 박막 전지 구현을 위해 펄스 레이저 증착법으로 LiCoO2 정극위에 성장시킨 비정질 (Li, La)TiO3고체 전해질의 특성)

  • 안준구;윤순길
    • Journal of the Korean Ceramic Society
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    • v.41 no.8
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    • pp.593-598
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    • 2004
  • To make the all-solid-state lithium thin film battery having less than 1 fm in thickness, LiCoO$_2$ thin films were deposited on Pt/TiO$_2$/SiO$_2$/Si substrate as a function of Li/Co mole ratio and the deposition temperature by Pulsed Laser Deposition (PLD). Especially, LiCoO$_2$ thin films deposited at 50$0^{\circ}C$ with target of Li/Co=1.2 mole ratio show an initial discharge capacity of 53 $\mu$Ah/cm$^2$-$\mu$m and capacity retention of 67.6%. The microstructural and electrochemical properies of (Li, La)TiO3 thin films grown on LiCoO$_2$Pt/TiO$_2$/SiO$_2$/Si structures by Pulsed Laser Deposition (PLD) were investigated at various deposition temperatures. The thin films grown at 10$0^{\circ}C$ show an initial discharge capacity of approximately 51 $\mu$Ah/cm$^2$-$\mu$m and moreover show excellent discharge capacity retention of 90% after 100 cycles. An amorphous (Li, La)TiO$_3$ solid electrolyte is possible for application to solid electrolyte for all-solid-state lithium thin film battery below 1 $\mu$m.

Characterization of a new commercial strain 'Gumbit' in Pleurotus cornucopiae var. citrinopileatus (노랑느타리 품종 '금빛'의 특성)

  • Yoo, Young-Bok;Kong, Won-Sik;Jang, Kab-Yeul;Kim, In-Yeup;Oh, Se-Jong;Jhune, Chang-Sung
    • Journal of Mushroom
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    • v.4 no.3
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    • pp.83-87
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    • 2006
  • A new commercial strain "Gumbit" of golden oyster mushroom was developed by hyphal anastomosis. It was improved with hybridization between monokaryotic strain derived from ASI 2295 and ASI 2703. The optimum temperature of mycelial growth and fruiting body development were $25{\sim}30^{\circ}C$ and $19{\sim}24^{\circ}C$, respectively. The pileus was golden to brilliant yellow color. Commercial strain "Gumbit" was not as prolific as the more commonly cultivated Pleurotus ostreatus in the conversion of substrate mass to mushrooms. However, cultivator can save money for mushroom growing on high-temperature season as like summer in Korea. Since picking individual mushrooms is tedious and often damages the fragile fruiting bodies compared with other species of oyster mushrooms.

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PCA­based Waveform Classification of Rabbit Retinal Ganglion Cell Activity (주성분분석을 이용한 토끼 망막 신경절세포의 활동전위 파형 분류)

  • 진계환;조현숙;이태수;구용숙
    • Progress in Medical Physics
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    • v.14 no.4
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    • pp.211-217
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    • 2003
  • The Principal component analysis (PCA) is a well-known data analysis method that is useful in linear feature extraction and data compression. The PCA is a linear transformation that applies an orthogonal rotation to the original data, so as to maximize the retained variance. PCA is a classical technique for obtaining an optimal overall mapping of linearly dependent patterns of correlation between variables (e.g. neurons). PCA provides, in the mean-squared error sense, an optimal linear mapping of the signals which are spread across a group of variables. These signals are concentrated into the first few components, while the noise, i.e. variance which is uncorrelated across variables, is sequestered in the remaining components. PCA has been used extensively to resolve temporal patterns in neurophysiological recordings. Because the retinal signal is stochastic process, PCA can be used to identify the retinal spikes. With excised rabbit eye, retina was isolated. A piece of retina was attached with the ganglion cell side to the surface of the microelectrode array (MEA). The MEA consisted of glass plate with 60 substrate integrated and insulated golden connection lanes terminating in an 8${\times}$8 array (spacing 200 $\mu$m, electrode diameter 30 $\mu$m) in the center of the plate. The MEA 60 system was used for the recording of retinal ganglion cell activity. The action potentials of each channel were sorted by off­line analysis tool. Spikes were detected with a threshold criterion and sorted according to their principal component composition. The first (PC1) and second principal component values (PC2) were calculated using all the waveforms of the each channel and all n time points in the waveform, where several clusters could be separated clearly in two dimension. We verified that PCA-based waveform detection was effective as an initial approach for spike sorting method.

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