• 한국표면공학회지
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• 제41권4호
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• pp.134-141
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• 2008

We have developed a numerical model for a remote ICP(inductively coupled plasma) system in 2D and 3D with gas distribution configurations and confirmed it by plasma diagnostics. The ICP source has a Cu tube antenna wound along a quartz tube driven by a variable frequency rf power source($1.9{\sim}3.2$ MHz) for fast tuning without resort to motor driven variable capacitors. We investigated what conditions should be met to make the plasma remotely localized within the quartz tube region without charged particles' diffusing down to a substrate which is 300 mm below the source, using the numerical model. OES(optical emission spectroscopy), Langmuir probe measurements, and thermocouple measurement were used to verify it. To maintain ion current density at the substrate less than 0.1 $mA/cm^2$, two requirements were found to be necessary; higher gas pressure than 100 mTorr and smaller rf power than 1 kW for Ar.

• Nuclear Engineering and Technology
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• 제25권1호
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• pp.136-147
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• 1993

본 논문은 다음의 내용을 기술한다 : ⅰ) 토카막 플라즈마의 경계면을 정의하고 계산하는 폴로이달 자속의 수학적 모형을 플라즈마경계면과 등자속면이 일치한다는 사실로부터 수립한다. 따라서 플라즈마의 경계위치를 제어한다 함은 리미터 접선상의 여러 점들에서 자속값을 같게 만드는 것을 의미한다. ⅱ) 자속, 자장, 자장구배의 선형조합으로 최외각 폴로이달 등자속면을 측정하는 방법을 제시한다. 이 방법은 내부플라즈마변수를 알 필요가 없어서 폴로이달베타와 플라즈마전류분포의 변동에 따르는 수정이나 진공용기의 유도전류를 보상하지 않아도 된다. ⅲ) 플라즈마의 경계면 위치조정을 위한 궤환제어 알고리즘을 수립하고, PID 제어이론을 기초로 해당 전자장비를 제작한다. ⅳ) 본 플라즈마 제어계를 사용한 RTP토카막 실험의 결과를 논의한다.

• 전기학회논문지
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• 제56권9호
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• pp.1626-1631
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• 2007

This paper presents a new modeling method using lamp output power and the modeling coefficients of the lamp. The proposed method utilizes the lamp modeling coefficients such as equivalent impedance Z(p), coupling coefficient of the transformer k(p), turns ratio of the transformer n(p), and plasma resistance Rp(p) as a function of lamp output power. The equivalent impedance Z(p) was developed from the equivalent resistance Req(p) and equivalent inductance Leq(p) of the lamp. Simulation and experimental results of the proposed model are presented in order to validate the proposed method. The modeling method can use to design an impedance matching circuit for a Class-D inverter.

• ETRI Journal
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• 제30권3호
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• pp.383-393
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• 2008

The etching mechanism of $ZrO_2$ thin films and etch selectivity over some materials in both $BCl_3$/Ar and $BCl_3/CHF_3$/Ar plasmas are investigated using a combination of experimental and modeling methods. To obtain the data on plasma composition and fluxes of active species, global (0-dimensional) plasma models are developed with Langmuir probe diagnostics data. In $BCl_3$/Ar plasma, changes in gas mixing ratio result in non-linear changes of both densities and fluxes for Cl, $BCl_2$, and ${BCl_2}^+$. In this work, it is shown that the non-monotonic behavior of the $ZrO_2$ etch rate as a function of the $BCl_3$/Ar mixing ratio could be related to the ion-assisted etch mechanism and the ion-flux-limited etch regime. The addition of up to 33% $CHF_3$ to the $BCl_3$-rich $BCl_3$Ar plasma does not influence the $ZrO_2$ etch rate, but it non-monotonically changes the etch rates of both Si and $SiO_2$. The last effect can probably be associated with the corresponding behavior of the F atom density.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.664-667
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• 1997

For higher component density per chip, it is necessary to identify and control the semiconductor manufacturing process more stringently. Recently, neural networks have been identified as one of the most promising techniques for modeling and control of complicated processes such as plasma etching process. Since wafer states after each run using identical recipe may differ from each other, conventional neural network models utilizing input factors only cannot represent the actual state of process and equipment. In this paper, in addition to the input factors of the recipe, real-time tool data are utilized for modeling of 64M DRAM s-poly plasma etching process to reflect the actual state of process and equipment. For real-time tool data, we collect optical emission spectroscopy (OES) data. Through principal component analysis (PCA), we extract principal components from entire OES data. And then these principal components are included to input parameters of neural network model. Finally neural network model is trained using feed forward error back propagation (FFEBP) algorithm. As a results, simulation results exhibit good wafer state prediction capability after plasma etching process.

