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서민현 샘터사 2013 월간 샘터 Vol.522 No.-

수열처리에 의한 TiO₂ 나노 튜브 센서의 가스 검지 특성

서민현,오상진,테츠야 키다,켄고 시마노에,허증수,Seo, Min-Hyun,Oh, Sang-Jin,Kida, Tetsuya,Shimanoe, Kengo,Huh, Jeung-Soo 한국재료학회 2007 한국재료학회지 Vol.17 No.8

Preparation and morphology control of $TiO_2$ nano powders for gas sensor applications are investigated. $TiO_2$ nanopowders with rutile and anatase structures were prepared by controlling the pH value of a precursor solution without any heat treatment. The mean particle size of $TiO_2$ powders were below 10nm. The prepared $TiO_2$ nano powders were hydrothermal treated by NaOH solution. The sample was washed in HCl solution. As a result and $TiO_2$ nanotubes were formed. The lengths of $TiO_2$ nanotube were $1{\mu}m$ and the diameters were 10nm. Crystal structure and microstructure of $TiO_2$ nanotube were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM) and transmission electron microscope (TEM). As-prepared $TiO_2$ nanotube powders have several advantages of nano particle size and high surface area and could be a prominent candidate for nano-sensors. The sensitivity of $TiO_2$ nanotube sensor was measured for toluene and NO in this study.

공공주도 대규모 해상풍력 발전단지의 개발 전략

서민현(Minhyun Seo),이정림(Jeonglim LEE),김상준(Sangjun Kim),김성완(Sungwan Kim) 한국신재생에너지학회 2019 한국신재생에너지학회 학술대회논문집 Vol.2019 No.5

보호계전기 동작 시뮬레이션 방법 및 장치 개발

서민현(Min-Huyn Seo),김영우(Young-Woo Kim),이상욱(SangWook Lee) 대한전기학회 2020 대한전기학회 학술대회 논문집 Vol.2020 No.7

Association Between Body Mass Index and Asthma Symptoms Among Korean Children: A Nation-Wide Study

서민아,김호현,최동필,김경원,손명현,하경화,황원주,김창수,김규언,신동천,박수경,강대희 대한의학회 2011 Journal of Korean medical science Vol.26 No.12

The purpose of this study was to investigate the association between body mass index (BMI)and the prevalence of wheeze using nation-wide cross-sectional study in Korean children. Total 50,200 children from 427 elementary schools were randomly selected according to residential areas (metropolitan, provincial, rural, and industrial areas) by the cluster sampling method. The International Study of Asthma and Allergies in Childhood (ISAAC)questionnaires were used to measure the prevalence of wheeze. Among 31,026respondents, 25,322 were analyzed. BMI was classified into quartiles based on BMI-forage percentile. In all residential areas, pets at home and visible mold or moisture were associated with an increased prevalence of wheeze in both genders. However, other living environment factors were not consistently associated among residential areas and gender. Among girls, lowest BMI was negatively associated with prevalence of wheeze and highest BMI was positively associated in all residential areas. In multilevel logistic regression analysis, environmental tobacco smoking exposure, pets at home, visible mold or moisture, and being in the lowest and highest BMI quartile were significantly associated with the prevalence of wheeze in both genders. BMI has become an important risk factor for asthma symptoms among Korean children.

심층신경망을 이용한 3D Vertical SONOS NAND Flash의 Grain Boundary Distribution과 Geometrical Variation에 의한 전기적 특성 변동 분석

