25 research outputs found
๋ถ๊ฝ์ ํ์์ง์์์ ๋ ธํน์ ์ต์ ํ๊ธฐ ์ํ ๋ฆฌ์์น์ฅํ๊ฐ100 ๊ฐ์๋ฆฐ-์ํ์ฌ ํผํฉ์ฐ๋ฃ ๋ด ์ํ์ฌ ํจ๋ ์ต์ ํ
ํ์๋
ผ๋ฌธ(๋ฐ์ฌ)--์์ธ๋ํ๊ต ๋ํ์ :๊ณต๊ณผ๋ํ ๊ธฐ๊ณํญ๊ณต๊ณตํ๋ถ,2020. 2. ์กํํธ.๋ณธ ๋
ผ๋ฌธ์์๋ ๋ฆฌ์์น์ฅํ๊ฐ(Research octane number; RON)๊ฐ 100์ผ๋ก ๊ณ ์ ๋ ์ํฉ์์ ๊ฐ์๋ฆฐ-์ํ์ฌ ํผํฉ ์ฐ๋ฃ ๋ด ์ํ์ฌ ํจ๋์ ์ต์ ํํ์ฌ ๋ถ๊ฝ์ ํ(Spark ignition; SI)์์ง์์์ ๋
ธํน์ ์ต์ ํ๋ ๋ฐฉ๋ฒ์ ๊ดํด ๋
ผํ์๋ค. ์ด๋ฅผ ์ํด ์ํ์ฌํ์ค์ฐ๋ฃ(Ethanol reference fuel; ERF) ๋ด ์ํ์ฌ ํจ๋ ํผํฉ์ ๋ฐ๊พธ์ด๊ฐ๋ฉฐ ์ด 4๊ฐ์ง ํ
์คํธ์ฐ๋ฃ๋ฅผ ์ ์ ํ ๋ค์, ๊ธ์์์ถ์ฅ์น๋ฅผ ์ด์ฉํ์ฌ ํด๋น์ฐ๋ฃ์ ์ ํ์ง์ฐ์ ์ธก์ ํ์๋ค. ์ธก์ ๊ฒฐ๊ณผ๋ฅผ ๋ฐํ์ผ๋ก ๊ฐ ERF์ ๋
ธํนํน์ฑ์ด ์์ง์ด์ ์กฐ๊ฑด์ ๋ฐ๋ผ ์ด๋ป๊ฒ ๋ณํํ๋์ง๋ฅผ ๋ถ์ํ์์ผ๋ฉฐ, ์ด๋ฅผ ํตํด ์์์ ์์ง์ด์ ์กฐ๊ฑด์์ ์ต์ ์ ์ํ์ฌ ํจ๋์ ๋์ถํ๋ ๋ฐฉ๋ฒ์ ์ ์ํ์๋ค.
๋ณธ ์ฐ๊ตฌ์ ์ฒซ ๋ฒ์งธ ๋ชฉํ๋ ์์ง์ด์ ์กฐ๊ฑด์ ๋ฐ๋ผ ์ค๋ฆฐ๋ ๋ด ์จ๋-์๋ ฅ ํ๋กํ์ผ์ด ๋ณํํ ์, ์๋ก ๋ค๋ฅธ ERF์ฐ๋ฃ๋ค์ ๋
ธํน ํน์ฑ์ด ๊ฐ๊ฐ ์ด๋ป๊ฒ ๋ณํํ๋์ง๋ฅผ ๋ถ์ํ๋ ๊ฒ์ด๋ค. ์ด๋ฅผ ์ํด ์จ๋, ์๋ ฅ ๋ฐ ์ํ์ฌ ํจ๋ ๋ณํ์ ๋ฐ๋ฅธ ์ ํ์ง์ฐ์ ์ธก์ ํ๊ณ , ํ๊ท๋ถ์์ ํตํด ์ด์ ๋ํ ๊ฒฝํ์์ ๋์ถํ์๋ค. ๊ทธ ํ, 0-D 2๊ตฌ์ญ SI์์ง ์๋ฎฌ๋ ์ด์
์ ์ฌ์ฉํ์ฌ ๋ค์ํ ์์ง์ด์ ์กฐ๊ฑด ๋ณํ์ ๋ฐ๋ฅธ ์จ๋-์๋ ฅ ํ๋กํ์ผ์ ํธ์ฐจ๋ฅผ ๊ณ์ฐํ ๋ค, ์จ๋-์๋ ฅ ํ๋กํ์ผ์ ํธ์ฐจ๊ฐ ์ ํ์ง์ฐ์ ์ด๋ป๊ฒ ๋ณํ์ํค๋์ง ์ ๋์ ์ผ๋ก ๋ถ์ํ์๋ค. ๊ทธ ๊ฒฐ๊ณผ, ํ
์คํธ์ฐ๋ฃ์ ์ ํ์ง์ฐ์ RON์ด ๋์ผํจ์๋ ๋ถ๊ตฌํ๊ณ ์จ๋ ๋ฐ ์๋ ฅ์ ๋ํด ์์ดํ ์์กด์ฑ์ ๋ํ๋ด๋ ๊ฒ์ผ๋ก ๋ฐํ์ก๋ค. ํนํ, ์ํ์ฌ ํจ๋์ด ๋์ ์๋ก ์ ํ์ง์ฐ์ ํ์ฑํ ์๋์ง๊ฐ ๋๊ธฐ ๋๋ฌธ์ ์จ๋ ํธ์ฐจ ฮT/T์ ๋ ๋ฏผ๊ฐํ๋ฉฐ, ์๋ ฅ ํธ์ฐจ ฮP/P์ ๋ ๋ฏผ๊ฐํ ๊ฒ์ ๋ฐ๊ฒฌํ์๋ค. ๋ํ, ์ ํ์ง์ฐ์ ๋ํ ์จ๋-์๋ ฅ ํธ์ฐจ์ ์ํฅ์ ฮT/T๊ฐ (ฮณ-1)/ฮณ ฮP/P์ ๋์ผํ ๊ฒฝ์ฐ์๋ง ์ํ์ฌ ํจ๋๊ณผ ๋ฌด๊ดํ๋ค๋ ๊ฒ์ด ๋ฐํ์ก๋ค. ๋ณธ ๊ฒฐ๊ณผ๋ Kalghatgi์ K ๊ฐ ์๋ฆฌ์์ ์์ธก ํ ๊ฒ๊ณผ ์ผ์นํ๋ ๊ฒ์ผ๋ก ํ์ธ๋์์ผ๋ฉฐ. ๊ฒฐ๊ณผ์ ์ผ๋ก ๋ณธ ์ฐ๊ตฌ์์ ์ฌ์ฉํ ๋ฐฉ๋ฒ๋ก ์ ํตํด ์์ง์ด์ ์กฐ๊ฑด์ ๋ฐ๋ฅธ ์ฐ๋ฃ ๋ณ ๋
ธํน ํน์ฑ์ ๋ํ ์๋ก์ด ๊ด์ ์ ์ ์ํ ์ ์์๋ค.
