• 제목/요약/키워드: Deep Dependence

검색결과 88건 처리시간 0.023초

ZnO Intermediate Layer가 GaN 박막의 PL 특성에 미치는 영향 연구 (Study of the Effects of ZnO Intermediate Layer on Photoluminescence Properties of Magnetron Sputtering Grown GaN Thin Films)

  • 성웅제;이용일;박천일;최우범;성만영
    • 한국전기전자재료학회:학술대회논문집
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    • 한국전기전자재료학회 2001년도 하계학술대회 논문집
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    • pp.574-577
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    • 2001
  • GaN thin films on sapphire were grown by rf magnetron sputtering with ZnO buffer layer. The dependence of GaN film quality on ZnO buffer layer was investigated by X-ray diffraction(XRD). The improved film quality has been obtained by using thin ZnO buffer layer. Using Auger electron spectroscopy(AES), it was observed that the annealing process improved the GaN film quality. The surface roughness according to the annealing temperatures(700, 900, 1100$^{\circ}C$) were investigated by AFM(atomic force microscopy) and it was confirmed that the crystallization was improved by increasing the annealing temperature. Photoluminescence at 8K shows a near-band-edge peak at 3.2eV with no deep level emission.

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Relationship between Phycoerythrin and Nitrogen Content in Gloiopeltis furcata and Porphyra yezoensis

  • Hiroyuki Mizuta
    • ALGAE
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    • 제17권2호
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    • pp.89-93
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    • 2002
  • Seasonal changes of pigment compositionin two intertidal red algae, Gloiopeltis furcata (Postels et Ruprecht) J. Agardh, and Porphyra yezoensis Ueda, were investigated. Chlorophyll α and phycoerythrin levels were high during winter, but decreased in late spring or summer, with accompanying discoloration from deep red to green or yellow. This discoloation corresponded closely to the fluctuationof phycoerythrin content. Nevertheless, photosynthesis capacity was maintained by the increasing water temperature in the field, suggesting that large amounts of phycoerythrin are not necessary for photosynthesis. Phycoerythrin conten correlated significantly with nitrogen content in both species when the nitrogen level was greater than the level of critical content (1.30% DW in G. furcata, and 2.26% DW in P. yezoensis), indicating that phycoerythrin plays a more important role in the nitrogen status as a nitrogen pool than that of nitrogen critical content. Furthermore, the dependence level of the alage on phycoerythrin as a nitrogen pool was greater in P. yezoensis than in G. furcata because of the remarkable increase of phycoerythrin content in P. yezoensis with increasing jnitrogen content.

건식식각 기술 이용한 실리콘 압력센서의 특성 (Characteristics silicon pressure sensor using dry etching technology)

  • 우동균;이경일;김흥락;서호철;이영태
    • 센서학회지
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    • 제19권2호
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    • pp.137-141
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    • 2010
  • In this paper, we fabricated silicon piezoresistive pressure sensor with dry etching technology which used Deep-RIE and etching delay technology which used SOI(silicon-on-insulator) wafer. We improved pressure sensor offset and its temperature dependence by removing oxidation layer of SOI wafer which was used for dry etching delay layer. Sensitivity of the fabricated pressure sensor was about 0.56 mV/V${\cdot}$kPa at 10 kPa full-scale, and nonlinearity of the fabricated pressure sensor was less than 2 %F.S. The zero off-set change rate was less than 0.6 %F.S.

Evaluation of Mg size dependence on superconductivity of MgB2

  • Sinha, B.B.;Jang, S.H.;Chung, K.C.;Kim, J.H.;Dou, S.X.
    • 한국초전도ㆍ저온공학회논문지
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    • 제15권2호
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    • pp.39-43
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    • 2013
  • $MgB_2$ bulk samples are synthesized through solid state reaction route using Mg precursors with different particle size by keeping the boron precursor unchanged. Scanning electron microscopy study of the fractured surface for all the samples depicts quite distinct structure depending on the Mg precursor. Big size of Mg precursor resulted in to largely elongated and deep pores while smaller one gave roughly ellipsoidal and shallow pore structure. Influence of the Mg particle size on the grain to grain connectivity reflected in the critical current density value which was greater for samples with smaller Mg precursor. All the synthesized samples undergo a superconducting transition at around 36.5 K irrespective of different Mg precursor particle size.

펨토초 레이저에 의한 SUS 가공 특성 및 리플 생성 (Ripple Formation and Polarization Effects in Femtosecond Laser Drilling)

  • 손익부;고명진;김영섭;노영철
    • 한국레이저가공학회지
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    • 제12권1호
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    • pp.14-18
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    • 2009
  • Ripple formation of femtosecond laser in stainless steel is investigated using 184 fs pulses with a center wavelength of 785 nm. The effect of the laser polarization relative to the translation direction is observed. For drilling with a certain aspect ratio, reflections at the hole walls take place, leading to a non-uniform intensity distribution deep inside the formed hole. Finally, it is shown that a circular polarization during the drilling process significantly improves the quality of the produced holes.

