122 research outputs found

    Pesticides as a risk factor for metabolic syndrome: Population-based longitudinal study in Korea

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    Background and purpose Metabolic syndrome (MetS) is an adverse health effect that can be associated with pesticide exposure. However, there are few epidemiologic studies on the relationship between pesticide use and MetS incidence. The present study examined the relationship between pesticide exposure and incidence of MetS in a rural population in Korea. Methods We examined the causal relationship between pesticide use and MetS incidence in a rural population. We used Data from the Korea Farmers Cohort study of 1,162 participants. Poisson regression with a robust error variance was used to calculate relative risks (RRs) and 95% confidence intervals (CIs) to estimate the relationship between pesticide exposure and MetS. Results The incidence of MetS was 20.7%. Pesticide use increased the RR of MetS incidence. In women, we observed a lowโ€“dose effect related to MetS and pesticide exposure. Conclusion Pesticide exposure is related to the incidence of MetS; the causal relationship differs in men and women. ๋ฐฐ๊ฒฝ ๋Œ€์‚ฌ์ฆํ›„๊ตฐ์€ ๋†์•ฝ ๋…ธ์ถœ๊ณผ ๊ด€๋ จ ๋  ์ˆ˜ ์žˆ๋Š” ์œ ํ•ดํ•œ ๊ฑด๊ฐ• ์˜ํ–ฅ์ด๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๋†์•ฝ ์‚ฌ์šฉ๊ณผ ๋Œ€์‚ฌ์ฆํ›„๊ตฐ ๋ฐœ์ƒ ์‚ฌ์ด์˜ ๊ด€๊ณ„์— ๋Œ€ํ•œ ์—ญํ•™์  ์—ฐ๊ตฌ๋Š” ๊ฑฐ์˜ ์—†๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ํ•œ๊ตญ์˜ ๋†์ดŒ ์ธ๊ตฌ์ง‘๋‹จ์—์„œ ๋†์•ฝ ๋…ธ์ถœ๊ณผ ๋Œ€์‚ฌ์ฆํ›„๊ตฐ ๋ฐœ๋ณ‘๋ฅ  ์‚ฌ์ด์˜ ๊ด€๋ จ์„ฑ์„ ์กฐ์‚ฌํ•˜์˜€๋‹ค. ๋Œ€์ƒ ๋ฐ ๋ฐฉ๋ฒ• ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋†์ดŒ ์ธ๊ตฌ์—์„œ ๋†์•ฝ ์‚ฌ์šฉ๊ณผ ๋Œ€์‚ฌ์ฆํ›„๊ตฐ ๋ฐœ๋ณ‘ ์‚ฌ์ด์˜ ์ธ๊ณผ ๊ด€๊ณ„๋ฅผ ์กฐ์‚ฌํ–ˆ๋‹ค. 1,162 ๋ช…์˜ ์—ฐ๊ตฌ๋Œ€์ƒ์ž์— ๋Œ€ํ•œ ์›์ฃผ ํ‰์ฐฝ ๋†์—…์ธ ์ฝ”ํ˜ธํŠธ ์—ฐ๊ตฌ์˜ ๋ฐ˜๋ณต ์ธก์ • ๋ฐ์ดํ„ฐ๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋†์•ฝ ๋…ธ์ถœ๊ณผ ๋Œ€์‚ฌ์ฆํ›„๊ตฐ ์‚ฌ์ด์˜ ๊ด€๊ณ„๋ฅผ ์ถ”์ •ํ•˜๊ณ , ์ƒ๋Œ€ ์œ„ํ—˜๋„(Relative risk)์™€ 95 % ์‹ ๋ขฐ ๊ตฌ๊ฐ„ (CI)์„ ๊ณ„์‚ฐํ•˜๊ธฐ ์œ„ํ•ด ๋กœ๋ฒ„์ŠคํŠธ ํฌ์•„์†ก ํšŒ๊ท€๋ถ„์„(Poisson regression with a robust error variance)์„ ์‹œํ–‰ ํ•˜์˜€๋‹ค. ๊ฒฐ๊ณผ ๋†์•ฝ ๋…ธ์ถœ ์ง‘๋‹จ์—์„œ ๋Œ€์‚ฌ์ฆํ›„๊ตฐ์˜ ๋ฐœ์ƒ๋ฅ ์€ 20.7 % ์ด์—ˆ๋‹ค. ๋†์•ฝ ์‚ฌ์šฉ์€ ๋Œ€์‚ฌ์ฆํ›„๊ตฐ ๋ฐœ์ƒ์˜ ์ƒ๋Œ€ ์œ„ํ—˜๋„๋ฅผ ์ฆ๊ฐ€์‹œ์ผฐ๋‹ค. ์—ฌ์„ฑ์—์„œ๋Š” ๋Œ€์‚ฌ์ฆํ›„๊ตฐ ๋ฐ ๋†์•ฝ ๋…ธ์ถœ๊ณผ ๊ด€๋ จ๋œ ์ €์šฉ๋Ÿ‰ ๊ฑด๊ฐ• ์˜ํ–ฅ ํšจ๊ณผ(low-dose effects )๋ฅผ ๊ด€์ฐฐํ•˜์˜€๋‹ค. ๊ฒฐ๋ก  ๋†์•ฝ ๋…ธ์ถœ์€ ๋Œ€์‚ฌ์ฆํ›„๊ตฐ์˜ ๋ฐœ์ƒ๊ณผ ๊ด€๋ จ์ด ์žˆ๋‹ค. ๋†์•ฝ ๋…ธ์ถœ๋กœ ์ธํ•œ ๋Œ€์‚ฌ์ฆํ›„๊ตฐ ๋ฐœ์ƒ์˜ ์ƒ๋Œ€์œ„ํ—˜๋„๋Š” ๋‚จ๋…€๊ฐ„์— ์ฐจ์ด๊ฐ€ ์žˆ๋‹ค.open๋ฐ•

    Mutation of Drosophila Gongpo Gene Causes Mitochondrial defect and Cell death

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์‚ฌ๋ฒ”๋Œ€ํ•™ ๊ณผํ•™๊ต์œก๊ณผ(์ƒ๋ฌผ์ „๊ณต),2019. 8. ์ „์ƒํ•™.phosphatidylserine(PS)์€ ์„ธํฌ๋ง‰์„ ๊ตฌ์„ฑํ•˜๊ณ  ์žˆ๋Š” ์ค‘์š”ํ•œ ์ธ์ง€์งˆ ์ค‘ ํ•˜๋‚˜์ด๋‹ค. ์ด๋Ÿฌํ•œ ๊ตฌ์กฐ์  ์ค‘์š”์„ฑ ์™ธ์—๋„, ์„ธํฌ ์‹ ํ˜ธ์™€ apoptotic cell์˜ cell clearance์— ์žˆ์–ด์„œ ์ค‘์š”ํ•œ ์—ญํ• ์„ ์ˆ˜ํ–‰ํ•˜๋ฉฐ, ์‹ ๊ฒฝ ํ‡ดํ–‰์— ๊ด€์—ฌํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋ณด์ธ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” PS ํ•ฉ์„ฑํšจ์†Œ๋ฅผ ์•”ํ˜ธํ™”ํ•˜๋Š” ์ดˆํŒŒ๋ฆฌ์˜ ์œ ์ „์ž Gongpo์˜ ๋Œ์—ฐ๋ณ€์ด ํ‘œํ˜„ํ˜•์„ ํ™•์ธํ•˜์˜€๋‹ค. Gongpo ์œ ์ „์ž ๋Œ์—ฐ๋ณ€์ด์˜ trans-heterozygous mutant์—์„œ ์‹ ๊ฒฝํ‡ดํ–‰์„ฑ ์งˆํ™˜์˜ ๋Œ€ํ‘œ์ ์ธ ํ‘œํ˜„ํ˜•์ด๋ผ๊ณ  ์•Œ๋ ค์ง„, ์ˆ˜๋ช… ๋‹จ์ถ•, ์šด๋™๋Šฅ๋ ฅ ๊ฐํ‡ด, ์ถฉ๊ฒฉ๋ฏผ๊ฐ์„ฑ ๋ฐ ์‹ ๊ฒฝ์กฐ์ง์˜ ํ‡ดํ™”๋ฅผ ํ™•์ธํ•˜์˜€๋‹ค. ๋˜ํ•œ Gongpo ๋Œ์—ฐ๋ณ€์ด์—์„œ ROS์˜ ์ฆ๊ฐ€์™€ ํ•จ๊ป˜ ์‹ ๊ฒฝ๊ณ„์˜ ๋ฏธํ† ์ฝ˜๋“œ๋ฆฌ์•„ ํ˜•ํƒœ ๋ฐ ๊ธฐ๋Šฅ์˜ ์ด์ƒ์„ ํ™•์ธํ•˜์˜€์œผ๋ฉฐ, autophagy ๋ฐ apoptosis์˜ ์ฆ๊ฐ€ ๋˜ํ•œ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. Gongpo ๋Œ์—ฐ๋ณ€์ด์—์„œ Secondary necrosis๊ฐ€ ํฌ๊ฒŒ ์ฆ๊ฐ€ํ•˜์—ฌ ๋ฐœ์ƒํ•จ์„ ํ™•์ธํ•˜์˜€๋Š”๋ฐ, ์ด๋Ÿฌํ•œ secondary necrosis๊ฐ€ ๋Œ์—ฐ๋ณ€์ด์—์„œ์˜ ๊ด‘๋ฒ”์œ„ํ•œ ์„ธํฌ์‚ฌ๋ฉธ์„ ์•ผ๊ธฐ์‹œํ‚ค๋Š” ๋“ฏํ•˜๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์‹ ๊ฒฝ๊ณ„ ๋‚ด PS์˜ ํ•ฉ์„ฑ ์ด์ƒ์— ์˜ํ•ด ์œ ๋ฐœ๋˜๋Š” ์‹ ๊ฒฝํ‡ดํ–‰์„ฑ ์งˆํ™˜์˜ ์ƒˆ๋กœ์šด ๊ธฐ์ „์„ ์ œ์•ˆํ•œ๋‹ค.Phosphatidylserine (PS) is one of the integral phospholipid components in the eukaryotic cell membranes and organelles. In addition to the structural importance, it is also shown to play active roles in cellular signaling and apoptotic cell clearance. In this study, we characterized mutant phenotypes of a Drosophila gene Gongpo that encodes a PS synthase. Adult flies trans-heterozygous for Gongpo mutations showed general neurodegenerative phenotypes such as bang-sensitivity, locomotion defects, reduced life span, and excessive formation of vacuoles in the brain. Gongpo mutants showed defective mitochondria in nervous system in conjunction with elevated production of reactive oxygen species (ROS), increased autophagy and apoptotic cell death in the adult brain. Moreover, secondary necrosis was occurred in Gongpo mutants and it seems to cause cell death even to the surrounding cells. All together leading to excessive neurodegeneration. This study proposes a new mechanism of neurodegenerative diseases triggered by defective PS metabolism in nervous system.