์๊ธฐ ๊ฒฐ๊ณผ๋ ์ธ๋ถ ๋ฐฐ๊ธฐ ๊ฐ์ค ์ฌ์ํ(External exhaust gas recirculation; external-EGR)์ ์ฌ์ฉํ๋ ์กฐ๊ฑด์์๋ ์ ์ฉํ ์ ์๋๋ก ํ์ฅ๋์๋ค. ์์ ๋ฐฉ๋ฒ๋ก ๊ณผ ์ ์ฌํ๊ฒ, External-EGR์ด ์์ง ๋ด ์ ํ์ง์ฐ์ ๋ฏธ์น๋ ์ํฅ์ ํฌ์ ํจ๊ณผ ๋ฐ ์จ๋-์๋ ฅ ํ๋กํ์ผ ํจ๊ณผ๋ก ๋๋์ด ๊ฐ๋ณ์ ์ผ๋ก ํ๊ฐํ์๋ค. ๊ทธ ๊ฒฐ๊ณผ, External-EGR์ ํฌ์ํจ๊ณผ๋ ์ฐ๋ฃ ๋ด ์ํ์ฌ ํจ๋์ด 10 %์ผ ๋(ERF10) ๊ทน๋ํ๋๋ค๋ ์ฌ์ค์ ๋ฐ๊ฒฌํ์๋ค. ์ด ์์ธ์ ๋ถ์ํ๊ธฐ ์ํด ํ๊ท ๋ถ์์ ์งํํ ๊ฒฐ๊ณผ, ํ์ผ์ ํ ๋์ ๋ฏธ์ฐ์๊ฐ์ค์์ ๋ฐฉ์ถ๋ ์ด๋๊ณผ ํฌ์ ํจ๊ณผ์ ํฌ๊ธฐ ์ฌ์ด์ ๊ฐํ ์๊ด๊ด๊ณ๊ฐ ์์์ ๋ฐ๊ฒฌ ํ์๋ค. ๋ฐ๋ผ์, ERF10๊ฐ ํฌ์ํจ๊ณผ์ ๊ฐ์ฅ ๋ฏผ๊ฐํ ์ด์ ๋ ํ์ผ์ ํ ๋์์ ์ด ๋ฐฉ์ถ๋์ด ํฌ๊ธฐ ๋๋ฌธ์ธ ๊ฒ์ผ๋ก ์ดํด๋๋ค. ํํธ, External-EGR์ ์ํ ์จ๋-์๋ ฅ ํ๋กํ์ผ ํจ๊ณผ๋ ์ฐ๋ฃ ๋ด ํจ๋์ด ๋ง์์๋ก ๋ ํฌ๊ฒ ๋ํ๋๋ ๊ฒ์ ํ์ธํ์์ผ๋ฉฐ, ์ด๋ External-EGR์ ์ํ ์จ๋-์๋ ฅ ํ๋กํ์ผ์ ํธ์ฐจ๊ฐ ํญ์ ฮT/T>(ฮณ-1)/ฮณ ฮP/P์ ์กฐ๊ฑด์ ๋ง์กฑ์ํค๊ธฐ ๋๋ฌธ์ธ ๊ฒ์ ์ ์ ์์๋ค. ๊ฒฐ๊ณผ์ ์ผ๋ก, RON์ธก์ ์กฐ๊ฑด์์ Externa-EGR์ด ์ฌ์ฉ๋ ์ ์ต์ ์ ์ํ์ฌ ํจ๋์ 10 %๋ก ํ์ธ๋์๋ค. ์ด์ ๋ํ์ฌ, ์์ง์๋๊ฐ ๋ณํํจ์ ๋ฐ๋ผ ํ์ผ์ ํ ๋์์ ์ด ๋ฐฉ์ถ๋์ด ์ค์ด๋๋ ์ํฉ์ ๋ชจ์ฌํ์ฌ, ์ต์ ์ ์ํ์ฌ ํจ๋์ด ์์ง์๋์ ๋ฐ๋ผ 0 %์์ 10 %๊น์ง ๋ณํ ์ ์๋ค๋ ์ ๋ ์ ์ ์์๋ค.
์์ง์ด์ ์กฐ๊ฑด์ ๋ฐ๋ฅธ ์ต์ ์ํ์ฌํจ๋์ ๋ํ ์ดํด๋ฅผ ๋ฐํ์ผ๋ก, ๋ํ๋ฏผ๊ตญ ๋ด SI์์ง์ฐจ๋๊ตฐ์ ๋
ธํน์ต์ ๋ฅผ ์ต๋ํํ ์ ์๋ ์ต์ ์ํ์ฌ ํจ๋์ ์ ์ํ์๋ค. ์ด์ ๊ด๋ จํ์ฌ, 2018๋
๋ํ๋ฏผ๊ตญ ์๋์ฐจํ๋งคํต๊ณ๋ฅผ ์ด์ฉํ์ฌ, ๊ฐ SI์์ง๋ชจ๋ธ ๋ณ ํ๋งค๋์ ๋์ถํ์๋ค. ๊ทธ ํ, 0-D 2 ๊ตฌ์ญ SI์์ง ๋ชจ๋ธ์ ์ฌ์ฉํ์ฌ ๋
ธํน๊ฒฝ๊ณ์ (Detonation borderline; DBL) ์กฐ๊ฑด์์์ ๊ฐ SI์์ง๋ชจ๋ธ ๋ด ์ด์ญํ์ ์ํ๋ฅผ ๊ณ์ฐํ์๋ค. ๊ทธ ๊ฒฐ๊ณผ, 2018 ๋
๋ํ๋ฏผ๊ตญ์์ ํ๋งค๋ SI์์ง์ฐจ๋๊ตฐ์ 72 %๊ฐ ERF30์ด ์ต์ ์ธ ์์ญ์์ ์ดํ๋๋ ๊ฒ์ ์ ์ ์์๋ค. ๋ํ ์์ง์๋๊ฐ ๋นจ๋ผ์ง์๋ก DBL์กฐ๊ฑด์์์ ์ค๋ฆฐ๋ ๋ด ์๋ ฅ์ด ์ฆ๊ฐํ์ฌ ERF30์ด ์ต์ ์ธ ์์ญ์์ ์ดํ๋๋ SI์์ง์ฐจ๋์ด๊ตฐ์ด ๋ ๋ง์์ง๋ ๊ฒ์ ํ์ธํ์๋ค. ๋ณธ ์ฐ๊ตฌ๊ฒฐ๊ณผ๋ฅผ ํ์ฅํ์ฌ, ๋ฏธ๋์ External-EGR์ด ํ๋ฐํ ์ฌ์ฉ๋๋ ์ํฉ์์ ์ต์ ์ ์ํ์ฌํจ๋์ด ์ด๋ป๊ฒ ๋ณํํ ๊ฒ์ธ์ง๋ฅผ ๋ถ์ํ์๋ค. ๊ฒฐ๊ณผ์ ์ผ๋ก, Extern-EGR์ด ๋์
๋จ์ ๋ฐ๋ผ ์ต์ ์ ์ํ์ฌ ํจ๋์ ERF10์ ๊ฐ๊น์ ์ง ๊ฒ์ด๋ฉฐ, ์ด๋ ERF10์์ External-EGR์ ํฌ์ ํจ๊ณผ๊ฐ ๊ทน๋ํ๋๊ธฐ ๋๋ฌธ์ธ ๊ฒ์ผ๋ก ๋ฐํ์ก๋ค. ๊ทธ๋ฌ๋ ์์ง์๋๊ฐ ๋นจ๋ผ์ง์ ๋ฐ๋ผ ํฌ์ ํจ๊ณผ๊ฐ ์ค์ด๋ค๊ธฐ ๋๋ฌธ์, ๊ณ RPM์์ญ์์๋ External-EGR์ ๊ด๊ณ์์ด ERF30๊ฐ ์ฌ์ ํ ์ต์ ์ธ ๊ฒ์ผ๋ก ํ์ธ๋์๋ค.