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열간성형공정에서 벌크 아몰퍼스 소재의 변형거동 (Deformation Behavior of Bulk Amorphous Alloys During Hot Forming Process)

  • 이용신
    • 소성∙가공
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    • 제13권8호
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    • pp.696-703
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    • 2004
  • The purpose of this study is to examine the bulk/sheet forming characteristics of bulk amorphous alloys in the super cooled liquid state. Recently it is reported that amorphous alloys exhibit stress overshoot/undershoot and non-Newtonian behaviors even in the super cooled liquid state. The stress-strain curves with the temperature-dependences as well as strain-rate dependence of Newtonian/non-Newtonian viscosities of amorphous alloys are obtained based on the previous experimental works. Then, those curves are directly used in the thermo-mechanical finite element analyses. Upsetting and deep drawing of amorphous alloys are simulated to examine the effects of process parameters such as friction coefficient, forming speed and temperature. It could be concluded that the superior formability of an amorphous alloy can be obtained by taking the proper forming conditions.

HVPE법으로 성장된 GaN 기판의 광학적 특성 (Optical Properties of HVPE Grown GaN Substrates)

  • 김선태;문동찬
    • 한국전기전자재료학회논문지
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    • 제11권10호
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    • pp.784-789
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    • 1998
  • In this work, the optical properties of freestanding GaN single crystalline substrate grown by hydride vapor phase epitaxy(HVPE) were investigated. The low temperature PL spectrum in freestanding GaN consists of free and bound exciton emissions, and a deep DAP recombination around at 1.8eV. The optically-pumped stimulated emission in freestanding GaN substrate was observed at room temperature. At the maximum power density of 2MW/$\textrm{cm}^2$, the peak energy and FEHM of stimulated emission were 3.318 eV and 8meV, respectively. The excitation power dependence on the integrated emission intensity indicates the threshold pumping power density of 0.4 MW/$\textrm{cm}^2$.

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고도 호열성 Archaebacterium Thermococcus profundus가 생산하는 Amylolytic Enzymes (Amylolytic Enzymes Produced from Hyperthermophilic Archaebactorium Thermococcus profundus)

  • 정영철;김경숙;노승환
    • 한국식품영양학회지
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    • 제7권4호
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    • pp.259-266
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    • 1994
  • The hyperthermophilic archaebacterium Thermococcus profundus Isolated from a deep-sea hydrothermal vent system, produced several amylolytic enzymes such as extracellular amylase and pullulanase, intracellular a-1,4-91ucosidase in respone to the presence of complex carbohydrates In the growth medium. This strain showed high activities on 0.5% maltose than on complex carbohydrates One of the amylases was partially purified by ammonium sulfate precipitation, DEAE-Toyopearl chromatography. The amylase exhibited maximal activity at pH 5.5 and 80$^{\circ}C$, and was stable in the range of pH 5.5 to 9.5 and up to 80$^{\circ}C$ for 30 min. The enzyme activity was no dependence on Ca2+ and not inhibited by detergents. The amylase hydrolyzed soluble starch, amylose, amylopectin and glycogen to produce maltose and maltotriose with trace amounts of glucose, but not pullulan and ${\alpha}$-, ${\beta}$-, ${\gamma}$-cyclodextrin. Malto-oligosaccharides ranging from maltotetraose to maltoheptaose were hydrolyzed in an endo fashion.

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Numerical Analysis of Light Extraction Efficiency of a Core-shell Nanorod Light-emitting Diode

  • Kangseok Kim;Gijun Ju;Younghyun Kim
    • Current Optics and Photonics
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    • 제7권5호
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    • pp.496-503
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    • 2023
  • We present a detailed analysis of the light extraction efficiency (LEE) of a core-shell nanorod light emitting diode (LED) using finite-difference time-domain (FDTD) simulations. We found that the LEE has a deep dependence on source positions and polarization directions based on the calculated LEE results for every x and z position inside the core-shell nanorod structure. The LEEs are different for the upper part (pyramid) and the lower part (sidewall) of the core-shell nanorod owing to total internal reflection (TIR) and the generated optical modes in the structure. As a result, the LEE of sidewall is much larger than that of pyramid. The averaged LEE of the core-shell nanorod LED is also investigated with variable p-GaN thickness, n-GaN thickness, and height for the design guidelines for the optimized LEE of core-shell nanorod LEDs.

Forecasting realized volatility using data normalization and recurrent neural network

  • Yoonjoo Lee;Dong Wan Shin;Ji Eun Choi
    • Communications for Statistical Applications and Methods
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    • 제31권1호
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    • pp.105-127
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    • 2024
  • We propose recurrent neural network (RNN) methods for forecasting realized volatility (RV). The data are RVs of ten major stock price indices, four from the US, and six from the EU. Forecasts are made for relative ratio of adjacent RVs instead of the RV itself in order to avoid the out-of-scale issue. Forecasts of RV ratios distribution are first constructed from which those of RVs are computed which are shown to be better than forecasts constructed directly from RV. The apparent asymmetry of RV ratio is addressed by the Piecewise Min-max (PM) normalization. The serial dependence of the ratio data renders us to consider two architectures, long short-term memory (LSTM) and gated recurrent unit (GRU). The hyperparameters of LSTM and GRU are tuned by the nested cross validation. The RNN forecast with the PM normalization and ratio transformation is shown to outperform other forecasts by other RNN models and by benchmarking models of the AR model, the support vector machine (SVM), the deep neural network (DNN), and the convolutional neural network (CNN).