하종현,방민지,이다복,서민기,류민상,김정식 대한전자공학회 2024 전자공학회논문지 Vol.61 No.4

Planar 형태의 NAND Flash memory의 Scaling down의 한계로 3D Vertical Silicon-Oxide-Nitride-Oxide-Silicon (SONOS) NAND가 개발되었다. 3D Vertical SONOS NAND로 한정된 크기의 wafer에서 많은 transistor를 적층하여 planar type보다 더 많은 memory capacity를 확보할 수 있다. 하지만 vertical 구조로 변경되면서 공정 난이도 상승과 함께 공정에 소모되는 비용이 증가했다. 그래서 공정에 투입되는 비용을 줄이고 소자의 전기적 특성을 빠르고 정확하게 예측하는 기술의 필요성이 대두되었다. 본 논문에서는 TCAD simulation과 딥러닝을 통해 3D Vertical SONOS NAND의 polysilicon grain boundary distribution (Max-angle, Ycut, Xseed, Yseed, Aseed)과 geometrical variation (Width, Lcg)에 따른 전기적 특성 (Vtgm, Vti) 변동을 예측하고 분석했다. TCAD simulation 결과값을 바탕으로 학습한 딥러닝을 통해 전기적 특성을 예측했고 매우 높은 수치의 R2 score (Vtgm R2 score = 0.997, Vti R2 score = 0.999)로 TCAD simulation 결과값에 수렴한다는 것을 알 수 있다. 또한 SHapley Additive exPlanations (SHAP) value를 통해 input parameter의 중요도를 평가한 결과 Ycut과 Xseed parameter가 전기적 특성 변동에 가장 많은 영향을 준 것을 확인했다. 3D Vertical Silicon-Oxide-Nitride-Oxide-Silicon (SONOS) NAND was developed as a solution to the scaling down of planar-type NAND Flash memory. With 3D Vertical SONOS NAND, it is possible to stack many transistors on a limited-size wafer to secure more memory capacity than the planar type. However, with the change to the vertical structure, the cost of the process has increased along with the increase in process difficulty. Therefore, there is a need for a technology that reduces the process's cost and predicts the device's electrical characteristics quickly and accurately. In this paper, we used TCAD simulation and deep learning to predict and analyze the variation of electrical characteristics (Vtgm and Vti) of 3D Vertical SONOS NAND due to polysilicon grain boundary distribution (Max-angle, Ycut, Xseed, Yseed, Aseed) and geometrical variation (Width, Lcg). The electrical characteristics were predicted using deep learning trained based on TCAD simulation results and converged to TCAD simulation results with very high R2 scores (Vtgm R2 score = 0.997, Vti R2 score = 0.999). We also evaluated the importance of the input parameters through the SHapley Additive exPlanations (SHAP) value. We found that the Ycut and Xseed had the most influence on the variation of electrical characteristics.

Prevalence of Allergic Diseases among Korean School-age Children: A Nationwide Cross-Sectional Questionnaire Study

서민아,김호현,손명현,김규언,김창수,신동천 대한의학회 2011 Journal of Korean medical science Vol.26 No.3

The purpose of this study was to investigate the nationwide prevalence of childhood asthma, eczema and other allergic diseases in Korean school-age children (8-11 yr old) and to assess the difference between residential areas. Among 6,279 elementary schools, 427schools were randomly selected according to residential area (metropolitan, provincial,rural, and industrial area) by the cluster sampling method. Parents of students completed a modified Korean version of a questionnaire formulated by the International Study of Asthma and Allergies in Childhood (ISAAC). Among 50,200 subjects, 31,026 (61.8%)responded, and 30,893 (99.6%) were analyzed. The 12-month prevalence of wheeze,flexural rash, and allergic rhinitis symptoms were 4.8%, 15.3%, and 32.9%, respectively. The prevalence of diagnosis of allergic diseases in boys was higher than that in girls, with the exception of eczema. In both boys and girls, the difference of the prevalence of allergic diseases among industrial, metropolitan and provincial areas was not statistically significant, but the differences between rural area and other areas were significant. Our results support the importance of contextual effect associated with residential area as causative agents of allergic diseases among Korean school-age children.

Triamcinolone Acetonide가 배양 켈로이드 섬유아세포의 G1 세포주기 관련 유전자 발현에 미치는 영향

설정현,우상현,백원기,서성일,서민호 大韓成形外科學會 1998 Archives of Plastic Surgery Vol.25 No.2

The effect of triamcinolone acetonide(TA) on the expression of Gl related genes was investigated the cultured keloid fibroblast. The addition of TA to the culture medium resulted in growth inhibition of keloid fibroblast. TA reduced the expression of cyclin A, B, E and cyclin dependent kinase(CDK) 2 mRNA, but unexpectedly, the expression of cyclin C, Dl and CDK4 mRAN was not affected significantly as compared with those of normal fibroblast. Expressions of p16, p21 and p27, the wellestabilished CDK-inhibitors, were also investigated. The level of p16 was not detected in both normal and keloid fibroblasts and the expression of p27 was significantly decreased in keloid fibroblast. The expression of p21 was dramatically increased in keloid fibroblast but not significantly changed in normal fibroblast. Also the expressions of p53 and pRb, the well known tumor suppressor genes, were increased by the addition of TA. These data suggested that the observed growth inhibitory effect of TA may be related to transcriptional inactivation of cyclin A, B, E and CDK2 and to the transcriptional activation of p21, but the mechanisms of unchanged expression of cyclin C, Dl and CDK4 mRNA remain to be elucidated.