๋ณธ ์ฐ๊ตฌ๋ ๋ค์ํ ์์ง์ดํ์กฐ๊ฑด์ ๋ฐ๋ผ ์ฐ๋ฃ ๋ณ ์ ํ์ง์ฐ ํน์ฑ์ ๋ถ์ํ๊ณ ๋ณธ ๊ฒฐ๊ณผ์ ๋
ธํน ํ์ ์ฌ์ด์ ์๊ด ๊ด๊ณ๋ฅผ ์ ์ํ ์ต์ด์ ์คํ์ฐ๊ตฌ์ด๋ค. ๋ํ, ๋ณธ ์ฐ๊ตฌ๋ ์์์ ์์ง์ดํ์กฐ๊ฑด์์ ์ต์ ์ ์ํ์ฌํจ๋์ ๊ฒฐ์ ํ๋ ๋ค์ด์ด๊ทธ๋จ์ ์ ์ํ์ฌ, ํฅํ ๋ํ๋ฏผ๊ตญ์ ๊ฐ์๋ฆฐ-์ํ์ฌ ํผํฉ์ฐ๋ฃ๊ฐ ๋์
๋ ์ ์ต์ ์ํ์ฌ ํจ๋์ ๊ฒฐ์ ํ ์ ์๋๋ก ํ์๋ค๋ ์ ์์๋ ์์๋ฅผ ์ง๋๋ค.This dissertation is devoted to optimize the ethanol content in gasoline-ethanol blend fuel with a fixed RON of 100, for maximizing antiknock characteristics in spark-ignition (SI) engines of light duty fleet in South Korea. To this end, the ethanol reference fuels (ERFs), which is a blend of ethanol and primary reference fuel, with varying ethanol content were chosen as surrogate fuels, then their auto-ignition characteristics were measured on rapid compression machine (RCM). The measurement was manipulated to quantitatively analyze the dependency of knocking characteristics of each ERF on engine operating condition from the aspect of chemical kinetics, whose results will eventually derive the optimal ethanol content with varying engine operating condition.
The first objective of this study was to analyze the dependency of knocking characteristic of various ERFs on temperatureโpressure profile of engine operating condition. To this end, an empirical correlation of the ignition delay with varying temperature, pressure, and ethanol content was derived based on a regression analysis using ignition delay measurement. Then, the deviation in the temperatureโpressure profile owing to changes in various engine operating parameters was calculated using a 0-D two zone SI engine simulation. Based on these results, it was quantified how the individual effects of temperature deviation and pressure deviation affect the ignition delay of each tested fuel. Consequently, it was found that the ignition delay of the tested fuels exhibits different dependencies on the temperature and pressure despite a fixed RON. In particular, the ignition delay of the fuel with the higher ethanol content is more sensitive to the temperature deviation, ฮT/T, owing to its higher activation energy, whereas it is less sensitive to the pressure deviation, ฮP/P. Moreover, it was revealed that the effect of temperatureโpressure deviation on the ignition delay is independent of the ethanol content, if and only if ฮT/T is equal to (ฮณ-1)/ฮณ*ฮP/P, where ฮณ is the specific heat ratio of the end gas. The results of this study were verified to be consistent with those predicted from Kalghatgis K value principle. Consequently, both approaches exhibited the same result on the knocking characteristics of various ERFs under varying engine operating conditions.
The above results were expanded to cover the engine operating condition with external-exhaust-gas-recirculation (EGR), where the thermodynamic state of end gas is significantly varied with the rate of dilution. Similar as the analysis on the effect of temperature-pressure effect, the total effect of external-EGR on the ignition delay of the simulated end gas was divided into two effects affecting the auto-ignition behavior: dilution effect and temperatureโpressure profile effect, then each effect was evaluated separately. As a result, the dilution effect by adding external-EGR was maximized when the fuel is ERF10. With a regression analysis, it was found that there is the correlation between the amount of dilution effect and the amount of pre-heat release in the end gas during a flame propagation; therefore, it is understood that ERF10 is the most sensitive to dilution effect due to its pre-heat release characteristic. On the other hand, ERF with lower ethanol content was more sensitive to temperatureโpressure effect by external-EGR on the ignition delay. It is found out that the deviation of temperatureโpressure profile by external-EGR always satisfies the condition of ฮT/T>(ฮณ-1)/ฮณ*ฮP/P; therefore, the temperatureโpressure effect of the fuel with lower ethanol content is higher than the other fuels, due to its lower sensitivity of ignition delay on temperature. Consequently, ERF10 has the highest external-EGR sensitivity in anti-knock behavior at RON test condition, and it is further discussed that the optimum ethanol content for external-EGR strategy could vary from ERF0 to ERF10 according to engine speed.
Based on the understanding of the effect of engine operating condition on the knocking characteristics of various ERFs, the ethanol content was optimized for maximizing knock suppression of light duty fleet in South Korea. In this regard, the sales volumes of each SI engine models was achieved from the statistics for model year 2018 in South Korea, which can be found from the database of KAMA. Then, the thermodynamic state of each SI engine design at detonation borderline (DBL) condition with varying engine speed were calculated using 0-D two-zone SI engine model. As a result, it was found that 72 % of SI engines sold for model year 2018 operates on the thermodynamic state where ERF30 is optimal for knock suppression. Moreover, as engine speed get faster, in-cylinder pressure at DBL condition increases, and more SI engines becomes operated on the thermodynamic state where ERF30 is optimal. The analysis was expanded to how the optimal ethanol content changes on the scenario that external-EGR is widely used in the future. Consequently, it was found that the introduction of external-EGR will makes the optimal ethanol content to be ERF10, which is the most sensitive to dilution effect of external-EGR. However, as the engine speed gets faster, the priority of ERF10 on dilution effect was surpassed by the priority of ERF30 on pressure effect, thus ERF30 still be optimal at the faster engine speed regardless of external-EGR.
