• 한국입자에어로졸학회지
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• 제11권4호
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• pp.93-98
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• 2015

Particles which generated from plasma enhanced chemical vapor deposition (PECVD) during thin film deposition process can affect to the process yield. By using light extinction method, ISPM can measure particles in the large-diameter pipe (${\leq}300mm$). In our research, in-situ particle monitor (ISPM) sensor was installed at the 300 mm diameter exhaust-line to count the particles in each size. In-house flange for mounting the transmitting and receiving parts of ISPM was carefully designed and installed at a certain point of exhaust line where no plasma light affect to the light extinction measurement. Measurement results of trend changes on particle count in each size can confirm that ISPM is suitable for real-time monitoring of vacuum process.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제1권1호
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• pp.87-94
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• 2001

Silicon nitride films grown by plasma-enhanced chemical vapor deposition (PECVD) are useful for a variety of applications, including anti-reflecting coatings in solar cells, passivation layers, dielectric layers in metal/insulator structures, and diffusion masks. PECVD systems are controlled by many operating variables, including RF power, pressure, gas flow rate, reactant composition, and substrate temperature. The wide variety of processing conditions, as well as the complex nature of particle dynamics within a plasma, makes tailoring SiN film properties very challenging, since it is difficult to determine the exact relationship between desired film properties and controllable deposition conditions. In this study, SiN PECVD modeling using optimized neural networks has been investigated. The deposition of SiN was characterized via a central composite experimental design, and data from this experiment was used to train and optimize feed-forward neural networks using the back-propagation algorithm. From these neural process models, the effect of deposition conditions on film properties has been studied. A recipe synthesis (optimization) procedure was then performed using the optimized neural network models to generate the necessary deposition conditions to obtain several novel film qualities including high charge density and long lifetime. This optimization procedure utilized genetic algorithms, hybrid combinations of genetic algorithm and Powells algorithm, and hybrid combinations of genetic algorithm and simplex algorithm. Recipes predicted by these techniques were verified by experiment, and the performance of each optimization method are compared. It was found that the hybrid combinations of genetic algorithm and simplex algorithm generated recipes produced films of superior quality.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2003년도 하계학술대회 논문집 Vol.4 No.2
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• pp.995-998
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• 2003

This paper presents the deposition of poly-Si thin-film and fabrication of a solar cell by VHF-PECVD method. The poly-Si thin films. and pin-type solar cells are fabricated using multi-chamber cluster tool system. A 7.4% conversion efficiency was achieved from poly-Si thin film solar cells with total thickness less than $5{\mu}m$. The physical characteristic was measured by Raman spectroscopy, solar cell characteristic was measured under AM1.5 illumination.

• 조명전기설비학회논문지
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• 제23권7호
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• pp.8-13
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• 2009

Plasma enhanced chemical vapor deposition (PECVD) is commonly used for Carbon nanotubes (CNTs) fabrication, and the process can easily be applied to industrial production lines. In this works, we developed novel magnetized radio frequency PECVD system for one line process of CNTs fabrication for charge storable electrode application. The system incorporates aspects of physical and chemical vapor deposition using capacitive coupled RF plasma and magnetic confinement coils. Using this magnetized RF-PECVD system, we firstly deposited Fe layer (about 200[nm]) on Si substrate by sputter method at the temperature of 300[$^{\circ}$] and hence prepared CNTs on the Fe catalyst layer and investigated fundamental properties by scanning electron microscopy (SEM) and Raman spectroscopy (RS). High-density, aligned CNTs can be grown on Fe/Si substrates at the temperature of 600[$^{\circ}$] or less.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.195-200
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• 1998

Since the neural network was introduced, significant progress has been made on data handling and learning algorithms. Currently, the most popular learning algorithm in neural network training is feed forward error back-propagation (FFEBP) algorithm. Aside from the success of the FFEBP algorithm, polynomial neural networks (PNN) learning has been proposed as a new learning method. The PNN learning is a self-organizing process designed to determine an appropriate set of Ivakhnenko polynomials that allow the activation of many neurons to achieve a desired state of activation that mimics a given set of sampled patterns. These neurons are interconnected in such a way that the knowledge is stored in Ivakhnenko coefficients. In this paper, the PNN model has been developed using the plasma enhanced chemical vapor deposition (PECVD) experimental data. To characterize the PECVD process using PNN, SiO$_2$films deposited under varying conditions were analyzed using fractional factorial experimental design with three center points. Parameters varied in these experiments included substrate temperature, pressure, RF power, silane flow rate and nitrous oxide flow rate. Approximately five microns of SiO$_2$were deposited on (100) silicon wafers in a Plasma-Therm 700 series PECVD system at 13.56 MHz.