์ œ 1 ์žฅ ์„œ ๋ก  1 ์ œ 1 ์ ˆ ์‹ ๊ฒฝํ‡ดํ–‰์„ฑ ์งˆํ™˜๊ณผ ์ธ์ง€์งˆ 1 ์ œ 2 ์ ˆ Phosphatidylserine(PS)์™€ Phosphatidylserine synthase 3 ์ œ 3 ์ ˆ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒฐ๊ณผ ๋ฐ ์—ฐ๊ตฌ ๋ชฉํ‘œ 5 ์ œ 2 ์žฅ ์‹คํ—˜ ๋ฐฉ๋ฒ• ๋ฐ ์žฌ๋ฃŒ 7 ์ œ 1 ์ ˆ ์‹คํ—˜์— ์‚ฌ์šฉ๋œ ์ดˆํŒŒ๋ฆฌ 7 ์ œ 2 ์ ˆ ๋‹จ๋ฐฑ์งˆ ์„œ์—ด alignment ๋ฐ ์„œ์—ด ์ƒ๋™์„ฑ ํ™•์ธ 7 ์ œ 3 ์ ˆ ์œ ์ „์ž ๋ฐœํ˜„๋Ÿ‰ ํ™•์ธ(Quantitative real-time PCR) 8 ์ œ 4 ์ ˆ ์‹ ๊ฒฝํ‡ดํ–‰์„ฑ ์งˆํ™˜์˜ ํ‘œํ˜„ํ˜• ํ™•์ธ 8 ์ œ 5 ์ ˆ ์ดˆํŒŒ๋ฆฌ์˜ ๋‡Œ ์ ˆํŽธ ์ œ์ž‘ ๋ฐ ๊ด€์ฐฐ 9 ์ œ 6 ์ ˆ ํˆฌ๊ณผ์ „์žํ˜„๋ฏธ๊ฒฝ(TEM) 10 ์ œ 7 ์ ˆ ๊ทผ์œก ๋ฏธํ† ์ฝ˜๋“œ๋ฆฌ์•„ ๊ด€์ฐฐ 10 ์ œ 8 ์ ˆ ๋‡Œ ์กฐ์ง์˜ ROS ์ธก์ • 10 ์ œ 9 ์ ˆ ๋‡Œ ์กฐ์ง์˜ ์„ธํฌ์‚ฌ๋ฉธ ํ™•์ธ 11 ์ œ 10 ์ ˆ ๋‡Œ ์กฐ์ง์˜ Necrosis ํ™•์ธ 12 ์ œ 3 ์žฅ ์‹คํ—˜ ๊ฒฐ๊ณผ 13 ์ œ 1 ์ ˆ ํฌ์œ ๋ฅ˜์˜ PSS์™€ ์ดˆํŒŒ๋ฆฌ์˜ Gong์˜ ์ƒ๋™์„ฑ ํ™•์ธ 13 ์ œ 2 ์ ˆ Gong ์œ ์ „์ž ๋Œ์—ฐ๋ณ€์ด์˜ ์‹ ๊ฒฝํ‡ดํ–‰์„ฑ ์งˆํ™˜ ํ‘œํ˜„ํ˜• ํ™•์ธ 17 ์ œ 3 ์ ˆ Gong ์œ ์ „์ž ๋Œ์—ฐ๋ณ€์ด์˜ ๋ฏธํ† ์ฝ˜๋“œ๋ฆฌ์•„ ํ˜•ํƒœ ์ด์ƒ ํ™•์ธ 22 ์ œ 4 ์ ˆ Gong ์œ ์ „์ž ๋Œ์—ฐ๋ณ€์ด์˜ ROS ๋ฐœ์ƒ๋Ÿ‰ ํ™•์ธ 27 ์ œ 5 ์ ˆ Gong ์œ ์ „์ž ๋Œ์—ฐ๋ณ€์ด์˜ autophagy ์ฆ๊ฐ€๋Ÿ‰ ํ™•์ธ 30 ์ œ 6 ์ ˆ Gong ์œ ์ „์ž ๋Œ์—ฐ๋ณ€์ด์˜ apoptosis ๋ฐ secondary necrosis ํ™•์ธ 34 ์ œ 7 ์ ˆ Cortex glia ํŠน์ด์  Gong ์œ ์ „์ž knock down ๋Œ์—ฐ๋ณ€์ด์˜ ์‹ ๊ฒฝํ‡ดํ–‰์„ฑ์งˆํ™˜ ํ‘œํ˜„ํ˜• ํ™•์ธ 39 ์ œ 4 ์žฅ ๊ณ ์ฐฐ 41 ์ฐธ๊ณ ๋ฌธํ—Œ 45 Abstract 55Maste

    Electrical and Interfacial Characterization of GaSb MOS Capacitors by Using Sulfuric Passivation, and Post- and Pre-Deposition Rapid Thermal Process

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› ๊ณต๊ณผ๋Œ€ํ•™ ์žฌ๋ฃŒ๊ณตํ•™๋ถ€, 2017. 8. ๊น€ํ˜•์ค€.GaSb has attracted significant attention as a strong channel candidate for next generation nanoscale logic metal oxide semiconductor field-effect transistors (MOSFETs), since it has extraordinary hole mobility(~ 3000 cm2/Vs) compared to conventional silicon devices, chemical resistance of its native oxides towards water, and high effective density of states(1.8 x 1019 cm-3). However, there are some drawbacks to adopt GaSb to the MOSFETs such as high interface states. When it comes to the operation of MOSFETs with โ…ข-โ…ค channel materials, because of the high interface states, the Fermi-level pinning phenomena lead to severe stretch-out of capacitance-voltage (C-V) and is one of the issues as well. The Fermi-level pinning comes especially from the native oxides and elemental Sb of GaSb upon exposure to oxygen. GaSb is also known to form the native oxides rapidly with air exposure, which makes it more difficult to reduce the native oxides. In this study, GaSb metal oxide semiconductor (MOS) capacitors were fabricated with low temperature atomic layer deposition (ALD). Electrical properties were evaluated by C-V frequency dispersion and interface traps density (Dit) from the Terman method. Interfacial analysis was performed to investigate the compositions, roughness, thickness, and density by Auger electron spectroscopy (AES), spectroscopic ellipsometer (SE), x-ray reflectometry (XRR), atomic-force microscopy (AFM), x-ray photoelectron spectroscopy (XPS), and transmission electron microscopy (TEM). Low temperature ALD was conducted to deposit Al2O3 on top of GaSb substrates as a gate oxide at various deposition process temperatures(100 ~ 310 โ„ƒ). It showed that the Dit level was lowered and the Fermi-level pinning behavior was alleviated in a C-V curve with low temperature ALD at 150 โ„ƒ. From the XPS results, the ratio of pure Ga2O3 over metastable Ga2O increased as the deposition temperature decreased and was highest with low temperature ALD at 150 โ„ƒ. The C-V curve deteriorated with low temperature ALD at 100 โ„ƒ. It can be explained by the XRR results that demonstrate the significant decrease in density of the Al2O3 film with low temperature ALD at 100 โ„ƒ. To reduce the Dit, a post deposition annealing process with N2 ambient at various temperatures (150 ~ 300 โ„ƒ) for 30 seconds was adopted after depositing Al2O3. The stretch-out of the C-V curve was alleviated by post deposition rapid thermal process (RTP) at 250 โ„ƒ but the C-V curve was more stretched out by the post-deposition RTP at 300 โ„ƒ. The roughness decreased as the RTP temperature increased, then increased when the RTP temperature was over 300 โ„ƒ. The ratio of pure Ga2O3 over metastable Ga2O increased as the RTP temperature increased then decreased when the RTP temperature was over 300 โ„ƒ. The Dit is very consistent with the interfacial results. Forming gas annealing (FGA) is known as one of the effective ways to reduce the Dit in the SiO2/Si systems by filling up dangling bonds with hydrogen. To verify these hydrogen annealing effects, Al2O3/GaSb had been annealed with hydrogen including gases (5% H2/95 % N2 and 10 % H2/90 % N2). Results from both experiments with two different gases showed that the reduction of pure Ga2O3 to metastable Ga2O occurred by hydrogen annealing. The ratio of Ga2O3 over Ga2O decreased as the process temperature increased and the flux of hydrogen increased. The stretch-out in the C-V curves became worse and the Dit level significantly increased by hydrogen annealing due to the decreased ratio of pure Ga2O3 over metastable Ga2O. As mentioned before, GaSb forms the native oxide quickly with air exposure. Therefore, passivation