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New application of layered silicates for carbon fiber reinforced carbon composites
정의경,이영석,Jinhoon Kim,Se Ho Cho,Jeong-il Kim,In-Sub Han 한국공업화학회 2011 Journal of Industrial and Engineering Chemistry Vol.17 No.2
To investigate potential use of a layered silicate, illite, for carbon fiber-reinforced (C/C) composites, the C/C composites were prepared at different carbonization temperatures, specifically 1000 8C and 1650 8C using illite. The physical and chemical changes in the prepared C/C composites that were induced by the addition of illite and anti-oxidation and mechanical properties of the composites were investigated. A carbothermal reaction occurred due to the addition of illite when the composite was prepared at 1650 8C,which resulted in the formation of SiC from the illite and carbon. The physical structures of the composites changed due to the increased interfacial adhesion between the reinforcing carbon fibers and the carbon matrix, which resulted increased bulk densities, and decreased porosities. The carbothermal reaction and physical structural changes that were induced by the addition of illite synergistically improved the anti-oxidation properties of the prepared composites, which were observed as a delay in oxidation. In addition, illite filler also improved flexural strength of the composite, due to the increased interfacial adhesion induced by illite addition. Therefore, the application of the layered silicate, illite, for C/C composites can be quite promising.
Convolutional Neural Network Technology in Endoscopic Imaging: Artificial Intelligence for Endoscopy
최준명,신기원,Jinhoon Jung,배현진,Do Hoon Kim,Jeong-Sik Byeon,김남국 대한소화기내시경학회 2020 Clinical Endoscopy Vol.53 No.2
Recently, significant improvements have been made in artificial intelligence. The artificial neural network was introduced in the 1950s. However, because of the low computing power and insufficient datasets available at that time, artificial neural networks sufferedfrom overfitting and vanishing gradient problems for training deep networks. This concept has become more promising owing tothe enhanced big data processing capability, improvement in computing power with parallel processing units, and new algorithmsfor deep neural networks, which are becoming increasingly successful and attracting interest in many domains, including computervision, speech recognition, and natural language processing. Recent studies in this technology augur well for medical and healthcareapplications, especially in endoscopic imaging. This paper provides perspectives on the history, development, applications, andchallenges of deep-learning technology.
Steam condensation in horizontal and inclined tubes under stratified flow conditions
Ahn, Taehwan,Kang, Jinhoon,Bae, Byeonggeon,Jeong, Jae Jun,Yun, Byongjo Elsevier 2019 INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER - Vol.141 No.-
<P><B>Abstract</B></P> <P>In this study, an experiment on condensation heat transfer was conducted to develop a condensation model considering the structure of separated flow patterns. Multidimensional local condensation heat transfer parameters were measured in pure saturated steam at pressures of 1–5 bar and mass fluxes of 10–50 kg/m<SUP>2</SUP> s in an inclinable tube with an inner diameter of 40 mm and a length of 3 m. A heat partition angle, which separated the upper and lower heat transfer areas for film condensation and convective heat transfer in stratified flow, was obtained based on the inflection point of the circumferential distribution function of local heat flux. A new condensation heat transfer model consisting of the heat partition angle and heat transfer coefficient correlations was developed based on the local heat transfer data. The experimental data for model development were obtained using circular tubes with inner diameters of 30–45 mm and inclination angles of 0–10° under pure saturated steam conditions at pressures of 1–67 bar and mass fluxes of 10–329 kg/m<SUP>2</SUP> s. The model predicted the average heat transfer coefficient with an average deviation of 6.2% against the present experimental data.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Condensation heat transfer models often neglect the structure of flow patterns. </LI> <LI> Local heat transfer parameters were measured inside a condensation tube. </LI> <LI> Heat partition angle was used to separate heat transfer areas in condensation tube. </LI> <LI> A condensation model was developed that accounts for flow channel inclination. </LI> <LI> Model predictions and experimental findings agreed well. </LI> </UL> </P>
산 촉매에 따른 아나타제/브루카이트 혼성형 TiO<sub>2</sub> 광촉매의 메틸렌블루 광분해특성
윤석민,김진훈,정의경,임지선,이영석,Yun, Seok-Min,Kim, Jinhoon,Jeong, Euigyung,Im, Ji Sun,Lee, Young-Seak 한국공업화학회 2011 공업화학 Vol.22 No.1
본 연구에서는 난분해성 유기물질의 광분해능을 증가시키고자 다양한 산 촉매 및 마이크로웨이브법으로 아나타제/브루카이트 혼성형 $TiO_2$ 광촉매를 제조하였다. 또한 그에 따른 입자 및 결정크기와 브루카이트 분율에 따른 메틸렌블루의 광분해특성을 고찰하였다. 아나타제/브루카이트 혼성형 $TiO_2$ 광촉매의 표면특성 및 입자크기는 주사전자현미경과 레이저회절 입도분석기를 통하여 평가하였고, 결정구조는 X선 회절장치를 통하여 확인하였다. 메틸렌블루의 광분해 특성은 자외선 가시광선 분광광도계를 통하여 확인하였다. 주사전자현미경과 레이저회절 입도분석결과로부터 아나타제 및 아나타제/브루카이트 혼성형 $TiO_2$ 광촉매는 약 500 nm 이하의 클러스터 형태의 입자크기 나타내었고, 평균입자 크기는 $6.66{\sim}6.85{\mu}m$로 산 촉매 종류에 의한 영향은 크지 않음을 알 수 있었다. 산 촉매의 종류 및 마이크로웨이브법으로 제조된 $TiO_2$ 광촉매는 XRD 분석결과로부터 아나타제/브루카이트 혼성형 결정구조를 나타내었고 그 결정구조는 마이크로웨이브 조사시간의 증가에 따라서 변화하지 않았다. 메틸렌블루의 광분해능 실험결과로부터 광분해능은 브루카이트 분율 및 결정크기에 비례하지 않았으며, 브루카이트 분율 및 결정크기가 적정치 이상이 되면 오히려 촉매활성이 저하되는 경향성을 나타내었다. 본 연구결과에서는 브루카이트 분율 및 결정크기가 9.4%, 4.53 nm인 아나타제/브루카이트 혼성형 $TiO_2$ 광촉매가 가장 우수한 광분해능을 나타내었다. In this study, anatase/brookite hybrid $TiO_2$ was prepared using different acid catalysts and microwave to improve photodegradation of organic pollutants. The methylene blue photodegradation properties of the prepared photocatalysts with different particle/crystal size and brookite fractions were investigated. Surface characteristics and particle sizes of anatase/brookite hybrid $TiO_2$ were evaluated using scanning electron microscopy (SEM) and laser diffraction particle size analyzer, respectively and crystal structures were investigated with X-ray diffraction (XRD). Methylene blue photodegradation properties were evaluated with UV-vis spectrophotometer. Anatase and anatase/brookite hybrid $TiO_2$ had less than 500 nm size of clusters and the average particle size of $6.66{\sim}6.85{\mu}m$, suggesting that types of acid catalysts did not affect the size. XRD of the prepared $TiO_2$ showed that the photocatalysts had anatase/brookite hybrid crystal structure and applying microwave did not change their crystal structure. Photodegradation of methylene blue with the prepared photocatalyst did not increased proportionally to the fraction of brookite and the crystal size and decreased when brookite fraction and the crystal size increased further. Anatase/brookite hybrid $TiO_2$ with brookite fraction of 9.4% and crystal size of 4.53 nm shows the best photodegradation activity of methylene blue.