• 한국전기전자재료학회논문지
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• 제15권4호
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• pp.367-372
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• 2002

The vertically well-aligned carbon nanotubes(CNTs) were successfully grown on Ni coated silicon wafer substrate by DC bias-assisted PECVD(Plasma Enhanced Chemical Vapor Deposition). As a catalyst, Ni thin film of thickness ranging from 15~30nm was prepared by electron beam evaporator method. In order to find the optimum growth condition, the type of gas mixture such as $C_2H_2-NH_3$ was systematically investigated by adjusting the gas mixing ratio at $570^{\circ}C$ under 0.4Torr. The diameter of the grown CNTs was 40~200nm and the diameter of the CNTs increased with increasing the Ni particles size. TEM images clearly showed carbon nanotubes to be multiwalled. The measured turn-on field was $3.9V/\mu\textrm{m}$ and an emission current of $1.4{\times}10^4A/\textrm{cm}^2$ was $7V/\mu\textrm{m}$. The CNTs grown by bias-assisted PECVD was able to demonstrate high quality in terms of vertical alignment, crystallization of graphite and the processing technique at low temperature of $570^{\circ}C$ and this can be applied for the emitter tip of FEDs.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2004년도 하계학술대회 논문집 Vol.5 No.2
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• pp.951-954
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• 2004

본 논문에서는 DLC(Diamond-like Carbon) 박막과 기판 사이에 금속층을 포함하는 DLC 박막의 기계적 특성을 분석하였다. 금속층은 sputtering법을 사용하고, DLC 박막은 PECVD법을 사용하여 각각 중착하였다. 티타늄(Ti), 니켄(Ni), 크롬(Cr)을 각 중간 금속층으로 사용한 후 DLC 박막과 실리콘(Si) 기판 간의 기계적 특성을 분석하였다. 각 막의 두께는 FE-SEM으로 확인하였고, DLC 박막의 구조 평가는 Raman spectrometer를 사용하여 분석하였으며, 각 금속층과 DLC 박막의 표면 상태는 AFM을 이용하여 확인하였다. XRD 분석을 통하여 박막의 격자분석을 하였고, SIMS(secondary ion mass spectrometry) 분석을 통하여 DLC 박막의 depth Profile을 확인하였다.

• 한국재료학회지
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• 제6권3호
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• pp.324-332
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• 1996

DLC 박막을 RF 플라즈마 화학증착법(PECVD)을 이용하여 CH4와 CO2기체로부터 합성하였다. 증착압력, CH4와 CO2가스의 조성비, 바이어스 전압(-VB) 등의 증착조건 변화에 따른 증착속도는 증착층의 두께를 알파스텝으로 측정하여 결정하였으며, 박막의 구조 변화에 따른 증착속도는 증착층의 두께를 알파스텝으로 측정하여 결정하였으며, 박막의 구조 변화는 FTIR 분광분석을 이용하여 분석을 행하였다. 이 연구로부터 얻은 실험 결과는 다음과 같다: 1) 증착속도는 증착압력 및 바이어스 전압의 증가에 따라 증가한다. 2)바이어스 전압 300V이상에서, CO2량 증가는 순증착속도를 증가 시킨다. 3) 순수한 CH4가스를 사용할 경우에는 바이어스전압(-VB)이 증가함에 따라 박막내 수소의 함량과 sp3/sp2비는 감소하는 경향을 나타낸다. 4)증착압력이 증가함에 따라 박막내 수소함량은 증가하며, sp3/sp2비는 감소한다. 5)50mTorr의 증착압력에 증착시, CH4-+Co2 혼합가스에서 이산화탄소의 부피분율에 따라서는 박막내 수소함량은 감소하며, sp3/sp2비는 증가한다.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2008년도 춘계학술대회 및 기술 세미나 논문집 디스플레이 광소자
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• pp.57-58
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• 2008

Microcrystalline (${\mu}c$) silicon thin films were prepared on glass by plasma-enhanced-chemical-vapor-deposition (PECVD) at various substrate temperature, and dilution ratio of $H_2$ with $SiH_4$. The structural and optical properties of. the ${\mu}c-Si$ thin films were investigated using XRD and UV-VIS spectrophotometer. The ${\mu}c-Si$ thin film with 42 nm grain size was grown at optimal condition of 2.5 Torr, spacing between electrodes of 3cm, deposition time of 3000s, RF power of 200W, substrate temperature of $350^{\circ}C$, $SiH_4$ ($20%SiH_4$+80%He) of 50sccm, and $H_2$ of 100sccm.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2001년도 하계학술대회 논문집
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• pp.935-938
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• 2001

Carbon nanotubes(CNTs) was successfully grown on Ni coated silicon wafer substrate by applying PECVD technique(Plasma Enhanced Chemical Vapor Deposition). As a catalyst, Ni thin film of thickness ranging from 15∼30nm was prepared by electron beam evaporator method. In order to find the optimum growth condition, the type of the gas mixture such as C$_2$H$_2$-NH$_3$was systematically investigated by adjusting the gas mixing ratio in temperature of 600$^{\circ}C$ under the pressure of 0.4 torr. The diameter of the grown CNTs was 40∼150nm. As NH$_3$etching time increased the diameters of the nanotubes decreased whereas the density of nanotubes increased. TEM images clearly demonstrated synthesized nanotubes was multiwalled. We investigated electrical properties for the application of FED.