is essential to be considered for fabricating the GaSb capacitors in ex-situ. Sulfuric passivation was chosen to be used, since the surface of GaSb can be passivated by forming Ga-S and Sb-S bonds, which would improve the electrical properties of the MOS capacitors. Each sample was immersed in the sulfuric solution (5 % (NH4)2S) for various times (1 ~ 15 minutes). The stretch-out of the C-V curve was successfully alleviated with immersion in the sulfuric solution for 5 minutes. However, immersion time longer than 5 minutes aggravated the C-V curves. The AFM results showed that the roughness increased as the immersion time increased. The inter layer (IL) between Al2O3 and GaSb also became longer with longer immersion duration. Sb-oxide is not able to be perfectly cleaned by HCl even though HCl is known as the most effective wet chemical to get rid of the native oxides of GaSb. This remaining Sb-oxide oxidizes GaSb to Ga-oxide and changes itself to elemental Sb. For this, pre-deposition RTP (N2 ambient), for improving electrical properties of the Al2O3/GaSb MOS capacitors, was adopted for the first time in this study. The improvement of stretch-out of the C-V curves was outstanding. The the Dit was also successfully reduced by the pre-deposition RTP at 550 and 575 โ„ƒ and this the Dit value is the lowest one among the ones of sulfur treated GaSb MOS capacitors in literature(1.06 x 1012 cm-2ev-1 @ E-Ev=0.004). The Fermi-level pinning phenomenon deteriorated by pre-deposition RTP at 500 โ„ƒ because chemical reactions for making the native oxides were accelerated at 500 โ„ƒ. The accelerated chemical reactions were proven by XPS, AFM, AES, and TEM analysis. The ratio of Ga2O3 over Ga2O is also very consistent with electrical results. In conclusion, low temperature ALD, post-deposition RTP, sulfuric passivation, and pre-deposition RTP are the effective ways to alleviate the Fermi-level pinning phenomenon that leads to the significant stretch-out in the C-V curves.1. Introduction 1 1.1. Indispensability and Issues to Adopt III-V Channel Materials for MOSFETs 1 1.2. Objective and Chapter Overview 5 2. Literature Review 7 2.1. Native Oxide Formation of GaSb 7 2.1.1. Fast Oxidation of GaSb with Air Exposure 9 2.1.2. Effects of the Native Oxide on Electrical Properties 13 2.1.3. Thermal Desorption Behavior of the Native Oxide of GaSb 19 2.2. Surface Treatments and Passivation of GaSb 23 2.2.1. Chemical Wet Cleaning 23 2.2.2. Hydrogen Plasma 25 2.2.3. Sulfuric Passivation 37 2.2.4. Insertion of Passivation Layers 48 2.3. Oxide Deposition on GaSb by Atomic Layer Deposition 52 2.3.1. Deposition of Almina by Atomic Layer Deposition 52 2.3.2. Low Temperature Atomic Layer Deposition 55 2.4. Post-Deposition Thermal Annealing Process 57 2.4.1. Rapid Thermal Process 57 2.4.2. Forming Gas Annealing 59 2.5. Electrical Characterization of III-V MOS Devices 60 2.5.1. The Terman Method for the Dit Extraction 60 3. Deposition of Alumina on GaSb by Low-Temperature Atomic Layer Deposition 63 3.1. Introduction 63 3.2. Experimental Procedures 64 3.3. Results and Discussions 69 3.4. Summary 76 4. Post-Deposition Rapid Thermal Process of Alumina Deposited GaSb 77 4.1. Introduction 77 4.2. Experimental Procedures 78 4.3. Results and Discussions 84 4.3.1. Post-Deposition Rapid Thermal Process in a Nitrogen Ambience 84 4.3.2. Post-Deposition Annealing in a Gas Mixture Ambience ( 5 % H2 and 95 % N2) 92 4.3.3. Post-Deposition Annealing in a Gas Mixture Ambience (10 % H2 and 90 % N2) 96 4.4. Summary 104 5. Sulfuric Passivation of GaSb 107 5.1. Introduction 107 5.2. Experimental Procedures 108 5.3. Results and Discussions 111 5.4. Summary 118 6. Pre-Deposition Rapid Thermal Annealing of GaSb in a Nitrogen Ambient 119 6.1. Introduction 119 6.2. Experimental Procedures 121 6.3. Results and Discussions 124 6.4. Summary 133 7. Conclusion 135 8. References 139 Abstract in Korean 151Docto

    SiC ๊ฒฐ์ •์˜ ๊ณ ์† ์„ฑ์žฅ์„ ์œ„ํ•œ ๊ณ ์˜จํ™”ํ•™์ฆ์ฐฉ๋ฒ•์— ๋Œ€ํ•œ ์ „์‚ฐ๋ฌ˜์‚ฌ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์žฌ๋ฃŒ๊ณตํ•™๋ถ€, 2014. 2. ๊น€ํ˜•์ค€.ํƒ„ํ™”๊ทœ์†Œ(SiC)๋Š” ๊ด‘์—ญ ์—๋„ˆ์ง€ ๊ธˆ์ง€๋Œ€์—ญ์„ ๊ฐ€์ง€๋ฉฐ, ๋†’์€ ํŒŒ๊ดด ์ „์••, ํฌํ™” ์ด๋™ ์†๋„, ์ „์ž ์ด๋™๋„, ๋‚ด๋ฐฉ์‚ฌ์„ ํŠน์„ฑ ๋“ฑ์œผ๋กœ ์ธํ•ด ๊ธฐ์กด์˜ ์‹ค๋ฆฌ์ฝ˜(Si)์ด๋‚˜ ๊ฐˆ๋ฅจ๋น„์†Œ(GaAs) ๋“ฑ์˜ ๋ฐ˜๋„์ฒด๊ฐ€ ๊ทธ ์„ฑ๋Šฅ์„ ์ œ๋Œ€๋กœ ๋ฐœํœ˜ํ•  ์ˆ˜ ์—†๋Š” ๊ณ ์˜จ, ๊ณ ์ถœ๋ ฅ, ๊ณ ์ฃผํŒŒ์ˆ˜, ๊ณ ๋ฐ€๋„ ๋ฐฉ์‚ฌ์„  ๋‚ด์—์„œ์˜ ์‚ฌ์šฉ์ด ๊ธฐ๋Œ€๋˜๊ณ  ์žˆ๋Š” ๋Œ€ํ‘œ์ ์ธ ๊ด‘๋Œ€์—ญ ํ™”ํ•ฉ๋ฌผ ๋ฐ˜๋„์ฒด ๋ฌผ์งˆ์ด๋‹ค. ์šฐ์ˆ˜ํ•œ ๋ฌผ์„ฑ์„ ์ง€๋‹ˆ๋Š” ํƒ„ํ™”๊ทœ์†Œ๋Š” ๊ณ ์˜จ ๊ณ ์••์—์„œ์˜ ๋†’์€ ์•ˆ์ •์„ฑ์— ์˜ํ•ด์„œ ๊ธฐ์กด์˜ ์‹ค๋ฆฌ์ฝ˜์„ ๋Œ€์ฒดํ•˜๊ธฐ์—๋Š” ๋น„์šฉ์ ์ธ ์ธก๋ฉด์—์„œ ๋‹จ์ ์„ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ์ด๋ฅผ ๊ทน๋ณตํ•˜๊ธฐ ์œ„ํ•ด ํƒ„ํ™”๊ทœ์†Œ bulk ์„ฑ์žฅ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๊ฐ€ ํ™œ๋ฐœํžˆ ์ด๋ฃจ์–ด์ง€๊ณ  ์žˆ๋Š” ์‹ค์ •์ด๋‹ค. ํƒ„ํ™”๊ทœ์†Œ bulk ์„ฑ์žฅ ๋ฐฉ๋ฒ•๋“ค์€ SiC powder๋ฅผ source๋กœ ์‚ฌ์šฉํ•˜๊ธฐ ๋•Œ๋ฌธ์— powder์—์„œ ์˜ค๋Š” ๋ณธ์งˆ์ ์ธ ํ•œ๊ณ„์ ๋“ค์„ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ํ•˜์ง€๋งŒ ๊ณ ์˜จ์—์„œ gas precursor์˜ ์ง์ ‘์ ์ธ ์—ด๋ถ„ํ•ด๋ฅผ ์ด์šฉํ•˜์—ฌ SiC๋ฅผ ์ฆ์ฐฉํ•˜๋Š” ๋ฐฉ๋ฒ•์ธ HTCVD(high temperature chemical vapor deposition)์˜ ๊ฒฝ์šฐ ์ƒ๋Œ€์ ์œผ๋กœ ๋†’์€ ์„ฑ์žฅ ์†๋„๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. HTCVD ๋ฐฉ๋ฒ•์„ ์ด์šฉํ•œ SiC์˜ ์„ฑ์žฅ์ด ๋‹ค๋ฅธ ์ฆ์ฐฉ ๋ฐฉ๋ฒ•์— ๋น„ํ•ด์„œ ๋น ๋ฅธ ์ด์œ ๋Š” ํ‘์—ฐ์œผ๋กœ ๋งŒ๋“ค์–ด์ง„ ์ˆ˜์ง ์›ํ†ตํ˜• ๋ฐ˜์‘๊ธฐ์™€ source๋กœ gas precursor๋ฅผ ์‚ฌ์šฉํ•จ์—์„œ ์˜ค๋Š” ๋…ํŠนํ•œ ๋ฉ”์ปค๋‹ˆ์ฆ˜ ๋•Œ๋ฌธ์ด๋ฉฐ, ์ด ๋ฉ”์ปค๋‹ˆ์ฆ˜์— ๋Œ€ํ•œ ์ฃผ์žฅ์ด ์ œ๊ธฐ๋˜์–ด ์™”๋‹ค. ๋˜ํ•œ ๋ฌธํ—Œ์ƒ์—์„œ ์ฃผ์žฅ๋˜์–ด์˜จ ๋ฉ”์ปค๋‹ˆ์ฆ˜์—์„œ ์ฃผ์š” ๋ฐœ์ƒ๋˜๋Š” ๊ฑฐ๋™์€ ์˜จ๋„๊ตฌ๋ฐฐ, gas์˜ ๋†๋„๊ฐ€ ๋†’์€ ์ •์ฒด๊ตฌ๊ฐ„, ๊ทธ๋ฆฌ๊ณ  ๋‹ค๋Ÿ‰์˜ cluster์˜ ์ƒ์„ฑ์ด๋‹ค. ํ•œํŽธ, ๊ณ ์˜จ์—์„œ ์ด๋ฃจ์–ด์ง€๋Š” ํ™”ํ•™ ๋ฐ˜์‘์„ ์œ„ํ•ด ๋ถˆํˆฌ๋ช…ํ•œ ํ‘์—ฐ์œผ๋กœ ์ด๋ฃจ์–ด์ง„ ์ˆ˜์ง ์›ํ†ตํ˜• ๋ฐ˜์‘๊ธฐ ๋‚ด๋ถ€์—์„œ ์—ด์ , ๋ฌผ๋ฆฌ์ , ํ™”ํ•™์  ์•ˆ์ •์„ฑ์„ ์œ ์ง€ํ•˜๋ฉด์„œ ์ด๋Ÿฌํ•œ ์„ธ ๊ฐ€์ง€ ๊ฑฐ๋™(์˜จ๋„๊ตฌ๋ฐฐ, ์ •์ฒด๊ตฌ๊ฐ„, cluster์˜ ์ƒ์„ฑ)์„ ์ธก์ •ํ•  ์ˆ˜ ์žˆ๋Š” In-situ measurement์žฅ๋น„๊ฐ€ ์—†๋Š” ์‹ค์ •์ด๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์œ„ ์„ธ ๊ฐ€์ง€ ๊ฑฐ๋™์˜ ๋ฐœ์ƒ ์—ฌ๋ถ€๋ฅผ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ํ†ตํ•ด์„œ ๊ด€์ฐฐํ•˜์—ฌ ๋ฌธํ—Œ์ƒ์˜ ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ๊ทœ๋ช…ํ•˜๊ณ  ์—ฌ๋Ÿฌ ๊ฐ€์ง€ ๋ณ€์ˆ˜๋“ค์„ ์ด์šฉํ•˜์—ฌ ์„ธ ๊ฐ€์ง€ ๊ฑฐ๋™์˜ ๋ณ€ํ™” ์ถ”์ด๋ฅผ ๋ณด๊ณ ์ž ํ•˜์˜€๋‹ค. ์ œ์ž‘ํ•œ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๋ชจ๋ธ์€ ํฌ๊ฒŒ ๋‘ ๊ฐ€์ง€๋กœ ํ•˜๋‚˜๋Š” ํ™”ํ•™์  ๊ฑฐ๋™์„ ์ง‘์ค‘์ ์œผ๋กœ ์‚ดํŽด๋ณด๊ธฐ ์œ„ํ•ด ๋ฐ˜์‘๊ธฐ ๋‚ด๋ถ€๋งŒ์˜ ๊ทธ๋ฆฌ๋“œ๋ฅผ ์ ์šฉํ•˜์—ฌ simulation scaling down์„ ์ ์šฉํ•œ ๋ชจ๋ธ๊ณผ ๋‚˜๋จธ์ง€ ํ•˜๋‚˜๋Š” ์‹ค์ œ ๊ณต์ •๊ณผ ์œ ์‚ฌํ•œ ํ™˜๊ฒฝ์˜ ๋ณต์žกํ•œ ๊ทธ๋ฆฌ๋“œ๋ฅผ ์ ์šฉํ•˜๊ณ  ์ด์— ์ถ”๊ฐ€์ ์œผ๋กœ inductive heating๊ณผ radiation๋“ฑ์„ ๊ณ ๋ คํ•œ ๋ชจ๋ธ์ด๋‹ค. ํ™”ํ•™์  ๊ฑฐ๋™์„ ๊ณ ๋ คํ•œ ๋ชจ๋ธ์„ ์ด์šฉํ•˜์—ฌ ๋ฌธํ—Œ์ƒ์—์„œ ์ œ์‹œํ•˜์˜€๋˜ cluster๊ฐ€ ๋ฐœ์ƒ๋˜๋Š” ์˜จ๋„๊ตฌ๊ฐ„์ธ(1300K-2400K)์—์„œ์˜ ํ™”ํ•™์  ๊ฑฐ๋™์„ ์‚ดํŽด๋ณด์•˜๋‹ค. ํŠนํžˆ ์œ ์ž…๊ตฌ๋ฅผ ํ†ตํ•ด์„œ ๋„ฃ์–ด์ฃผ์—ˆ๋˜ gas๋“ค์ด ๋ฐ˜์‘๊ธฐ์˜ ์œ„์ชฝ์œผ๋กœ ์ด๋™ํ•จ์— ๋”ฐ๋ผ ์†Œ๋ชจ๋˜๋ฉด์„œ ์ค‘๊ฐ„์ƒ์„ฑ๋ฌผ๋“ค์ด ๋ฐœ์ƒํ•˜๋Š” ๊ฒƒ์„ ํ™•์ธ ํ•˜์˜€๋‹ค. ์ด ์ค‘๊ฐ„ ์ƒ์„ฑ๋ฌผ๋“ค์€ ๊ธฐํŒ์—์„œ์˜ ํ‘œ๋ฉด๋ฐ˜์‘์— ์˜ํ•ด์„œ ์†Œ๋ชจ๊ฐ€ ๋œ๋‹ค. ๋˜ํ•œ, ์ด ์ค‘๊ฐ„ ์ƒ์„ฑ๋ฌผ๋“ค์˜ fraction์„ ๋น„๊ตํ•˜์˜€์„ ๋•Œ Si์˜ fraction์ด ๋‹ค๋ฅธ ์ค‘๊ฐ„ ์ƒ์„ฑ๋ฌผ๋“ค์— ๋น„ํ•ด ์•ฝ 10000๋ฐฐ ๊ฐ€๋Ÿ‰ ์›”๋“ฑํžˆ ์ปธ์œผ๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด์„œ ์ค‘๊ฐ„ ์ƒ์„ฑ๋ฌผ์ธ Si์ด ๋ฐ˜์‘์— ๊ธฐ์—ฌํ•˜๋Š” ์ •๋„๊ฐ€ ๋‹ค๋ฅธ ์ค‘๊ฐ„ ์ƒ์„ฑ๋ฌผ๋“ค์— ์›”๋“ฑํžˆ ํด ๊ฒƒ์œผ๋กœ ํŒ๋‹จํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋”ฐ๋ผ์„œ ๋‹ค์Œ์˜ ์‹คํ—˜์€ ๋‹ค๋ฅธ ์ค‘๊ฐ„ ์ƒ์„ฑ๋ฌผ๋“ค์˜ ์ƒ์„ฑ๋Ÿ‰์„ ๋ณ€ํ™”์‹œํ‚ค๋Š” ๊ฒƒ๋ณด๋‹ค Si์˜ ์ƒ์„ฑ๋Ÿ‰์„ ๋ณ€ํ™”์‹œ์ผœ๋ณด๋Š” ๊ฒƒ์ด ๋” ํšจ๊ณผ์ ์ผ ๊ฒƒ์ด๋ผ๋Š” ํŒ๋‹จ์„ ๋‚ด๋ฆด ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์‹ค์ œ ๊ณต์ •๊ณผ ์œ ์‚ฌํ•œ ํ™˜๊ฒฝ์˜ ๋ณต์žกํ•œ ๊ทธ๋ฆฌ๋“œ๋ฅผ ์ ์šฉํ•˜๊ณ  ์ด์— ์ถ”๊ฐ€์ ์œผ๋กœ inductive heating๊ณผ radiation์„ ๊ณ ๋ คํ•œ ๋ชจ๋ธ์„ ์ด์šฉํ•˜์—ฌ์„œ ์œ ์ž…ํ•˜์—ฌ ์ฃผ๋Š” source gas๋“ค, ์ฆ‰ precursor๋“ค์˜ ์–‘์— ๋”ฐ๋ผ ์˜จ๋„๊ตฌ๋ฐฐ, ์ •์ฒด๊ตฌ๊ฐ„, cluster์˜ ์ƒ์„ฑ์˜ ๋ณ€ํ™” ์ถ”์ด๋ฅผ ์‚ดํŽด๋ณด์•˜๋‹ค. Silane(SiH4) gas์˜ ์–‘์„ ๋ณ€ํ™”์‹œํ‚ค๊ธฐ์— ์•ž์„œ ์ตœ์ ์˜ deposition rate์„ ๊ฐ€์ง€๋Š” propane(C3H8)์˜ ์œ ๋Ÿ‰์„ ํŒŒ์•…ํ•˜๊ธฐ ์œ„ํ•ด์„œ ์ˆ˜์†Œ(H2) gas์˜ ์–‘์„ 6000 sccm, silane gas์˜ ์–‘์„ 150 sccm์œผ๋กœ ๊ณ ์ •ํ•˜๊ณ  propane gas์˜ ์œ ๋Ÿ‰์„ ๊ฐ๊ฐ 20 sccm, 24 sccm, 28 sccm, 32 sccm ์”ฉ ๋Š˜๋ ค์„œ ์‹คํ—˜์„ ์ง„ํ–‰ ํ•˜์˜€๋‹ค. propane์„ 20 sccm์„ ๋„ฃ์–ด์ค€ ๊ฒƒ์ด cluster์˜ ์ƒ์„ฑ์ด ๊ฐ€์žฅ ๋งŽ์€ ๊ฒƒ์œผ๋กœ ํ™•์ธ๋˜์—ˆ๊ธฐ ๋•Œ๋ฌธ์— Si-source์ธ silane gas์˜ ์˜ํ–ฅ์„ ์‚ดํŽด๋ณด๋Š” ์‹คํ—˜์—์„œ๋Š” propane์„ 20 sccm์œผ๋กœ ๊ณ ์ •ํ•˜๊ณ  ์ง„ํ–‰ํ•˜์˜€๋‹ค. ๋งˆ์ฐฌ๊ฐ€์ง€๋กœ ์ˆ˜์†Œ gas์˜ ์–‘์„ 6000 sccm, propane gas์˜ ์–‘์„ 20 sccm ์œผ๋กœ ๊ณ ์ •ํ•˜๊ณ  silane gas์˜ ์–‘์„ ๊ฐ๊ฐ 150 sccm, 180 sccm, 210 sccm, 240 sccm ์”ฉ ๋Š˜๋ ค์„œ ์‹คํ—˜์„ ์ง„ํ–‰ ํ•˜์˜€๋‹ค. Silane gas์˜ ์–‘์„ 240 sccm ๋„ฃ์–ด ์ฃผ์—ˆ์„ ๊ฒฝ์šฐ cluster์˜ ์ƒ์„ฑ์ด ๊ฐ€์žฅ ๋งŽ์€ ๊ฒƒ์œผ๋กœ ํ™•์ธ ๋˜์—ˆ๋‹ค. ๋˜ํ•œ ์œ„ ์‹คํ—˜์„ ํ†ตํ•˜์—ฌ ์ˆ˜์ง ์›ํ†ตํ˜• ๋ฐ˜์‘๊ธฐ์˜ ๋†’์ด ๋ฐฉํ–ฅ์œผ๋กœ ์˜ฌ๋ผ๊ฐˆ์ˆ˜๋ก ์˜จ๋„๊ฐ€ ์ฆ๊ฐ€ํ•˜๋‹ค๊ฐ€ ๊ฐ์†Œํ•˜๋Š” ์˜จ๋„๊ตฌ๋ฐฐ, velocity magnitude๊ฐ€ ์ฆ๊ฐ€ํ•˜๋‹ค๊ฐ€ ๊ฐ์†Œํ•˜๋Š” ๊ฒƒ์œผ๋กœ ์ •์ฒด๊ตฌ๊ฐ„์ด ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ํ†ตํ•ด ๊ตฌํ˜„๋˜๋Š” ๊ฒƒ์„ ํ™•์ธ ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๊ตฌ๋ฆฌ ์ฝ”์ผ์— ์˜ํ•œ ํ‘์—ฐ ๋ฐ˜์‘๊ธฐ์˜ inductive heating์„ ์‚ฌ์šฉํ•˜๊ธฐ ๋•Œ๋ฌธ์— ๋ฐ˜์‘๊ธฐ ์ž์ฒด๊ฐ€ ๊ณต์ •์ƒ์—์„œ heat source๋กœ ์ž‘์šฉํ•˜๊ฒŒ ๋œ๋‹ค. ๋”ฐ๋ผ์„œ ๊ณต์ • ์˜จ๋„๋ฅผ ์ฆ๊ฐ€์‹œํ‚ค๊ธฐ ์œ„ํ•˜์—ฌ ์œ„์™€ ๊ฐ™์€ ๋ชจ๋ธ์„ ์‚ฌ์šฉํ•˜๊ณ  ๋ฐ˜์‘๊ธฐ์˜ ๊ธธ์ด๋ฅผ 5 %, 10 % ๋Š˜๋ ค์„œ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ๋ฐ˜์‘๊ธฐ์˜ ๊ธธ์ด๋ฅผ ๋Š˜์ผ์ˆ˜๋ก ์ „์ฒด์ ์ธ ์˜จ๋„๊ฐ€ ์ฆ๊ฐ€ํ•จ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๊ณ , velocity magnitude๋„ ์—ญ์‹œ ์ „์ฒด์ ์œผ๋กœ ์ฆ๊ฐ€ ํ•˜๊ฒŒ ๋œ๋‹ค. ์ƒ์„ฑ๋˜๋Š” cluster์˜ ์–‘์ด ์˜จ๋„๊ฐ€ ์ฆ๊ฐ€ํ•จ์— ๋”ฐ๋ผ์„œ ๋งŽ์ด ์ƒ์„ฑ๋˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋Š”๋ฐ condensed phase๋กœ ๊ฐ€๋ ค๊ณ  ํ•˜๋Š” driving force์˜ ์ •๋„๋ฅผ ๋‚˜ํƒ€๋‚ด๋Š” super saturation์ด ๋œ ์ •๋„์™€ ์ฆ์ฐฉ ์†๋„๋ฅผ ๋น„๊ต๋ฅผ ํ•˜์˜€์„ ๋•Œ, super saturation์ด ๋œ ์ •๋„๊ฐ€ ์ฆ๊ฐ€ํ• ์ˆ˜๋ก Si์˜ ์ฆ์ฐฉ ์†๋„๊ฐ€ ์ปค์ง€๋Š” ๊ฒƒ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ด๋ฅผ ํ†ตํ•ด ์ƒ์„ฑ๋˜๋Š” silicon์€ liquid ์ƒํƒœ์˜ silicon cluster์ด๋ฉฐ ์ด silicon cluster์˜ ์–‘์ด ๋งŽ์•„์งˆ์ˆ˜๋ก deposition rate์ด ์ฆ๊ฐ€ํ•œ๋‹ค๋Š” ๊ฒฐ๋ก ์„ ๋‚ด๋ฆด ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋˜ํ•œ ๋„ฃ์–ด์ฃผ๋Š” silicon source gas์˜ ๋†๋„๋ฅผ ์ฆ๊ฐ€์‹œํ‚ค๊ณ , carrier gas์˜ ์–‘์„ ๊ฐ์†Œ์‹œํ‚ค๋ฉฐ, ๋ฐ˜์‘๊ธฐ์˜ ๊ธธ์ด๋ฅผ ๋Š˜์—ฌ์ค„์ˆ˜๋ก silicon cluster์˜ ์–‘์ด ์ฆ๊ฐ€ํ•œ๋‹ค๋Š” ๊ฒฐ๋ก ์„ ๋‚ด๋ฆด ์ˆ˜ ์žˆ์—ˆ๋‹ค.