This is the first experimental study to analyze the effect of engine operating condition on the ignition delay of various ERFs and develop quantitative correlations between ignition delay and knocking phenomena, reflecting operating conditions of modern engines. Moreover, this study suggested the useful diagram determining the optimal ethanol content at an arbitrary engine operating condition, which can be manipulated for government to determine the optimal ethanol content in gasoline-ethanol blend fuel suitable for the countries.Chapter 1. Introduction 1
1.1 Research background 1
1.1.1 Regulations on carbon dioxide emissions and petroleum consumption from light duty vehicles 1
1.1.2 Advance in engine design for high thermal efficiency 5
1.1.3 Knocking 8
1.1.4 Ethanol as an antiknock additive 11
1.1.5 Optimal ethanol content for a fixed RON 13
1.2 Literature review 15
1.2.1 New knock metrics 15
1.2.2 Optimization of fuel composition 17
1.3 Research objective and implication 18
1.4 Summary 19
Chapter 2. Methodology 21
2.1 Fuel matrix 21
2.2 0-D two-zone SI engine model 22
2.2.1 Determination of representative engine operating condition 22
2.2.2 Governing equation for the model 23
2.3 Rapid compression machine experiment 30
2.3.1 Measurement procedure and data processing 30
2.3.2 Active manipulation of compression process for simulating the flame propagation process in SI engine 38
Chapter 3. Effect of temperaturepressure profile of the end gas on optimal ethanol content 43
3.1 Engine simulation for varying engine operating conditions 44
3.2 Regression analysis on the ignition delay data 48
3.3 Quantitative analysis on the effect of engine operating condition on knocking characteristics 56
3.4 Uncertainty Quantification of E_T, E_P, and E_TP 57
3.5 The effect of engine operating condition on the knocking characteristics 58
3.6 Dependency of optimal ethanol content on the engine design 62
3.7 Analogy with K value principle 67
3.8 Summary 71
Chapter 4. Effect of external exhaust gas recirculation on optimal ethanol content 74
4.1 Engine simulation for the engine operating condition with external-EGR 76
4.2 Regression analysis on the ignition delay data 78
4.3 Quantitative analysis on the effect of engine operating condition on knocking characteristics 84
4.4 The effect of external-EGR on the knocking characteristics 85
4.4.1 Dilution effect 85
4.4.2 Temperature and pressure profile effect 88
4.4.3 The total effect of external-EGR 90
4.5 Dependency of the effect of external-EGR on engine speed 91
4.6 Summary 94
Chapter 5. Ethanol content optimization for light duty fleet in South Korea 95
5.1 Optimal ethanol content diagram 96
5.2 Thermodynamic state of SI engines in South Korea 98
5.3 Optimal ethanol content maximizing knock suppression in South Korea 103
5.4 Summary 106
Chapter 6. Conclusion 107
6.1 Knocking analysis based on the ignition delay 107
6.2 Optimal ethanol content for South Korea 110
6.3 Future work 111
Nomenclature 113
Abbreviation 118
Reference 121
๊ตญ๋ฌธ์ด๋ก 134Docto
๊ฐ์ ๋ฆฌ ์์ ๊ฒฐ์ ์์ ์์ ์ ์กฐ์ง๊ฒ์ฌ๊ฐ ํ์ํ๊ฐ์ ๋ํ ๊ณ ์ฐฐ
ํ์๋
ผ๋ฌธ (์์ฌ)-- ์์ธ๋ํ๊ต ๋ํ์ : ์ํ๊ณผ ๋ด๊ณผํ, 2016. 2. ์ด์ถํ.Introduction: Percutaneous needle aspiration or biopsy (PCNA or PCNB) is an established diagnostic technique that has a high diagnostic yield. However, its role in the diagnosis of nodular ground-glass opacities (nGGOs) is controversial, and the necessity of preoperative histologic confirmation by PCNA or PCNB in nGGOs has not been well addressed.
Methods: We here evaluated the rates of malignancy and surgery-related complications, and the cost benefits of resecting nGGOs without prior tissue diagnosis when those nGGOs were highly suspected for malignancy based on their size, radiologic characteristics, and clinical courses. Patients who underwent surgical resection of nGGOs without preoperative tissue diagnosis from January 2009 to October 2013 were retrospectively analyzed.
Results: Among 356 nGGOs of 324 patients, 330 (92.7%) nGGOs were resected without prior histologic confirmation. The rate of malignancy was 95.2% (314/330). In the multivariate analysis, larger size was found to be an independent predictor of malignancy (odds ratio, 1.08695% confidence interval, 1.001-1.178, p =0.047). A total of 324 (98.2%) nGGOs were resected by video-assisted thoracoscopic surgery (VATS), and the rate of surgery-related complications was 6.7% (22/330). All 16 nGGOs diagnosed as benign nodules were resected by VATS, and only one patient experienced postoperative complications (prolonged air leak). Direct surgical resection without tissue diagnosis significantly reduced the total costs, hospital stay, and waiting time to surgery.
Conclusions: With careful selection of nGGOs that are highly suspicious for malignancy, surgical resection of nGGOs without tissue diagnosis is recommended as it reduces costs and hospital stay.Introduction 1
Material and Methods 5
Study population and study design 5
Radiologic evaluation 5
Total costs, days of hospitalization, and waiting time 7
Statistical analysis 8
Results 9
Patient characteristics 9
Radiologic characteristics 12
Surgical procedure and complications related to surgery 14
Pathologic diagnosis 14
Advantages on costs, hospital stay, and waiting time 16
Discussion 18
Conclusions 23
References 24
Abstract in Korean 31Maste
Modeling charge transport in organic hosts: BCP and NBPhen
ํ์๋
ผ๋ฌธ(์์ฌ)--์์ธ๋ํ๊ต ๋ํ์ :๊ณต๊ณผ๋ํ ์ฌ๋ฃ๊ณตํ๋ถ,2020. 2. ๊น์ฅ์ฃผ.์ ์ ์ด๋์ธต ๋ฌผ์ง๋ก ์ฃผ๋ก ์ฌ์ฉ๋๋ BCP์ NBPhen ๋ถ์๋ ์๋ก ๋ค๋ฅธ ์ ํ mobility ๊ฐ์ ๊ฐ์ง๋ค. ๊ตฌ์ฒด์ ์ผ๋ก ์คํ์ ์ผ๋ก ์ธก์ ๋ NBPhen์ ์ ์ mobility ๊ฐ์ BCP์ ๊ฒฝ์ฐ๋ณด๋ค 10๋ฐฐ ๊ฐ๋ ๋๊ฒ ์ธก์ ๋๋ฉฐ, ์๋ฎฌ๋ ์ด์
์ ํตํ ๊ฒฐ๊ณผ์์๋ 9๋ฐฐ ๊ฐ๋ ๋์ ๊ฐ์ด ๋ํ๋ฌ๋ค. ์ด์ ๊ฐ์ mobility์ ๋ถ์ ๊ตฌ์กฐ ์ฌ์ด์ ๊ด๊ณ๋ฅผ ๊ท๋ช
ํ๊ธฐ ์ํ์ฌ microscopic simulation ๋ฐฉ๋ฒ๋ก ์ ์ฌ์ฉํ์๋ค. ์ด ๋ฐฉ๋ฒ๋ก ์์ ์ ๊ธฐ ๋ฐ๋ง์ ๋ชจ์ฌํ ๋ฌด์ ํ ์์คํ
์ ๋ง๋ค๊ธฐ ์ํ์ฌ ๋ถ์ ๋์ญํ ์๋ฎฌ๋ ์ด์
๋ฐฉ๋ฒ์ด ์ฌ์ฉ๋์์ผ๋ฉฐ, ๊ฐ ๋ถ์์ ์ ์ ํน์ฑ ์ค transfer integral, site energy, reorganization energy๋ฅผ ๊ตฌํ๊ธฐ ์ํ์ฌ ๋ฐ๋ ๋ฒํจ์ ์ด๋ก ๊ณผ Polarizable force field ๋ฐฉ๋ฒ๋ก ์ด ์ฌ์ฉ๋์๋ค. ๋ง์ง๋ง์ผ๋ก ์๋ฎฌ๋ ์ด์
์์ ์์์ ์ ํ์ ๋์ญํ ํน์ฑ์ ๋ชจ์ฌํ๊ธฐ ์ํ์ฌ Kinetic Monte Carlo ๋ฐฉ๋ฒ๋ก ์ ์ฌ์ฉํ์๋ค. BCP์ NBPhen ์ฌ์ด์ ์ ํ mobility ์ฐจ์ด์ ์์ธ์ ํฌ๊ฒ 3๊ฐ์ง ํญ๋ชฉ์ผ๋ก ๊ตฌ๋ถํ ์ ์๋๋ฐ ์ด๋ energetic disorder, transfer integral ๊ทธ๋ฆฌ๊ณ reorganization energy๋ก ๊ตฌ์ฑ๋๋ค. Energetic disorder์ ๊ด์ ์์๋, ์๋์ ์ผ๋ก ๋ ํฐ ๋ถ์ ์๊ทน์ ๋ถํฌ ํน์ฑ์ ๊ฐ๋ NBPhen์ ๊ฒฝ์ฐ energetic disorder ๊ฐ์ด ํฌ๊ธฐ ๋๋ฌธ์ ์ ํ mobility ํน์ฑ์ ์์ ํจ๊ณผ๋ฅผ ์ผ๊ธฐํ๋ค. ํ์ง๋ง transfer integral๊ณผ reorganization energy์ ๊ด์ ์์๋ transfer integral์ ํ๊ท ๊ฐ์ด ํฌ๊ณ reorganization energy ๊ฐ์ด ์์ NBPhen์ด ์ ํ mobility ๊ฐ์ ์์ด์ ์์ ํจ๊ณผ๋ฅผ ๊ฐ๋๋ฐ, ์ด๋ energetic disorder๋ก๋ถํฐ ์ผ๊ธฐ๋๋ ์์ ํจ๊ณผ๋ฅผ ๋ฐ์ด ๋๊ธฐ ๋๋ฌธ์ ๊ฒฐ๊ณผ์ ์ผ๋ก NBPhen์ mobility๊ฐ ํฌ๊ฒ ์ธก์ ๋๋ ๊ฒ์ผ๋ก ๋ถ์ ๋์๋ค. ๋ณธ ์ฐ๊ตฌ๋ฅผ ํตํด Phenanthroline ์ค์ฌ๋ถ๋ฅผ ๊ณตํต์ผ๋ก ๊ฐ์ง๋ฉฐ ๋ฉํธ๊ธฐ์ ๋ํํ๋ ๊ธฐ์์ ์นํ๊ธฐ์ ์ฐจ์ด์ ์ ๊ฐ๋ BCP์ NBPhen ๋ถ์์ mobility ์ฐจ์ด์ ๋ํด์๋ง ๋ถ์์ ํ์์ผ๋, ์ด์ ๋ ๋์๊ฐ ๋ค์ํ ์ข
๋ฅ์ ์นํ๊ธฐ์ ๋ฐ๋ฅธ mobility ์ฐจ์ด๋ฅผ ํตํด ์ผ๋ฐํ๊ฐ ๊ฐ๋ฅํ ๊ฒ์ผ๋ก ์์๋๋ฉฐ, ๋์ mobility ํน์ฑ์ ๊ฐ๊ธฐ ์ํด์๋ ๋ฎ์ energetic disorder์ reorganization energy ๊ฐ์ ๊ฐ์ง๋ฉฐ ๋์ transfer integral ํ๊ท ๊ฐ์ ๊ฐ์ง๋๋ก ๋ถ์๋ฅผ ์ค๊ณํด์ผ ํ ๊ฒ์ด๋ฉฐ, ์ด๋ ์นํ๊ธฐ์ ์ข
๋ฅ์ ๋ฐ๋ฅธ ๋ถ์์ ์ ์ ๊ตฌ์กฐ ์ฐจ์ด ๋ถ์๊ณผ ๋ฌด์ ํ ์์คํ
๋ด์์์ ์งํฉ์ ์ธ ํน์ฑ (energetic disorder, transfer integral) ๋ถ์์ ๊ธฐ๋ฐ์ผ๋ก ์ด๋ฃจ์ด ์ง ์ ์์ ๊ฒ์ผ๋ก ๊ธฐ๋๋๋ค.The charge carrier mobility of BCP and NBPhen which are commonly used as an electron transport material, are different from each other. Specifically, experimentally measured electron mobility of NBPhen is nearly 10 times larger than that of BCP and 9 times larger in charge carrier transport simulation. In order to unveil the relation between mobility and molecular structure, microscopic simulation method was used. In this methodology, amorphous system was constructed by using Molecular Dynamics (MD) simulation and electronic properties of molecule such as transfer integral, site energy of each molecular site and reorganization energy were calculated by using DFT method and Polarizable force field. Finally, charge dynamics was explicitly simulated by using Kinetic Monte Carlo method in the simulation box. The reason of difference in mobility can be categorized into three terms: energetic disorder, transfer integral and reorganization energy term. In the respective of energetic disorder, larger molecular dipole distribution of NBPhen which results in high energetic disorder has negative effect on charge carrier mobility. However, in the respective of transfer integral and reorganization energy, higher average value of transfer integral and smaller value of reorganization energy of NBPhen have positive effect on charge carrier mobility, which exceed the negative effect from energetic disorder. This result is originated from the difference in molecular structure between BCP and NBPhen. To sum up, from this research, we only analyzed the difference between BCP and NBPhen molecule that have Phenanthroline core in common and difference in substituents. However, by analyzing the mobility difference with different substituent groups, the analysis of this research can be generalized. Furthermore, in order to obtain high mobility value, the molecule should be designed to have low energetic disorder and reorganization value, and high average value of transfer integral which can be achieved by analyzing the difference in electronic properties of molecules with different substituent and collective property of amorphous system.Chapter 1 Introduction 6
1.1 OLEDs 6
1.2 Charge transfer theory 8
1.3 Brief history of charge transport simulation 11
1.4 Motivation 17
1.5 Contents of the thesis 18
Chapter 2 Microscopic charge transport simulation 19
2.1 Workflow of Microscopic charge transport simulation 19
2.2 Material morphology 22
2.3 Reorganization energy 33
2.4 Site energy 36
2.5 Transfer integrals 40
2.6 Charge transfer rate equation 41
2.7 Solving the master equationโฏ; KMC method 46
2.8 Finite-size scaling of charge carrier mobility 51
Chapter 3 Application: Understanding mobility difference between BCP and NBPhen molecule 54
3.1 Introduction 54
3.2 Simulation results and analysis 54
3.3 Summary 70
Chapter 4 Summary and Conclusion 72
References 73
Curriculum Vitae 77
์์ฝ (๊ตญ๋ฌธ ์ด๋ก) 79Maste
Etopside์ ์ํ HeLa ์ธํฌ์ฌ๋ฉธ ๊ธฐ๊ฐ ์ค acetyltransferase์ธ ARD1์ cytoplasmic translocation ์ ๋ํจ๊ณผ์ ๊ดํ ์ฐ๊ตฌ
Thesis(master`s)--์์ธ๋ํ๊ต ๋ํ์ :์ฝํ๊ณผ ์์ฝ์๋ช
๊ณผํ์ ๊ณต,2005.Maste
์์ฒด ๊ฐ์ด์์์ ๊ฒฝ๋์ ์ง๋ฐฉ๊ฐ์ด ์๋ ์ด์ํธ์ ๊ฐ์ฌ์ ๋ฅ๋ ฅ
Thesis(master`s)--์์ธ๋ํ๊ต ๋ํ์ :์ํ๊ณผ ์ธ๊ณผํ์ ๊ณต,2005.Maste
Genome-wide association study of non-tuberculous mycobacterial pulmonary disease
ํ์๋
ผ๋ฌธ(๋ฐ์ฌ) -- ์์ธ๋ํ๊ต๋ํ์ : ์๊ณผ๋ํ ์ํ๊ณผ, 2021.8. ์์ฌ์ค.Background The prevalence and incidence of non-tuberculous mycobacterial pulmonary disease (NTM-PD) are increasing in different parts of the world including South Korea. Despite ubiquitous exposure to NTM, a subset of people develop NTM-PD. Moreover, the presence of ethnic disparity, familial clustering, and the distinct phenotype of NTM-PD indicate the presence of genetic predispositions to this disease. However, the genetic factors associated with susceptibility to NTM-PD have been unclear. We aimed to find genetic variants in individuals with NTM-PD by a genome-wide association study (GWAS).