심층신경망을 이용한 Nanowire FETs의 공정 조건 특성 예측

하종현(Jonghyeon Ha),이경엽(Gyeongyeop Lee),서민기(Minki Suh),방민지(Minji Bang),김태형(Tae Heoung Kim),김정식(Jungsik Kim) 대한전자공학회 2022 전자공학회논문지 Vol.59 No.12

FinFET(Fin Field Effect Transistor) 이후 차세대 logic 반도체 GAAFET (Gate All Around Field Effect Transistor)인 NWFET (Nanowire FET) 그리고 NSFET (Nanosheet FET)이 주목받고 있다. 우수한 성능을 지닌 GAAFET은 이전 logic 반도체들보다 매우 높은 수준의 공정 난이도를 지닌다. 공정 난이도가 높아질수록 개발단계에서 더 많은 공정 시간 및 금액이 발생한다. 이러한 높은 비용이 투입되는 반도체 개발에 머신러닝을 도입하면 더 적은 비용 및 시간으로 공정을 진행할 수 있다. 본 논문에서는 Synopsys 사 TCAD (Technology Computed-Aided Design) Sentaurus tool과 QTX tool을 활용하여 추출한 NWFET dataset을 DNN (Deep Neural Network) 통해 반도체 소자의 parameter 변화에 따른 전기적 특성 변동에 대해 forward prediction 및 reverse prediction 사용하여 예측 및 분석하였다. Forward prediction에서는 낮은 MSE (Mean Square Error) loss 로 예측을 잘 하였지만, reverse prediction 내 D (원의 직경), W<SUB>top</SUB> (사다리꼴 윗변), Shape (Nanowire 모양), Scattering 예측과 달리 cDir (채널 격자 방향) 및 nSubbands (subband의 개수) 예측에서 cDir 및 nSubbands 변화에 따른 전기적 특성 변동 비율이 낮아 분포가 고르게 나타나지 않아 낮은 예측률을 보였다. Since FinFET (Fin Field Effect Transistor), NWFET (Nanowire FET), the next-generation logic semiconductor GAAFET (Gate All Around Field Effect Transistor), and NSFET (Nanosheet FET) have been in the spotlight. GAAFET with excellent performance has a very high level of process difficulty compared to previous logic semiconductors. As the difficulty level of the process increases, more process time and amount of money are generated in the development stage. If machine learning is introduced into such high-cost semiconductor development, the process can proceed with less cost and time. In this paper, the NWFET dataset extracted using Synopsys TCAD (Technology Computed-Aided Design) Sentaurus tool and QTX tool was predicted and analyzed using forward prediction and reverse prediction for the variation of electrical characteristics according to parameter change of semiconductor devices through DNN (Deep Neural Network). Forward prediction is well predicted with low MSE (Mean Square Error) loss, but Unlike the predictions of D (diameter of circle), W<SUB>top</SUB> (top of trapezoid), Shape (Nanowire shape), and Scattering in the Reverse prediction, the rate of change in electrical characteristics because change in cDir (channel direction) and nSubbands (the number of subbands) was low in the predictions of cDir and nSubbands, and thus the distribution was not uniform.

심층신경망을 이용한 Total Ionizing Dose 및 Displacement Defect에 의한 Saddle Fin DRAM의 열화 특성 예측

류민상,하종현,이경엽,서민기,방민지,이다복,김정식 대한전자공학회 2023 전자공학회논문지 Vol.60 No.11

본 논문에서는 saddle fin dynamic random access memory (DRAM) 에 대한 total ionizing dose (TID) 와 displacement defect (DD) 영향을 Technology Computer-Aided Design (TCAD) simulation과 deep neural network (DNN) 를 사용해 조사하였다. Trap의 energy level, 농도, 위치 그리고 면적을 변수로 설정하였고, TCAD를 사용하여 saddle fin DRAM의 전류-전압 특성 dataset을 생성하였다. TCAD dataset을 전처리 과정을 거친 경우와 전처리를 하지 않은 경우로 나누어 DNN의 예측 정확도를 비교하였다. 그 결과 전처리 과정을 거쳐 훈련된 모델은 전처리 과정을 하지 않은 훈련 모델보다 mean square error (MSE) loss가 80 % 증가함과 동시에 R2 score가 37 % 증가하였다. 따라서 DNN을 활용한 정확한 예측을 위해서는 전처리 과정이 필수적이다. In this paper, the effects of total ionizing dose (TID) and displacement defect (DD) in saddle fin dynamic random access memory (DRAM) are investigated using technology computer-aided design (TCAD) simulation and deep neural network (DNN). TCAD is used for generating the current-voltage characteristic data of the saddle fin DRAM and the energy level, concentration, location, and area of the trap are utilized for variables. The TCAD dataset is divided into preprocessed and un-processed cases to compare the prediction accuracy of DNN. The result shows that the model trained with preprocessing has an 80 % increase in mean square error (MSE) loss and a 37 % increase in R2 score compared to the training model without preprocessing. Therefore, preprocessing of a dataset is necessary for high prediction accuracy using DNN.