์ดˆ๋ก ๋ชฉ์ฐจ List of Figures 1. ์„œ ๋ก  2. ๋ฌธํ—Œ์—ฐ๊ตฌ 2.1. ํƒ„ํ™”๊ทœ์†Œ์˜ ๊ตฌ์กฐ์™€ ๋ฌผ์„ฑ 2.1.1. ๊ตฌ์กฐ 2.1.2. ๋ฌผ์„ฑ 2.2. ์—ฐ๊ตฌ์˜ ๋ชฉ์  2.2.1. SiC bulk ์„ฑ์žฅ๋ฐฉ๋ฒ•๋“ค์˜ ํŠน์ง•๊ณผ ํ•œ๊ณ„์  2.2.1.1. Growth from melt 2.2.1.2. Lely growth 2.2.1.3. Seeded sublimation growth 2.3. High temperature chemical vapor deposition(HTCVD) 2.3.1. HTCVD์˜ ํŠน์ง• 2.3.1.1. ๋ฐ˜์‘๊ธฐ์˜ ํ˜•์ƒ ๋ฐ ํŠน์ง• 2.3.1.2. Precursor ๋ฐ carrier gas 2.3.2. HTCVD ๋ฉ”์ปค๋‹ˆ์ฆ˜์— ๊ด€ํ•œ ์—ฐ๊ตฌ 2.3.2.1. ๋น ๋ฅธ SiC ์„ฑ์žฅ์˜ ๋ฉ”์ปค๋‹ˆ์ฆ˜ 2.3.2.2. ๋ฉ”์ปค๋‹ˆ์ฆ˜ ์ƒ์˜ ์„ธ ๊ฐ€์ง€ ๊ฑฐ๋™ ๋ฐ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์˜ ํ•„์š”์„ฑ 2.3.3. Si liquid cluster indicating factors 2.3.3.1. Super saturation 2.4. Simulation 2.4.1. Simulator์˜ ํŠน์ง•๊ณผ ํ•œ๊ณ„์  2.4.2. Residual์˜ ์ •์˜์™€ Iterations 3. ์‹คํ—˜ ๋ฐฉ๋ฒ• 3.1. ํ™”ํ•™์  ๊ฑฐ๋™์„ ๊ณ ๋ คํ•œ ๋ชจ๋ธ 3.1.1. ๊ทธ๋ฆฌ๋“œ ํ˜•์ƒ 3.1.2. ์‹คํ—˜ ์กฐ๊ฑด ๋ฐ ๊ฐ€์ • 3.2. Inductive heating๊ณผ radiation์„ ์ถ”๊ฐ€์ ์œผ๋กœ ๊ณ ๋ คํ•œ ๋ณต์žกํ•œ ๋ชจ๋ธ 3.2.1. ๊ทธ๋ฆฌ๋“œ ํ˜•์ƒ 3.2.2. ์‹คํ—˜ ์กฐ๊ฑด ๋ฐ ๊ฐ€์ • 4. ์‹คํ—˜ ๊ฒฐ๊ณผ ๋ฐ ํ† ์˜ 4.1. ํ™”ํ•™์  ๊ฑฐ๋™์„ ๊ณ ๋ คํ•œ ๋ชจ๋ธ์˜ ๋ถ„์„ 4.1.1. ํ‘œ๋ฉด ๋ฐ˜์‘์„ ๊ณ ๋ คํ•˜์˜€์„ ๋•Œ์˜ ํ™”ํ•™์  ๊ฑฐ๋™ ์—ฐ๊ตฌ 4.1.2. ํ‘œ๋ฉด ๋ฐ˜์‘์„ ๊ณ ๋ คํ•˜์ง€ ์•Š์•˜์„ ๋•Œ์˜ Si์˜ ํ™”ํ•™์  ๊ฑฐ๋™ ์—ฐ๊ตฌ 4.1.3. ์†Œ๊ฒฐ๋ก  4.2. Inductive heating๊ณผ radiation์„ ์ถ”๊ฐ€์ ์œผ๋กœ ๊ณ ๋ คํ•œ ๋ณต์žกํ•œ ๋ชจ๋ธ์˜ ๋ถ„์„ 4.2.1. Propane gas์˜ ์œ ๋Ÿ‰์— ๋”ฐ๋ฅธ ๊ฑฐ๋™ ์—ฐ๊ตฌ 4.2.1.1. ์˜จ๋„๊ตฌ๋ฐฐ์˜ ํ˜•์„ฑ ๋ฐ ๋ณ€ํ™” ๊ฑฐ๋™ 4.2.1.2. ์ •์ฒด๊ตฌ๊ฐ„์˜ ํ˜•์„ฑ ๋ฐ ๋ณ€ํ™” ๊ฑฐ๋™ 4.2.1.3. Si cluster์˜ ํ˜•์„ฑ ๋ฐ ๋ณ€ํ™” ๊ฑฐ๋™ 4.2.2. Silane gas์˜ ์œ ๋Ÿ‰์— ๋”ฐ๋ฅธ ๊ฑฐ๋™ ์—ฐ๊ตฌ 4.2.2.1. ์˜จ๋„๊ตฌ๋ฐฐ์˜ ํ˜•์„ฑ ๋ฐ ๋ณ€ํ™” ๊ฑฐ๋™ 4.2.2.2. ์ •์ฒด๊ตฌ๊ฐ„์˜ ํ˜•์„ฑ ๋ฐ ๋ณ€ํ™” ๊ฑฐ๋™ 4.2.2.3. Si cluster์˜ ํ˜•์„ฑ ๋ฐ ๋ณ€ํ™” ๊ฑฐ๋™ 4.2.3. Carrier gas์˜ ์œ ๋Ÿ‰์— ๋”ฐ๋ฅธ ๊ฑฐ๋™ ์—ฐ๊ตฌ 4.2.3.1. ์˜จ๋„๊ตฌ๋ฐฐ์˜ ํ˜•์„ฑ ๋ฐ ๋ณ€ํ™” ๊ฑฐ๋™ 4.2.3.2. ์ •์ฒด๊ตฌ๊ฐ„์˜ ํ˜•์„ฑ ๋ฐ ๋ณ€ํ™” ๊ฑฐ๋™ 4.2.3.3. Si cluster์˜ ํ˜•์„ฑ ๋ฐ ๋ณ€ํ™” ๊ฑฐ๋™ 4.2.4. ๋ฐ˜์‘๊ธฐ์˜ ๊ธธ์ด์— ๋”ฐ๋ฅธ ๊ฑฐ๋™ ์—ฐ๊ตฌ 4.2.4.1. ์˜จ๋„๊ตฌ๋ฐฐ์˜ ํ˜•์„ฑ ๋ฐ ๋ณ€ํ™” ๊ฑฐ๋™ 4.2.4.2. ์ •์ฒด๊ตฌ๊ฐ„์˜ ํ˜•์„ฑ ๋ฐ ๋ณ€ํ™” ๊ฑฐ๋™ 4.2.4.3. Si cluster์˜ ํ˜•์„ฑ ๋ฐ ๋ณ€ํ™” ๊ฑฐ๋™ 4.2.5. ์†Œ๊ฒฐ๋ก  5. ๊ฒฐ ๋ก  6. ์ฐธ๊ณ  ๋ฌธํ—Œ AbstractMaste

    Out-of-pocket health expenditures by adults and elderly persons in Korea

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    ๋ณด๊ฑดํ•™๊ณผ/์„์‚ฌ[ํ•œ๊ธ€] ์˜๋ฃŒ๋ณดํ—˜์˜ ๋ณด์žฅ๋ฒ”์œ„์—์„œ ์ œ์™ธ๋œ ์„œ๋น„์Šค ์˜์—ญ์— ๋Œ€ํ•˜์—ฌ ์˜๋ฃŒ์ด์šฉ์ž๊ฐ€ ์ง€๋ถˆํ•˜๋Š” ๊ฐœ์ธ๋ถ€๋‹ด ์˜๋ฃŒ๋น„์šฉ์€ ๊ทธ ๋ถ€๋‹ด์ •๋„์— ๋”ฐ๋ผ ์˜๋ฃŒ์˜ ์ ‘๊ทผ์„ฑ๊ณผ ๊ฑด๊ฐ•์ƒํƒœ, ์‚ถ์ด ์งˆ์— ์˜ํ–ฅ์„ ๋ฏธ์น  ์ˆ˜ ์žˆ์œผ๋‚˜, ์ด๋Ÿฌํ•œ ๋น„์šฉ์— ๋Œ€ํ•œ ์‹ค์ฆ์ ์ธ ์ž๋ฃŒ์— ๊ธฐ์ดˆํ•œ ์—ฐ๊ตฌ๊ฐ€ ๋ถ€์กฑํ•œ ์‹ค์ •์ด๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” 20์„ธ ์ด์ƒ ์šฐ๋ฆฌ๋‚˜๋ผ ์„ฑ์ธ์˜ ๊ฐœ์ธ๋ถ€๋‹ด ์˜๋ฃŒ๋น„์šฉ์˜ ๊ทœ๋ชจ์™€ ์ด์— ๋Œ€ํ•œ ๊ด€๋ จ์š”์ธ์„ ํŒŒ์•…ํ•˜๋Š”๋ฐ ๊ทธ ๋ชฉ์ ์ด ์žˆ์œผ๋ฉฐ, ์ด๋ฅผ ์œ„ํ•ด 2001๋…„๋„ โ€˜๊ตญ๋ฏผ๊ฑด๊ฐ•ใ†์˜์–‘์กฐ์‚ฌโ€™ ์ž๋ฃŒ๋ฅผ ์ด์šฉํ•˜์˜€๋‹ค. 20์„ธ ์ด์ƒ 26,154๋ช…์„ ๋ถ„์„๋Œ€์ƒ์œผ๋กœ 65์„ธ ๋ฏธ๋งŒ๊ณผ ์ด์ƒ์œผ๋กœ ๊ตฌ๋ถ„ํ•˜์˜€์œผ๋ฉฐ, ์ด ๊ฐœ์ธ๋ถ€๋‹ด ์˜๋ฃŒ๋น„๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์ž…์›๊ณผ ์™ธ๋ž˜์˜ ๋ณธ์ธ๋ถ€๋‹ด ๋น„์šฉ์œผ๋กœ ๊ฐ๊ฐ ๋‚˜๋ˆ„์–ด ๋ถ„์„ํ•˜์˜€๊ณ , ์‚ฌํšŒ์ธ๊ตฌํ•™์  ๋ณ€์ˆ˜์™€ ๊ฑด๊ฐ•๊ด€๋ จ ๋ณ€์ˆ˜๋ฅผ ๋…๋ฆฝ๋ณ€์ˆ˜๋กœ ๊ฐœ์ธ๋ถ€๋‹ด ์˜๋ฃŒ๋น„๋ฅผ ์ž์—ฐ๋กœ๊ทธ ๋ณ€ํ™˜ํ•˜์—ฌ ํšŒ๊ท€๋ถ„์„ ํ•˜์˜€๋‹ค. ์ด ์—ฐ๊ตฌ์˜ ์ฃผ์š” ๊ฒฐ๊ณผ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ์ฒซ์งธ, 65์„ธ๋ฏธ๋งŒ ์„ฑ์ธ์˜ ๊ฐœ์ธ๋ถ€๋‹ด ์˜๋ฃŒ๋น„์šฉ์€ ์›” ํ‰๊ท  14,800์›, 65์„ธ ์ด์ƒ ๋…ธ์ธ์˜ ๊ฐœ์ธ๋ถ€๋‹ด ์˜๋ฃŒ๋น„์šฉ์€ ์›” ํ‰๊ท  27,200์›์œผ๋กœ ๋…ธ์ธ์ด ํ†ต๊ณ„ํ•™์ ์œผ๋กœ ์œ ์˜ํ•˜๊ฒŒ ๋†’์•˜์œผ๋ฉฐ, ๋ณธ์ธ๋ถ€๋‹ด ์ž…์›๋น„์šฉ๊ณผ ์™ธ๋ž˜๋น„์šฉ์—์„œ๋„ ์„ฑ์ธ๊ณผ ๋น„๊ตํ•˜์—ฌ ๋…ธ์ธ์˜ ๋น„์šฉ ์ˆ˜์ค€์ด ํ†ต๊ณ„ํ•™์ ์œผ๋กœ ์œ ์˜ํ•˜๊ฒŒ ๋†’์•˜๋‹ค. ๋‘˜์งธ, ์˜๋ฃŒ๋ณด์žฅํ˜•ํƒœ, ๊ฑฐ์ฃผ์ง€์—ญ, ์ฃผ๊ด€์  ๊ฑด๊ฐ•์ƒํƒœ, ํ™œ๋™์ œํ•œ ์ผ์ˆ˜, ์นจ์ƒ์™€๋ณ‘ ์ผ์ˆ˜, ๊ธ‰ใ†๋งŒ์„ฑ์งˆํ™˜์˜ ์ข…๋ฅ˜๊ฐ€ ์„ฑ์ธ๊ณผ ๋…ธ์ธ ๋ชจ๋‘์—์„œ ๊ฐœ์ธ๋ถ€๋‹ด ์˜๋ฃŒ๋น„ ๋ฐ ๋ณธ์ธ๋ถ€๋‹ด ์ž…์›๋น„์šฉ, ๋ณธ์ธ๋ถ€๋‹ด ์™ธ๋ž˜๋น„์šฉ๊ณผ ํ†ต๊ณ„ํ•™์ ์œผ๋กœ ์œ ์˜ํ•œ ๊ด€๋ จ์„ฑ์ด ์žˆ์—ˆ๋‹ค. ์…‹์งธ, ์—ฐ๋ น๊ณผ ์„ฑ์€ ์„ฑ์ธ์—์„œ๋งŒ ๊ฐœ์ธ๋ถ€๋‹ด ์˜๋ฃŒ๋น„์šฉ๊ณผ ํ†ต๊ณ„ํ•™์ ์œผ๋กœ ์œ ์˜ํ•œ ๊ด€๋ จ์„ฑ์ด ์žˆ์—ˆ๋‹ค. ๋„ท์งธ, ์„ฑ์ธ์˜ ๋ณธ์ธ๋ถ€๋‹ด ์ž…์›๋น„์šฉ์€ ์—ฌ์ž๊ฐ€ ํ†ต๊ณ„ํ•™์ ์œผ๋กœ ์œ ์˜ํ•˜๊ฒŒ ๋‚ฎ์•˜์œผ๋‚˜, ๋ณธ์ธ๋ถ€๋‹ด ์™ธ๋ž˜๋น„์šฉ์€ ์—ฌ์ž๊ฐ€ ํ†ต๊ณ„ํ•™์ ์œผ๋กœ ์œ ์˜ํ•˜๊ฒŒ ๋†’์•˜๋‹ค. ๋‹ค์„ฏ์งธ, ์„ฑ์ธ์—์„œ ์—ฐ๋ น์€ ๋ณธ์ธ๋ถ€๋‹ด ์™ธ๋ž˜๋น„์šฉ๊ณผ ํ†ต๊ณ„ํ•™์ ์œผ๋กœ ์œ ์˜ํ•œ ๊ด€๋ จ์„ฑ์ด ์žˆ์—ˆ๋‹ค. ์—ฌ์„ฏ์งธ, ๋…ธ์ธ์—์„œ ์›” ๊ฐ€๊ตฌ์†Œ๋“๊ณผ ๋™๊ฑฐ ๊ฐ€๊ตฌ์›์ˆ˜๋Š” ๋ณธ์ธ๋ถ€๋‹ด ์™ธ๋ž˜๋น„์šฉ๊ณผ ํ†ต๊ณ„ํ•™์ ์œผ๋กœ ์œ ์˜ํ•œ ๊ด€๋ จ์„ฑ์ด ์žˆ์—ˆ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ์ผ๋ฐ˜์ธ๊ตฌ ์ง‘๋‹จ์˜ ์˜๋ฃŒ์— ๋Œ€ํ•œ ๊ฐœ์ธ๋ณ„ ๊ฒฝ์ œ์  ๋ถ€๋‹ด์ˆ˜์ค€ ๋ฐ ๊ด€๋ จ์š”์ธ์„ ์‚ดํŽด๋ณธ ๊ฒƒ์— ์˜์˜๊ฐ€ ์žˆ์œผ๋ฉฐ, ์ด์™€ ๊ด€๋ จํ•œ ํ–ฅํ›„ ๊ตญ๊ฐ€์˜ ์˜๋ฃŒ์ •์ฑ… ์ˆ˜๋ฆฝ ๋“ฑ์— ์žˆ์–ด์„œ ๋…ธ์ธ๊ณผ ์„ฑ์ธ์„ ๊ตฌ๋ถ„ํ•  ํ•„์š”์„ฑ์ด ์žˆ์Œ์„ ๋ณด์—ฌ์ฃผ์—ˆ๋‹ค. ๋”ฐ๋ผ์„œ ๊ฐœ์ธ๋ถ€๋‹ด ์˜๋ฃŒ๋น„์šฉ์ด ๋…ธ์ธ๋“ค์˜ ๋ณด๊ฑด์˜๋ฃŒ์ด์šฉ์— ์–ด๋–ค ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š”์ง€์— ๋Œ€ํ•œ ์ถ”๊ฐ€์ ์ธ ์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•˜๋ฉฐ, ์ฃผ์š” ์งˆํ™˜๋ณ„๋กœ ์–ด๋–ค ์งˆํ™˜์˜ ๊ฐœ์ธ๋ถ€๋‹ด๋น„์šฉ์ด ๋†’์€์ง€ ํŒŒ์•…ํ•  ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ๋˜ํ•œ ๊ฐœ์ธ๋ถ€๋‹ด ์˜๋ฃŒ๋น„์šฉ์œผ๋กœ ์ธํ•ด ํ•„์š”ํ•œ ์˜๋ฃŒ์„œ๋น„์Šค๋ฅผ ์ง€์—ฐ์‹œํ‚ค๊ฑฐ๋‚˜ ํฌ๊ธฐํ•˜๋Š” ์ผ์ด ์—†๋„๋ก ๋ณดํ—˜์˜ ๋ณด์žฅ์„ฑ์„ ๊ฐ•ํ™”ํ•˜๊ณ  ๋ณดํ—˜๊ธ‰์—ฌ์˜ ๋‚ด์‹ค์„ ๊ธฐํ•  ํ•„์š”๊ฐ€ ์žˆ์œผ๋ฉฐ, ์ด๋ฅผ ํ†ตํ•ด ์˜๋ฃŒ์ด์šฉ์ž์˜ ๊ฑด๊ฐ•๊ณผ ์‚ถ์˜ ์งˆ ํ–ฅ์ƒ์— ๊ธฐ์—ฌํ•  ๊ฒƒ์œผ๋กœ ์ƒ๊ฐ๋œ๋‹ค. [์˜๋ฌธ]Out-of-pocket health expenditures defined as the charges for services not covered by health insurance have been shown to impede access to care and affect health status and quality of life. However, studies based on comprehensive national estimates of out-of-pocket health spending by the general population are scarce. Data from the 2001 National Public Health and Nutrition Survey were used to determine the impact of socioeconomic and health characteristics on out-of-pocket health spending for individuals age 20 and older in Korea. The final sample size for this analysis was 26,154 persons. Two separate multiple linear regression models were used by age group, that is, one for those under age sixty-five and the other for those age sixty-five and older. In these analyses, expenditures were divided into out-of-pocket spending for inpatient and outpatient services and transformed to a logarithmic scale to reduce skewness. The principle findings are as follows. 1. Out-of-pocket health expenditures for those under age 65 averaged 14,800 won per month, whereas expenditures for those age 65 and older averaged 27,200 won per month. In the bivariate analyses, elderly persons spent more than the non-elderly on health services. This result was statistically significant. 2. In the regression analysis, insurance type, resident area, self-reported health status, acute or chronic condition, activity-limited day, lying day in a sickbed were statistically significant determinants for both age groups. 3. Gender and age were statistically significant determinants only for the non-elderly. 4. Compared with non-elderly men, women had lower expenditures on inpatient services, whereas non-elderly women had higher expenditures on outpatient services. These results were statistically significant. 5. For the non-elderly, age had positive and statistically significant impacts on outpatient expenditures. 6. For the elderly, household income and family size had statistically significant impacts on outpatient expenditures. Findings from this study show that mean out-of-pocket health expenditures were high for the elderly. The level of this spending also varied by diverse characteristics. Thus, policymakers should consider out-of-pocket health expenditure differentials between elderly and non-elderly persons. In addition, further research is necessary to assess the impact of high out-of-pocket spending on health care utilization for the elderly. It is necessary to identify which disease is most likely to generate large out-of-pocket spending. Finally, improvement of insurance coverage for the subgroups identified in this study as vulnerable needs to be carefully considered.ope

    Improvement in Cycle Life of LiNi0.5Mn1.5O4 Positive Electrode for Lithium-Ion Secondary Batteries by Employing Quercetin as an Electrolyte Additive at Elevated Temperature

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ํ™”ํ•™์ƒ๋ฌผ๊ณตํ•™๋ถ€, 2016. 2. ๊น€์žฌ์ •.๋ฆฌํŠฌ ์ด์˜จ์ „์ง€๋Š” ๋†’์€ ์—๋„ˆ์ง€ ๋ฐ€๋„, ๊ฐ€๋ฒผ์šด ํŠน์„ฑ์„ ๋ฐ”ํƒ•์œผ๋กœ ๋น ๋ฅด๊ฒŒ ์‹œ์žฅ์— ๋ณด๊ธ‰๋˜์—ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜, ์ง€์†์ ์œผ๋กœ ์ฆ๊ฐ€ํ•˜๋Š” ์—๋„ˆ์ง€ ์ˆ˜์š”๋ฅผ ๋งž์ถ”๊ธฐ ์œ„ํ•ด ๋‹จ์œ„ ์ค‘๋Ÿ‰๋‹น ๋˜๋Š” ๋‹จ์œ„ ๋ถ€ํ”ผ๋‹น ์—๋„ˆ์ง€ ๋ฐ€๋„๋ฅผ ๋”์šฑ ๋†’์ด๋Š” ์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•œ ์‹ค์ •์ด๋‹ค. ์ „์ง€์˜ ์—๋„ˆ์ง€ ๋ฐ€๋„๋Š” ์ „์ง€์˜ ํ‰๊ท  ์ž‘๋™ ์ „์•• * ์šฉ๋Ÿ‰์œผ๋กœ ์ฃผ์–ด์ง€๋ฉฐ, ๋†’์€ ์ „์••์—์„œ ์ž‘๋™ํ•˜๋Š” ์ „๊ทน ๋ฌผ์งˆ์„ ์ง€์†์ ์œผ๋กœ ์—ฐ๊ตฌํ•จ์œผ๋กœ์จ ์ „์ง€์˜ ์ž‘๋™ ํ‰๊ท  ์ „์••์„ ๋†’์ด๋Š” ๋ฐฉํ–ฅ์œผ๋กœ ์—ฐ๊ตฌ๊ฐ€ ๋งŽ์ด ์ง„ํ–‰๋˜๊ณ  ์žˆ๋‹ค. ์ „์ง€์˜ ์ž‘๋™ ํ‰๊ท  ์ „์••์€ ์–‘๊ทน์˜ ํ‰๊ท  ์ž‘๋™ ์ „์•• โ€“ ์Œ๊ทน์˜ ํ‰๊ท  ์ž‘๋™ ์ „์••์œผ๋กœ ์“ธ ์ˆ˜ ์žˆ๋‹ค. ์ผ๋ฐ˜์ ์ธ ์Œ๊ทน์˜ ๊ฒฝ์šฐ ์ด๋ฏธ ๋ฆฌํŠฌ ์ „๊ทน์„ ๊ธฐ์ค€์œผ๋กœ 0 V ์ˆ˜์ค€์ด๊ธฐ ๋•Œ๋ฌธ์—, ๋”์šฑ ๋‚ฎ์ถ”๊ธฐ๋Š” ์–ด๋ ต๊ณ  ๋”ฐ๋ผ์„œ ์–‘๊ทน์˜ ์ž‘๋™ ์ „์œ„๋ฅผ ๋†’์ด๋Š” ๊ฒƒ์ด ์ „์ง€์˜ ์—๋„ˆ์ง€ ๋ฐ€๋„๋ฅผ ๋†’์ด๋Š” ํ•˜๋‚˜์˜ ๋ฐฉ๋ฒ•์ด ๋œ๋‹ค. ํ˜„ ์„ธ๋Œ€์˜ ์–‘๊ทน์œผ๋กœ์จ ๊ฐ€์žฅ ๋งŽ์ด ์“ฐ์ด๋Š” ๋ฌผ์งˆ์€ LiCoO2 ๋กœ, 4 V (vs. Li/Li+) ์ˆ˜์ค€์˜ ์ž‘๋™ ์ „์••์„ ๊ฐ–์œผ๋ฉฐ ํ‘์—ฐ ์Œ๊ทน๊ณผ์˜ ์ „์•• ์ฐจ์ด๋กœ 3.7 V ์ˆ˜์ค€์˜ ์‹ค์ œ ์ž‘๋™ ์ „์••์„ ๋ฐœํ˜„ํ•œ๋‹ค. ํ•œํŽธ LiCoO2๋ฅผ ๋Œ€์ฒดํ•˜๋Š” ๊ณ ์ „์œ„ ์ „๊ทน ๋ฌผ์งˆ๋กœ ์—ฐ๊ตฌ๋œ ๋ฌผ์งˆ์—๋Š” LiCoPO4, LiNi0.5Mn1.5O4(LNMO), LiNiPO4, Li3V2(PO4)3, NCA (Nickel Cobalt Aluminium Oxide), OLO (Over lithiated Layered Oxide) ๋“ฑ์ด ์žˆ๋‹ค. ์ด ์ค‘, LNMO์˜ ๊ฒฝ์šฐ ํ‰๊ท  ์ž‘๋™์ „์••์ด 4.7 V๋กœ 4 V ์ˆ˜์ค€์˜ LiCoO2์˜ ์ž‘๋™์ „์••๋ณด๋‹ค ๋†’์œผ๋ฉฐ, ์ƒ์˜จ์„ ๊ธฐ์ค€์œผ๋กœ ์ถฉยท๋ฐฉ์ „ ํŠน์„ฑ์ด ๋งค์šฐ ์šฐ์ˆ˜ํ•˜๋ฉด์„œ๋„ ๋‹จ์œ„ ์ค‘๋Ÿ‰ ๋‹น ์–ป์„ ์ˆ˜ ์žˆ๋Š” ์šฉ๋Ÿ‰์ด 130 mAh ์ˆ˜์ค€์œผ๋กœ LiCoO2์™€ ๋น„๊ฒฌํ•  ์ˆ˜ ์žˆ์„ ์ •๋„๋กœ ์ค€์ˆ˜ํ•ด ์œ ๋งํ•œ ์–‘๊ทน ๋ฌผ์งˆ๋กœ ๋ณผ ์ˆ˜ ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ผ๋ฐ˜์ ์œผ๋กœ 5 V vs. Li/Li+ ์ˆ˜์ค€์˜ ๋†’์€ ์ „์œ„์—์„œ ์ถฉโˆ™๋ฐฉ์ „์ด ์ด๋ฃจ์–ด์ง€๊ธฐ ๋•Œ๋ฌธ์—, ์ „ํ•ด์งˆ์˜ ์‚ฐํ™”๋ถ„ํ•ด์— ์˜ํ•œ ํ‘œ๋ฉดํ”ผ๋ง‰(SEI: Solid Electrolyte Interface)์˜ ์ƒ์„ฑ์ด ๋ถˆ๊ฐ€ํ”ผํ•˜๋‹ค. ์ง€์†์ ์ธ ์ถฉโˆ™๋ฐฉ์ „์€ ์ „ํ•ด์•ก์„ ์ง€์†์ ์œผ๋กœ ๋ถ„ํ•ด์‹œํ‚ด์œผ๋กœ SEI์˜ ๋‘๊ป˜๋ฅผ ์ ์ฐจ ๋‘๊ป๊ฒŒ ๋งŒ๋“ค๊ณ  ์ด๋Š” Li+์˜ ์ „๊ทน ๋‚ด๋ถ€ ๋ฐ ์™ธ๋ถ€๋กœ์˜ ์ด๋™์„ ์ ์ฐจ ์–ด๋ ต๊ฒŒ ๋งŒ๋“ฆ์œผ๋กœ์จ ์ „์ง€์˜ ์ „์ฒด์ ์ธ ์ „ํ•˜์ „๋‹ฌ์ด ์ง€์—ฐ๋œ๋‹ค. ๋‹ค์‹œ ๋งํ•ด, ์ „ํ•ด์งˆ์˜ ๋ถ„ํ•ด๋Š” ์ „์ง€์˜ ๋ถ„๊ทน๋„(polarization)๋ฅผ ์ฆ๊ฐ€์‹œ์ผœ ์„ฑ๋Šฅ์˜ ๊ฐํ‡ด๋ฅผ ์ดˆ๋ž˜ํ•˜๊ฒŒ ๋œ๋‹ค. ๋ณธ ์‹คํ—˜์—์„œ๋Š” ์‹๋ฌผ๊ณ„์— ๋„๋ฆฌ ์กด์žฌํ•˜๋Š” flavonoid์˜ ์ผ์ข…์ธ Quercetin์ด ์ „์ง€์˜ ์„ฑ๋Šฅ ๊ฐํ‡ด๋ฅผ ์™„ํ™”ํ•  ์ˆ˜ ์žˆ๋Š”์ง€ ์•Œ์•„๋ณด์•˜๋‹ค. Quercetin์˜ HOMO ๊ฐ’์€ -5.8 eV ์ˆ˜์ค€์œผ๋กœ -11 eV์˜ EC ์šฉ๋งค๋ณด๋‹ค ๋” ๋†’์•„ ์ „ํ•ด์•ก์˜ ์‚ฐํ™” ๋ถ„ํ•ด์ด์ „์— Quercetin์˜ ์‚ฐํ™” ๋ถ„ํ•ด๊ฐ€ ์ง„ํ–‰๋  ๊ฒƒ์œผ๋กœ ์˜ˆ์ƒ๋˜์—ˆ๋‹ค. ์‹คํ—˜ ๊ฒฐ๊ณผ Quercetin์„ ์ „ํ•ด์•ก์— ์ฒจ๊ฐ€ํ•œ ๊ฒฝ์šฐ๋Š” ์•ฝ 3.6 V vs. Li/Li+์˜ ์ „์œ„์—์„œ ์ „๋ฅ˜๊ฐ€ ๊ธ‰๊ฒฉํžˆ ์ฆ๊ฐ€ํ•œ ๋ฐ˜๋ฉด ๊ธฐ์ค€์ „ํ•ด์•ก์˜ ๊ฒฝ์šฐ ์•ฝ 4.3 V vs. Li/Li+์˜ ์ „์œ„์—์„œ๋ถ€ํ„ฐ ์ „๋ฅ˜๊ฐ€ ์ฆ๊ฐ€ํ•˜๊ธฐ ์‹œ์ž‘ํ•˜์˜€๊ณ  ๋”ฐ๋ผ์„œ Quercetin์˜ ์‚ฐํ™”๊ฐ€ ์ „ํ•ด์•ก์˜ ์‚ฐํ™”๋ณด๋‹ค ๋จผ์ € ์ผ์–ด๋‚จ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์‚ฌ์ดํด ํŠน์„ฑ์˜ ๊ด€์ ์—์„œ Quercetin์ด ์ฒจ๊ฐ€๋œ ๊ฒฝ์šฐ, ์ƒ์˜จ์˜ ์กฐ๊ฑด์—์„œ๋Š” 1 C์˜ ์ถฉยท๋ฐฉ์ „์„ 100์‚ฌ์ดํด๊นŒ์ง€ ์ง„ํ–‰ํ•œ ๊ฒฐ๊ณผ ์šฉ๋Ÿ‰ ์œ ์ง€์œจ ๋ฉด์—์„œ ์ฐจ์ด๊ฐ€ ์—†์—ˆ์œผ๋‚˜, Quercetin์ด ์ฒจ๊ฐ€๋œ ์ „์ง€์˜ ํ‰๊ท ์ ์ธ ์ฟจ๋กฑํšจ์œจ์ด ๋” ๋†’์Œ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ด๋Š” ์ „ํ•ด์•ก์˜ ๋ถ„ํ•ด์— ์˜ํ•œ ๋ถ€๋ฐ˜์‘์ด Quercetin์ด ์ฒจ๊ฐ€๋œ ๊ฒฝ์šฐ ๋” ์ ์—ˆ์Œ์„ ์˜๋ฏธํ•œ๋‹ค. ์ผ๋ฐ˜์ ์œผ๋กœ ์ „ํ•ด์•ก์˜ ๋ถ„ํ•ด์— ์˜ํ•œ ์ „๊ทน์˜ ํ‡ดํ™”๋Š” ๊ณ ์˜จ์—์„œ ์‹ฌํ•ด์ง€๊ธฐ ๋•Œ๋ฌธ์— ๊ณ ์˜จ(60โ„ƒ)์˜ ์กฐ๊ฑด์—์„œ๋Š” ์ฟจ๋กฑํšจ์œจ์ด ์ƒ์˜จ์— ๋น„ํ•ด ๋” ๋‚ฎ์•„์ง„๋‹ค. ๊ณ ์˜จ(60โ„ƒ) ์กฐ๊ฑด์—์„œ 1 C์˜ ์ „๋ฅ˜๋กœ 80์‚ฌ์ดํด๊นŒ์ง€ ์ถฉยท๋ฐฉ์ „์„ ์ง„ํ–‰ํ•ด ๋ณธ ๊ฒฐ๊ณผ LNMO // Li ์ „์ง€์˜ ์ถฉยท๋ฐฉ์ „์— ๋”ฐ๋ฅธ ์šฉ๋Ÿ‰๊ฐํ‡ด๋ฅผ ์ค„์ผ ์ˆ˜ ์žˆ์—ˆ์Œ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์‹คํ—˜์ด ๋๋‚œ ๋’ค, LNMO ์ „๊ทน์„ ํšŒ์ˆ˜ํ•˜์—ฌ XRD ๋ฐ XPS ๋ถ„์„์„ ์‹œํ–‰ํ•˜์˜€๊ณ , Quercetin์˜ ์กด์žฌ ํ•˜์— ๊ฒฐ์ •์„ฑ์˜ ์œ ์ง€๊ฐ€ ๋” ์ž˜ ๋˜๋ฉฐ ์ „ํ•ด์•ก์˜ ๋ถ„ํ•ด๊ฐ€ ์™„ํ™”๋จ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ž๊ฐ€๋ฐฉ์ „(self-discharge) ์‹คํ—˜์˜ ๊ฒฝ์šฐ ๊ณ ์˜จ์˜ ์˜ค๋ธ(60โ„ƒ)์—์„œ ์ „์ง€๋ฅผ 7์ผ๊ฐ„ ๋ณด๊ด€ํ•˜์—ฌ ์ง„ํ–‰ํ•˜์˜€๊ณ  Quercetin์ด ์ฒจ๊ฐ€๋œ ๊ฒฝ์šฐ์˜ ์ž๊ฐ€๋ฐฉ์ „ ์ •๋„๊ฐ€ ๋” ์ ์€ ๊ฒƒ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ž๊ฐ€๋ฐฉ์ „ ์ดํ›„ 1 C์˜ ์ „๋ฅ˜๋กœ ์‚ฌ์ดํด์„ ๋Œ๋ฆฐ ๊ฒฐ๊ณผ ์šฉ๋Ÿ‰์˜ ๊ฐํ‡ด ๋˜ํ•œ ๋” ์ ์Œ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋˜ํ•œ ์ž๊ฐ€๋ฐฉ์ „ ์‹คํ—˜์— ์“ฐ์ธ Lithium metal์„ ํšŒ์ˆ˜ํ•˜์—ฌ ICP-MS ๋ถ„์„์„ ์‹œํ–‰ํ•œ ๊ฒฐ๊ณผ, Quercetin์ด ์ฒจ๊ฐ€๋œ ์ „ํ•ด์•ก์„ ์‚ฌ์šฉํ•œ ๊ฒฝ์šฐ Mn๊ณผ Ni ๋“ฑ์˜ ์ „์ด๊ธˆ์†์˜ ๋†๋„๊ฐ€ ๋” ์ ๊ฒŒ ๊ฒ€์ถœ๋˜์—ˆ๋‹ค. ์ข…ํ•ฉ์ ์œผ๋กœ ๋ณผ ๋•Œ, Quercetin ๊ธฐ๋ฐ˜์˜ SEI๊ฐ€ ๊ธฐ์ค€์ „ํ•ด์•ก(Blank) ๊ธฐ๋ฐ˜์˜ SEI๋ณด๋‹ค ๋” ์•ˆ์ •์ ์ด๊ธฐ ๋•Œ๋ฌธ์— ์ „๊ทน์˜ ์•ˆ์ •์„ฑ์ด ํ–ฅ์ƒ๋˜์—ˆ๋‹ค๊ณ  ๋ณผ ์ˆ˜ ์žˆ๋‹ค.์ œ 1 ์žฅ. ์„œ๋ก  1 1.1. ์ด์ฐจ์ „์ง€์˜ ์›๋ฆฌ ๋ฐ ํŠน์ง• 1 1.2. ๋ฆฌํŠฌ ์ด์˜จ์ „์ง€์˜ ๊ตฌ์„ฑ์š”์†Œ 2 1.2.1. ์–‘๊ทน(Positive electrode) 3 1.2.2. ์Œ๊ทน(Negative electrode) 4 1.2.3. ์ „ํ•ด์•ก(Electrolyte) 6 1.2.4. ๋ถ„๋ฆฌ๋ง‰(Separator) 7 1.3. LiNi0.5Mn1.5O4 ์–‘๊ทน์˜ ํŠน์„ฑ 16 1.4. ํ‘œ๋ฉดํ”ผ๋ง‰(SEI) 22 1.4.1. ํ‘œ๋ฉดํ”ผ๋ง‰ ํ˜•์„ฑ 22 1.4.2. ํ‘œ๋ฉดํ”ผ๋ง‰ ํ˜•์„ฑ ์ฒจ๊ฐ€์ œ 23 1.4.3. Quercetin์˜ ํŠน์ง• 24 1.5. ์—ฐ๊ตฌ ๋ชฉํ‘œ 31 ์ œ 2 ์žฅ. ์‹คํ—˜ 32 2.1. ์ „๊ทน์˜ ์ œ์กฐ(Electrode preparation) 32 2.2. ์ „ํ•ด์•ก ์ œ์กฐ(Electrolyte preparation) 33 2.3. Quercetin์˜ ์‚ฐํ™” ๊ฑฐ๋™(Oxidation of Quercetin) 33 2.4. ์ „๊ธฐํ™”ํ•™์  ์„ฑ๋Šฅ ํ‰๊ฐ€(Electrochemical performance) 34 2.5. ๊ณ ์˜จ ํ‡ดํ™” ์‹คํ—˜(Degradation) 35 2.6. ํ‘œ๋ฉด ๋ถ„์„(Surface analysis) 35 ์ œ 3 ์žฅ. ๊ฒฐ๊ณผ ๋ฐ ํ† ๋ก  40 3.1. ์ „๊ทน์˜ ํŠน์„ฑ ํ™•์ธ(Electrode characterization) 40 3.2. Quercetin์˜ ์‚ฐํ™” ๊ฑฐ๋™(Oxidation of Quercetin) 44 3.3. ์ „๊ธฐํ™”ํ•™์  ์„ฑ๋Šฅ ํ‰๊ฐ€(Electrochemical performance) 48 3.3.1. ์ƒ์˜จ ์‚ฌ์ดํด(Room temperature) 48 3.3.2. ๊ณ ์˜จ ์‚ฌ์ดํด(High temperature) 51 3.4. ๊ณ ์˜จ ํ‡ดํ™” ์‹คํ—˜(Degradation) 55 3.5. ์ „๊ทน ํ‘œ๋ฉด ๋ถ„์„(Surface analysis) 59 3.5.1. EIS ๋ถ„์„(EIS analysis) 59 3.5.2. XPS ๋ถ„์„(XPS analysis) 62 3.5.3. FE-SEM ๋ถ„์„(FE-SEM analysis) 73 3.5.4. XRD ๋ถ„์„(XRD analysis) 75 3.5.5. ICP-MS ๋ถ„์„(ICP-MS analysis) 78 ์ œ 4 ์žฅ. ๊ฒฐ๋ก  81 ์ฐธ๊ณ  ๋ฌธํ—Œ 84 Abstract 89Maste

    ์‹ฌํ˜ˆ๊ด€๊ณ„ ๋ฐ ์ž๊ฐ€๋ฉด์—ญ ์งˆํ™˜ ์ง„๋‹จ์„ ์œ„ํ•œ ์ „๊ธฐํ™”ํ•™์  ์••ํƒ€์„ผ์„œ ๊ฐœ๋ฐœ์— ๊ด€ํ•œ ์—ฐ๊ตฌ