Methods We performed a GWAS with Korean patients with NTM-PD and controls from the Healthy Twin Study, Korea cohort. Candidate single-nucleotide polymorphisms (SNPs) from this discovery cohort were then validated in another Korean replication cohort. The Genotype-Tissue Expression (GTEx) data set was utilized to find expression quantitative trait loci (eQTL). In addition, we conducted the PrediXcan analysis to predict the candidate gene expression levels using our imputed genotype data and the GTEx data set. We performed a Mendelian randomization (MR) analysis to evaluate the causal effect related to the expression level of a candidate gene on the risk of development of NTM-PD. Moreover, we performed a transcriptome profiling analysis with publicly accessible data sets to identify differentially expressed genes (DEGs) in NTM-infected macrophages.
Results Through the GWAS with 403 patients with NTM-PD and 306 controls, we found rs849177 on chromosome 7p13 as the candidate SNP associated with susceptibility to NTM-PD (odds ratio, 2.34; 95% confidence interval [CI], 1.71 ~ 3.21; p=1.36ร10โ7). Its association was replicated in the independent cohort of 184 individuals with NTM-PD and 1,680 controls. When the Fisherโs method was applied, the combined p-value for both cohorts was 4.92ร10โ8. The eQTL analysis revealed that a risk allele (C) at rs849177 was associated with decreased expression levels of STK17A, a proapoptotic gene. According to the PrediXcan analysis, STK17A was the most significant DEG between individuals with NTM-PD and controls. A causal effect of STK17A on the development of NTM-PD was found in the MR analysis (ฮฒ, -4.627; 95% CI, -8.768 ~ -0.486; p=0.029). According to the transcriptome profiling analysis, the expression levels of STK17A increased significantly in macrophages infected with NTM.
Conclusions We found rs849177 on chromosome 7p13 as a susceptibility marker for NTM-PD in a Korean population. This genetic variant might be related to susceptibility to NTM-PD by modifying the expression level of a proapoptotic gene.์๋ก : ๋น๊ฒฐํตํญ์ฐ๊ท ์ ํ ์๊ณผ ๊ฐ๋ฌผ ๋ฑ์ ์์ฐํ๊ฒฝ์ ๋๋ฆฌ ๋ถํฌํ๊ณ ์์ผ๋ฏ๋ก ๊ฑฐ์ ๋ชจ๋ ์ฌ๋๋ค์ด ์ข
์ข
๋น๊ฒฐํตํญ์ฐ๊ท ์ ํก์
ํ๊ฒ ๋๋๋ฐ, ์ด๋ค ์ค ์ผ๋ถ์์๋ง ๋น๊ฒฐํตํญ์ฐ๊ท ํ์งํ์ด ๋ฐ์ํ๋ค๋ ์ ์ ์ด ์งํ์ ๋ํ ์ ์ ์ ์์ธ์ด ์กด์ฌํ๋ค๋ ์ ์ ์์ฌํ๋ค. ๋ณธ ์ฐ๊ตฌ์ ๋ชฉํ๋ ์ต๊ทผ ๊ธ๊ฒฉํ ์ฆ๊ฐํ๊ณ ์๋ ๋น๊ฒฐํตํญ์ฐ๊ท ํ์งํ์๋ค์ ์ ์ ์ ๊ฒฐํจ ์กด์ฌ ์ฌ๋ถ๋ฅผ ์ ์ฅ์ ์ ์ฒด์ฐ๊ด๋ถ์์ฐ๊ตฌ๋ฅผ ํตํด ํ์ธํ๋ ๊ฒ์ด๋ค.
๋ฐฉ๋ฒ: ๋น๊ฒฐํตํญ์ฐ๊ท ํ์งํ์์ ์๋ฅ์ด ์ฝํธํธ์ ์ฐธ์ฌํ ๊ฑด๊ฐ์ธ์ ๋์กฐ๊ตฐ์ผ๋ก ์ผ์ ์ ์ฅ์ ์ ์ฒด์ฐ๊ด๋ถ์์ฐ๊ตฌ๋ฅผ ์ํํ๋ค. ์๋ฅ์ด๋ ๋ฌด์์๋ก ๋ฐฐ์ ๋ 1๋ช
๋ง ๋์กฐ๊ตฐ์ผ๋ก ์ฐธ์ฌํ ์ ์์๋ค. ์ ์ฅ์ ์ ์ฒด์ฐ๊ด๋ถ์์ฐ๊ตฌ์์ ํ๋ณด๋ก ์ ์ ๋ ์ ์ ์ ๋ณ์ด์ ๋ํด์๋ ๋
๋ฆฝ์ ์ธ ๋น๊ฒฐํตํญ์ฐ๊ท ํ์งํ์-๋์กฐ๊ตฐ ์ฝํธํธ์์ ์ฐ๊ด์ฑ์ด ์ฌํ๋๋์ง ํ์ธํ๋ค. GenotypeโTissue Expression (GTEx) ๋ฐ์ดํฐ๋ฒ ์ด์ค๋ฅผ ์ด์ฉํด์ ๋ฐํ ์์ ํ์ง ์ ์ ์์๋ฆฌ(expression quantitative trait loci, eQTL)๋ฅผ ์๋ณํ๊ณ , ๋ฉ๋ธ ๋ฌด์์๋ฐฐ์ (Mendelian randomization) ๋ถ์์ ์ํํ๋ค.