• Nuclear Engineering and Technology
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• 제53권7호
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• pp.2251-2260
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• 2021

The motion control of the divertor maintenance system of the China Fusion Engineering Test Reactor (CFETR) was studied in this paper, in which CFETR Multi-Functional Maintenance Platform (MFMP) was simplified as a parallel robot for the convenience of theoretical analysis. In order to design the motion controller of parallel robot, the kinematics analysis of parallel robot was carried out. After that, the dynamic modeling of the hydraulic system was built. As the large variation of heavy payload on MFMP and highly nonlinearity of the system, A Fuzzy-PID controller was built for self-tuning PID controller parameters by using Fuzzy system to achieve better performance. In order to test the feasibility of the Fuzzy-PID controller, the simulation model of the system was built in Simulink. The results have showed that Fuzzy-PID controller can significantly reduce the angular error of the moving platform and provide the stable motion for transferring the divertor.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1485-1488
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• 1997

The capacity of memory chip has increased vert quickly and 64MDRAM becomes main product in semiconductor manufacturing lines consists of many sequential processes, including etching process. although it needs direct sensing of wafer state for the accurae detching, it depends on indirect esnsing and sample test because of the complexity of the plasma etching. This equipment receives the inner light of etch chamber through the viewport and convets it to the voltage inetnsity. In this paper, EDP voltage signal has a new role to detect etching failure. First, we gathered data(EPD sigal, etching time and etchrate) and then analyzed the relationships between the signal variatin and the etch rate using two neural network modeling. These methods enable to predict whether ething state is good or not per wafer. For experiments, it is used High Density Inductive coupled Plasma(HDICP) ethcing equipment. Experiments and results proved to be abled to determine the etching state of wafer on-line and analyze the causes by modeling and EPD signal data.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.252-258
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• 1995

The purpose of this study is to provide the integrated process control system, utilizing neural network modeling, to search for the appropriate choice input, and to keep the process output within the desired rang in the real etch process.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1996년도 추계학술대회 학술발표 논문집
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• pp.234-238
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• 1996

In this paper, Plasma-Enhanced Chemical Vapor Deposition (PECVD) modeling using Polynomial Neural Networks (PNN) has been introduced. The deposition of SiO2 was characterized via a 25-1 fractional factorial experiment, was used to train PNNs using predicted squared error (PSE). The optimal neural network structure and learning parameters were determined by means of a second fractional factorial experiment. The optimized networks minimized both learning and prediction error. From these PNN process models, the effect of deposition conditions on film properties has been studied. The deposition experiments were carried out in a Plasma Therm 700 series PECVD system. The models obtained will ultimately be used for several other manufacturing applications, including recipe synthesis and process control.

• Applied Science and Convergence Technology
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• 제23권3호
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• pp.139-144
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• 2014

GaN deposition equipment and processes for the fabrication of white LEDs (Light Emitting Diode) using MOCVD (Metal Organic Chemical Vapor Deposition) were numerically modeled to analyze the effects of a reactive gas introduction strategy. The source gases, TMGa and $NH_3$, were injected from a shower head at the top of the chamber; the carrier gases, $H_2$ or $N_2$, were introduced using two types of injection structures: vertical and horizontal. Wafers sat on the holder at a radial distance between 100 mm and 150 mm. The non-uniformity of the deposition rates for vertical and horizontal injection were 4.3% and 3.1%, respectively. In the case of using $H_2$ as a carrier gas instead of $N_2$, the uniform deposition zone was increased by 20%.