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    Masterํšจ๊ณผ์ ์ธ ์งˆ๋ณ‘ ์ง„๋‹จ์€ ๊ฑด๊ฐ•ํ•œ ์‚ถ์„ ์˜์œ„ํ•˜๊ธฐ ์œ„ํ•œ ํ•„์ˆ˜์š”์†Œ์ด๋‹ค. ํŠน๋ณ„ํžˆ, ์ƒ์ฒด์ง€ํ‘œ๋ฅผ ํ™œ์šฉํ•œ ์ง„๋‹จ์ด ๋งŽ์€ ๊ด€์‹ฌ์„ ๋ฐ›๊ณ  ์žˆ๋‹ค. ์ƒ์ฒด์ง€ํ‘œ๋ฅผ ๊ฒ€์ถœํ•˜๊ธฐ ์œ„ํ•ด์„œ ํ•ญ์ฒด๊ฐ€ ์ฃผ๋กœ ์ด์šฉ๋˜๊ณ  ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ํ•ญ์ฒด์˜ ํ•œ๊ณ„์ ์„ ๊ทน๋ณตํ•  ์ˆ˜ ์žˆ๋Š” ๋ฌผ์งˆ๋กœ ์•Œ๋ ค์ง„ ์••ํƒ€๋จธ๋ฅผ ์ด์šฉํ•ด์„œ ์ƒˆ๋กœ์šด ์ง„๋‹จ๋ฒ•์„ ๊ฐœ๋ฐœํ•˜๊ณ ์ž ํ•œ๋‹ค. 1์žฅ์—์„œ๋Š” ์••ํƒ€๋จธ์— ๋Œ€ํ•œ ์ „๋ฐ˜์ ์ธ ์ดํ•ด์™€ ์••ํƒ€๋จธ๋ฅผ ๊ฐœ๋ฐœํ•˜๋Š” ๊ธฐ์ˆ ์ธ in vitro selection ๋˜๋Š” systematic evolution of ligands by exponential enrichment (SELEX) ๋ฐฉ๋ฒ•์— ๋Œ€ํ•ด ๋‹ค๋ฃจ์—ˆ๋‹ค. 2์žฅ์—์„œ๋Š” ์‹ฌํ˜ˆ๊ด€๊ณ„ ์งˆํ™˜์˜ ์ƒ์ฒด์ง€ํ‘œ ๋‹จ๋ฐฑ์งˆ๋กœ ์ž˜ ์•Œ๋ ค์ง„ creatine kinase MB isoenzyme (CK-MB), n-terminal pro atrial natriuretic peptide (NT-proANP), n-terminal pro brain natriuretic peptide (NT-proBNP), heart type fatty acid binding protein (hFABP)์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋ฅผ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ๋จผ์ €, ์ด 4๊ฐ€์ง€ ๋‹จ๋ฐฑ์งˆ์„ ์„ฑ๊ณต์ ์œผ๋กœ ๋ฐœํ˜„ ๋ฐ ์ •์ œํ•˜์˜€๋‹ค. ๊ทธ ์ค‘, CK-MB, NT-proBNP, hFABP์— ๋Œ€ํ•œ ๋‹จ์ผ ๊ฐ€๋‹ฅ DNA ์••ํƒ€๋จธ ๊ฐœ๋ฐœ์„ ์„ฑ๊ณต์ ์œผ๋กœ ์ˆ˜ํ–‰ํ•˜์˜€์œผ๋ฉฐ, ์ „๊ธฐ์˜๋™ ์ด๋™๋„ ๊ฒ€์‚ฌ๋ฒ• (EMSA)์œผ๋กœ ์ƒ์ฒด์ง€ํ‘œ ๋‹จ๋ฐฑ์งˆ๊ณผ ์••ํƒ€๋จธ๊ฐ„์˜ ๊ฒฐํ•ฉ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๊ฐœ๋ฐœ๋œ ์••ํƒ€๋จธ๋Š” ํ˜•๊ด‘ ๋ถ„๊ด‘๋ฒ•์„ ์ด์šฉํ•˜์—ฌ ๋†’์€ ๋ฏผ๊ฐ๋„๋ฅผ ํ™•์ธํ•˜์˜€๋‹ค. CK-MB์˜ ๊ฒฝ์šฐ ํ•ด๋ฆฌ์ƒ์ˆ˜๊ฐ€ 43.32 nM์ด์˜€๊ณ , NT-proBNP๋Š” 54.58 nM์ด์˜€๋‹ค. ์ƒ์ฒด์ง€ํ‘œ ๋‹จ๋ฐฑ์งˆ์„ ๊ฒ€์ถœํ•˜๊ธฐ ์œ„ํ•ด์„œ ๊ฐœ๋ฐœ๋œ CK-MB, NT-proBNP ์••ํƒ€๋จธ๋ฅผ ํ™œ์šฉํ•œ ์ „๊ธฐํ™”ํ•™ ์ž„ํ”ผ๋˜์Šค ๋ถ„๊ด‘ํ•™ (EIS) ๊ธฐ๋ฐ˜ ์„ผ์„œ๋ฅผ ๋””์ž์ธํ•˜์˜€๊ณ , 1 ng/mL์˜ ํ‘œ์ ๋‹จ๋ฐฑ์งˆ ๊ฒ€์ถœ์— ์„ฑ๊ณตํ•˜์˜€๋‹ค. ๊ฐœ๋ฐœ๋œ ์••ํƒ€์„ผ์„œ๋Š” ์‹ฌํ˜ˆ๊ด€๊ณ„ ์งˆํ™˜ ์ง„๋‹จ์— ํ™œ์šฉํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์ด๋ผ ๊ธฐ๋Œ€๋œ๋‹ค. 3์žฅ์—์„œ๋Š” ์ž๊ฐ€๋ฉด์—ญ ์งˆํ™˜์—์„œ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•œ๋‹ค๊ณ  ์•Œ๋ ค์ง„ interleukin-17 receptor (IL-17R) ๊ฒ€์ถœ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋ฅผ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ๊ธˆ ๋‚˜๋…ธ ์ž…์ž๋ฅผ ๋„ํฌํ•ด์„œ ๋ฏผ๊ฐ๋„๋ฅผ ๋†’์ธ ๊ธˆ ์ „๊ทน์— IL-17R ์••ํƒ€๋จธ๋ฅผ ๊ณ ์ •์‹œ์ผœ์„œ 10 pg/mL ? 10 ng/mL์˜ IL-17R์„ ์„ฑ๊ณต์ ์œผ๋กœ ๊ฒ€์ถœํ–ˆ๋‹ค. ๊ฐœ๋ฐœ๋œ ์••ํƒ€์„ผ์„œ๋Š” interleukin-5 receptor (IL-5R), interleukin-13 receptor (IL-13R), cluster of differentiation 166 (CD166, ๋˜๋Š” ALCAM), albumin, bovine serum albumin(BSA), lysozyme์— ๋‚ฎ์€ ๊ฒฐํ•ฉ๋ ฅ์„ ๊ฐ–๋Š” ๊ฒƒ์„ ํ™•์ธํ•จ์œผ๋กœ์จ ๊ฐœ๋ฐœ๋œ ์„ผ์„œ๊ฐ€ ๋†’์€ ์„ ํƒ๋„๋ฅผ ๊ฐ–๋Š” ๊ฒƒ์„ ๊ฒ€์ฆํ•˜์˜€๋‹ค. ๋˜ํ•œ, ๋ฐ”์ด์˜ค์„ผ์„œ๋กœ์„œ์˜ ์œ ์šฉ์„ฑ์„ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•ด ์‚ฌ๋žŒ ํ˜ˆ์ฒญ ๋‚ด์—์„œ 100 pg/mL์˜ IL-17R์„ ๊ฒ€์ถœํ•˜์˜€๋‹ค. ๋˜ํ•œ, ์„ธํฌ ํ‘œ๋ฉด์— ๋ฐœํ˜„๋œ IL-17R ๊ฒ€์ถœ๋„ ์„ฑ๊ณตํ•จ์œผ๋กœ์จ ์„ผ์„œ ํ™œ์šฉ ๊ฐ€๋Šฅ์„ฑ์„ ์ž…์ฆํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์••ํƒ€๋จธ์™€ ์ „๊ธฐํ™”ํ•™์  ๊ฒ€์ถœ๋ฒ•์„ ์ ‘๋ชฉํ•˜์—ฌ ์‹ฌํ˜ˆ๊ด€๊ณ„ ์งˆํ™˜ ๋ฐ ์ž๊ฐ€๋ฉด์—ญ ์งˆํ™˜์— ๋Œ€ํ•œ ์ƒˆ๋กœ์šด ์ง„๋‹จ๋ฒ•์„ ์ œ์‹œํ•˜์˜€๋‹ค. ์ด๋Š” ๊ธฐ์กด ์ง„๋‹จ๋ฒ•์˜ ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•˜๊ณ , ์ƒˆ๋กœ์šด ์กฐ๊ธฐ ์ง„๋‹จ๋ฒ•์œผ๋กœ ํ™œ์šฉ๋  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋œ๋‹ค.Rapid and accurate diagnostic technology for cardiovascular diseases (CVDs) is highly important because CVDs are a major cause of death worldwide. Creatine kinase MB isoenzyme (CK-MB), N-terminal prohormone of atrial natriuretic peptide (NT-proANP), N-terminal prohormone of brain natriuretic peptide (NT-proBNP), and heart-type fatty acid binding protein (hFABP) are released into circulating blood immediately after CVDs. Therefore, CK-MB, NT-proANP, NT-proBNP, and hFABP are reliable biomarkers for the early diagnosis of CVDs. Also, a novel method is required for diagnosis of autoimmune disease. Because traditional diagnosis methods have difficulty in diagnosing earlier stages of autoimmune disease. Many factors are involved in immune response. Among them, interleukin-17 (IL-17) and interleukin-17 receptor (IL-17R, also known as IL-17RA) play significant roles in autoimmune disease. Observing the concentrations of biomarkers can be an important step in diagnosing the CVDs and autoimmune disease. Diagnosis based on biomarkers is relatively simple and cost-effective. Moreover, the diagnosis can be used to determine whether more complicated or invasive procedures are required. Numerous studies on biomarkers have been conducted to develop more sensitive and specific diagnostic approaches. In the clinical field, the level of a biomarker is commonly monitored by enzyme-linked immunosorbent assay (ELISA) and radioimmunoassay (RIA), which are both based on a selective antigen-antibody interaction. However, these antibody-based methods have several limitations, such as difficulty of production, low stability at high temperatures, and difficulty of modification for biological detection. Aptamers are single-stranded DNA (ssDNA), RNA or peptide molecules discovered by in vitro selection or Systematic Evolution of Ligands by Exponential enrichment (SELEX) methods. In both diagnostic and therapeutic applications, they have been considered to be rivals of antibodies. Aptamer-based detection methods are becoming more appealing because aptamers have many advantages over antibodies, such as their convenience of chemical synthesis, ease of modification, specificity to targets, thermal stability, rare immunological rejection and low cost. In this study, ssDNA aptamers targeted to CK-MB, NT-proBNP, and hFABP were developed. These aptamers were isolated by binding a random ssDNA library over magnetic beads of immobilized target protein, washing away unbound ssDNAs, and subsequently eluting. Next, target proteins for CVDs and autoimmune disease were successively detected using aptamers and electrochemical impedance spectroscopy (EIS) methods
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