๊ฒฐ๊ณผ: 403๋ช
์ ๋น๊ฒฐํตํญ์ฐ๊ท ํ์งํ์์ 306๋ช
์ ๋์กฐ๊ตฐ์ ๋์์ผ๋ก ํ ์ ์ฅ์ ์ ์ฒด์ฐ๊ด๋ถ์์ฐ๊ตฌ๋ฅผ ํตํด์ 7๋ฒ ์ผ์์ฒด ๋จ์(7p13)์ ์์นํ ์ ์ ์ ๋ณ์ด์ธ rs849177์ด ๋น๊ฒฐํตํญ์ฐ๊ท ํ์งํ์ ๋ํ ๊ฐ์์ฑ๊ณผ ๊ด๋ จ๋ ์ ์ ์ ๋ณ์ด๋ก ์ถ์ ๋์๋ค (OR, 2.34; 95% CI, 1.71 to 3.21; p=1.36ร10โ7). ์ด ์ฐ๊ด์ฑ์ ๋
๋ฆฝ์ ์ธ ๋น๊ฒฐํตํญ์ฐ๊ท ํ์งํ์-๋์กฐ๊ตฐ ์ฝํธํธ์์ ์ฌํ๋์๊ณ , ๋ ์ฝํธํธ๋ฅผ ํจ๊ป ๋ถ์ํ์ ๋์ ์ ์ํ๋ฅ ์ 4.92ร10โ8์๋ค. eQTL ๋ถ์์ ํตํด rs849177์ ์ํ ๋๋ฆฝ์ ์ ์(risk allele)๊ฐ ์ธํฌ์๋ฉธ์ฌ๋ฅผ ์ ๋ฐํ๋ ์ ์ ์์ธ STK17A์ ๋ฐํ ๊ฐ์์ ์ฐ๊ด๋์ด ์๋ค๋ ๊ฒ์ ๋ฐํ๋ค. ๋ฉ๋ธ ๋ฌด์์๋ฐฐ์ ๋ถ์์ ํตํด STK17A๊ฐ ๋น๊ฒฐํตํญ์ฐ๊ท ํ์งํ ๋ฐ์์ ์ธ๊ณผ๊ด๊ณ๊ฐ ์๋ค๋ ๊ฒ์ ํ์ธํ๋ค (ฮฒ, -4.627; 95% CI, -8.768 ~ -0.486; p=0.029).
๊ฒฐ๋ก : 7๋ฒ ์ผ์์ฒด ๋จ์(7p13)์ ์์นํ ์ ์ ์ ๋ณ์ด๊ฐ ํ๊ตญ์ธ์ ๋น๊ฒฐํตํญ์ฐ๊ท ํ์งํ์ ๋ํ ๊ฐ์์ฑ๊ณผ ์ฐ๊ด๋์ด ์์๋ค. ๋น๊ฒฐํตํญ์ฐ๊ท ํ์งํ์๋ ์ด ์ ์ ์ ๋ณ์ด์ ์ํ ๋๋ฆฝ์ ์ ์๋ฅผ ๊ฐ์ง๊ณ ์์ ๊ฐ๋ฅ์ฑ์ด ๋์๋ฐ, ์ด ์ํ ๋๋ฆฝ์ ์ ์๋ ์ธํฌ์๋ฉธ์ฌ๋ฅผ ์ ๋ฐํ๋ ์ ์ ์์ธ STK17A์ ๋ฐํ ๊ฐ์์ ์ฐ๊ด๋์ด ์๋ค. ๋ฐ๋ผ์ ๋น๊ฒฐํตํญ์ฐ๊ท ์ ๊ฐ์ผ๋ ๋์์ธํฌ์ ์ธํฌ์๋ฉธ์ฌ๊ฐ ์ ์์ ์ผ๋ก ์งํ๋์ง ์์ ๋น๊ฒฐํตํญ์ฐ๊ท ํ์งํ์ ๋ํ ๊ฐ์์ฑ์ด ์ฆ๊ฐํ ๊ฒ์ผ๋ก ์ถ์ ๋๋ค.I. ์ ๋ก 1
1. ๋น๊ฒฐํตํญ์ฐ๊ท ํ์งํ์ ์ธ๊ณ์ ์ธ ์ฆ๊ฐ ์ถ์ธ 1
2. ๋น๊ฒฐํตํญ์ฐ๊ท ํ์งํ ์น๋ฃ์ ์ด๋ ค์ 6
3. ๋น๊ฒฐํตํญ์ฐ๊ท ํ์งํ์ผ๋ก ์ธํ ์ฌ๋ง๋ฅ ๋ฐ ์ฌํโ๊ฒฝ์ ์ ๋น์ฉ์ ์ฆ๊ฐ 6
4. ๋น๊ฒฐํตํญ์ฐ๊ท ํ์งํ์ ๋ํ ์ ์ ์ ์์ธ 8
5. ์ต๊ทผ์ ์์ ์ผ๊ธฐ์์ด ๋ถ์ ์ฐ๊ตฌ์ ์ ํ์ 10
6. ์ฐ๊ตฌ์ ํ์์ฑ 14
II. ์ฐ๊ตฌ ๋ฐฉ๋ฒ 15
1. ๋ฐ๊ตด ์ฝํธํธ(discovery cohort) 15
2. ์ฌํ ์ฝํธํธ(replication cohort) 16
3. ๋ฐ๊ตด ์ฝํธํธ์์ ์ํ๋ ์ ์ฅ์ ์ ์ฒด์ฐ๊ด๋ถ์์ฐ๊ตฌ 17
4. ์ฌํ ์ฝํธํธ๋ฅผ ํตํ ๊ฒ์ฆ(validation) 21
5. ๋ค์ฐจ์ ์ฒ๋๋ฒ(multidimensional scaling, MDS) 23
6. ์ง์ญ ํ๋กฏ(regional plot) 24
7. ์ ์ฅ์ ์ ์ฒด ๋ณตํฉ ํ์ง ๋ถ์(genome-wide complex trait analysis) 24
8. ํ ํด๋ก์ง ์ฐ๊ด ๋๋ฉ์ธ ๋ถ์(topologically associating domain analysis) 25
9. ๋ฐํ ์์ ํ์ง ์ ์ ์์๋ฆฌ(expression quantitative trait loci, eQTL)์ PrediXcan ๋ถ์ 25
10. 2-ํ๋ณธ ๋ฉ๋ธ ๋ฌด์์๋ฐฐ์ (two-sample Mendelian randomization) ๋ถ์ 26
11. ๋น๊ฒฐํตํญ์ฐ๊ท ์ ๊ฐ์ผ๋ ๋์์ธํฌ(macrophage)์ ์ ์ฌ์ฒด(transcriptome) ํ๋กํ์ผ๋ง ๋ถ์ 29
12. Gene Ontology enrichment ๋ถ์ 30
13. ๊ธฐ์กด์ ์๋ ค์ง ์ ์ ์์ ๋ํ ํํ ๋ณ์ด(common variant) ๋ถ์๊ณผ ์ ์ ์ ์ธํธ(gene set) ๋ถ์ 30
III. ๊ฒฐ ๊ณผ 32
1. ์ ์ฅ์ ์ ์ฒด์ฐ๊ด๋ถ์์ผ๋ก ์ป์ ์ ์ฌ์ ํ๋ณด SNP 32
2. ์ ์ฌ์ ํ๋ณด SNP์ ๊ฒ์ฆ 45
๏ผ. 3์ฐจ์ ๊ตฌ์กฐ ๋ถ์ 48
๏ผ. ๋น๊ฒฐํตํญ์ฐ๊ท ํ์งํ๊ณผ ์ฐ๊ด๋ ํ๋ณด ์ ์ ์ 49
๏ผ. ํ๋ณด ์ ์ ์๊ฐ ๋น๊ฒฐํตํญ์ฐ๊ท ํ์งํ ๋ฐ์์ ๋ฏธ์น๋ ์ธ๊ณผ์ ์ํฅ(causal effect) 56
๏ผ. ๋น๊ฒฐํตํญ์ฐ๊ท ์ ๊ฐ์ผ๋ ๋์์ธํฌ์์ ํ๋ณด ์ ์ ์์ ์ฐจ๋ณ์ ๋ฐํ(differential expression) 58
๏ผ. ๋น๊ฒฐํตํญ์ฐ๊ท ์ ๊ฐ์ผ๋ ๋์์ธํฌ์์ ์ธํฌ์๋ฉธ์ฌ(apoptosis) ๊ฒฝ๋ก์ ๊ฐํ(enrichment) 60
๏ผ. ๊ธฐ์กด์ ์๋ ค์ง ๋น๊ฒฐํตํญ์ฐ๊ท ํ์งํ ๊ด๋ จ ์ ์ ์์ ๋ํ ์ฐ๊ด ์ฐ๊ตฌ 64
IV. ๊ณ ์ฐฐ 69
V. ๊ฒฐ ๋ก 79
์ฐธ๊ณ ๋ฌธํ 80
Abstract 96๋ฐ
Effect of V addition on the ferrite transformation in low carbon steels
ํ์๋
ผ๋ฌธ(๋ฐ์ฌ)--์์ธ๋ํ๊ต ๋ํ์ :์ฌ๋ฃ๊ณตํ๋ถ,2002.Docto
์์ฒด๊ฐ์ด์ ํ ์ง๋ฐฉ๊ฐ ์ด์ํธ์์์ ๊ฐ์ ๊ตฌ์ธํฌ์ ์ฆ์
ํ์๋
ผ๋ฌธ(๋ฐ์ฌ) --์์ธ๋ํ๊ต ๋ํ์ :์ํ๊ณผ ์ธ๊ณผํ ์ ๊ณต,2007.Docto
ํ๋ผ์ดํธ-ํผ์ผ๋ผ์ดํธ๊ฐ์ ๋๊ฐ์๋์ ๋ฐ๋ฅธ ๋ฏธ์ธ์กฐ์ง๊ณผ ๊ธฐ๊ณ์ ์ฑ์ง ์์ธก
ํ์๋
ผ๋ฌธ(์์ฌ)--์์ธ๋ํ๊ต ๋ํ์ :๊ธ์๊ณตํ๊ณผ,1997.Maste
Long-working(0.3m) distance microscope
MasterThe need for a high magnification microscope with a long-working distance has emerged in order to observe the laser focus position for TMDC sample with a 30~40 ฮผm. To solve this problem, a long-working (0.3m) distance microscope should be manufactured to measure TMDC samples in a vacuum chamber.
Some conditions and restrictions were placed for simple implementation.
(1) Operates at a single wavelength of 532 to reduce chromatic aberration
(2) Realize a magnification of 10 times or more
(3) Limit the distance from the first lens to the detector to 40 or less for actual production
(4) Use of commercial lenses as much as possible for simple production
(5) Minimization of monochromatic aberration through simulation
Simulations were conducted through the above conditions and constraints.
As a result of the experiment based on the simulation, it succeeded in obtaining an image with a magnification of up to 25 times and a resolution of 8 ฮผm.ํฌํญ๊ณต๋ ์ํ ์ด ๊ณผํ ์ฐ๊ตฌ์ค ๋ด ์ํ ์ด ๊ด ์์ค์ ๊ฒฝ์ฐ ๋ฐ๊ฒฝ์ด 25 ์์ค์ ์ง๊ณต ์ฑ๋ฒ ์์ ์์ญ ์์ค์ TMDC ์ํ์ ํ์ฉํ๋ ์คํ์ ์งํํ๊ณ ์๋ค. ์ง๊ณต ๋ฐ์์ 30~40 ์์ค์ TMDC ์ํ์ ๋ํ ๋ ์ด์ ์ ์ง์์์น๋ฅผ ๊ด์ธกํ๊ธฐ ์ํด์ ๊ธด Working distance์ ๊ณ ๋ฐฐ์จ ํ๋ฏธ๊ฒฝ์ ํ์์ฑ์ด ๋๋๋์๋ค. ์ด๋ฅผ ํด๊ฒฐํ๊ธฐ ์ํด Long-working(0.3m) distanace microscope์ ์ ์์ ํ์ฌ ์ง๊ณต ์ฑ๋ฒ ์์ TMDC์ํ์ ์ธก์ ํด์ผ ํ๋ค. Microscope๋ฅผ ์์ ์ํฉ์ ๊ณ ๋ คํ๋ฉฐ, ๊ฐ๋จํ๊ฒ ๊ตฌํํ๊ธฐ ์ํ์ฌ ๋ช ๊ฐ์ง ์กฐ๊ฑด๊ณผ ์ ์ฝ์ ๋์๋ค.
(1) ์์์ฐจ๋ฅผ ์ค์ด๊ธฐ ์ํด 532 ์ ๋จ์ผ ํ์ฅ์์ ์๋
(2) 10๋ฐฐ ์ด์์ ๋ฐฐ์จ์ ๊ตฌํ
(3) ์ค์ ์ ์์ ์ํด ์ฒซ๋ฒ์งธ ๋ ์ฆ๋ก๋ถํฐ detector๊น์ง์ ๊ฑฐ๋ฆฌ๋ฅผ 40 ์ดํ ์ ์ฝ
(4) ๊ฐ๋จํ ์ ์์ ์ํด ์ต๋ํ์ ์์ฉ๋ ์ฆ ์ฌ์ฉ
(5) ์๋ฎฌ๋ ์ด์
์ ํตํด ๋จ์์์ฐจ์ ์ต์ํ
์์ ์กฐ๊ฑด๊ณผ ์ ์ฝ์ ํตํด ์๋ฎฌ๋ ์ด์
์ ์งํํ์๊ณ , ์๋ฎฌ๋ ์ด์
๊ฒฐ๊ณผ๋ฅผ ๋ฐํ์ผ๋ก ์คํ์ ์งํํ์๋ค.์๋ฎฌ๋ ์ด์
์ ๊ธฐ๋ฐ์ผ๋ก ํ ์คํ ๊ฒฐ๊ณผ ์ต๋ 25๋ฐฐ์ ๋ฐฐ์จ๊ณผ 8ฮผm ๋ถํด๋ฅ์ ์ด๋ฏธ์ง๋ฅผ ์ป๋ ๋ฐ ์ฑ๊ณตํ๋ค