• Proceedings of the Korean Vacuum Society Conference
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• 2008.02a
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• pp.203-203
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• 2008

• Proceedings of the Korean Vacuum Society Conference
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• 2015.08a
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• pp.132-132
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• 2015

Virtual metrology (VM) model based on plasma information (PI) parameter for C4F8 plasma-assisted oxide etching processes is developed to predict and monitor the process results such as an etching rate with improved performance. To apply fault detection and classification (FDC) or advanced process control (APC) models on to the real mass production lines efficiently, high performance VM model is certainly required and principal component regression (PCR) is preferred technique for VM modeling despite this method requires many number of data set to obtain statistically guaranteed accuracy. In this study, as an effective method to include the 'good information' representing parameter into the VM model, PI parameters are introduced and applied for the etch rate prediction. By the adoption of PI parameters of b-, q-factors and surface passivation parameters as PCs into the PCR based VM model, information about the reactions in the plasma volume, surface, and sheath regions can be efficiently included into the VM model; thus, the performance of VM is secured even for insufficient data set provided cases. For mass production data of 350 wafers, developed PI based VM (PI-VM) model was satisfied required prediction accuracy of industry in C4F8 plasma-assisted oxide etching process.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.1062-1065
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• 2010

Plasma 물성 데이터는 Plasma내에서 일어나는 입자(전자, 원자, 이온, 분자 등)들의 충돌에 대한 데이터로써 Plasma 발생 장치 설계 및 제어의 핵심 요소이며, Plasma 공정조건 확립을 위한 필수 정보가 된다. 참조표준은 과학기술데이터나 정보에 대하여 정확도와 신뢰도에 대한 분석 및 평가가 이루어진 공인데이터를 말한다. 이러한 플라즈마 물성 정보를 체계적으로 관리하고 신뢰성 있는 데이터를 필요로 하는 산업체에 지원하기 위하여 특정 참조표준과 참조데이터로 제정, 보급하는 Plasma 물성 참조표준 수집평가 시스템이 필요하고, 이에 대한 설계가 필요하다.

• Journal of the Semiconductor & Display Technology
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• v.20 no.4
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• pp.146-150
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• 2021

Plasma information based virtual metrology (PI-VM) that predicts wafer-to-wafer etch rate variation after wet cleaning of plasma facing parts was developed. As input parameters, plasma information (PI) variables such as electron temperature, fluorine density and hydrogen density were extracted from optical emission spectroscopy (OES) data for etch plasma. The PI-VM model was trained by stepwise variable selection method and multi-linear regression method. The expected etch rate by PI-VM showed high correlation coefficient with measured etch rate from SEM image analysis. The PI-VM model revealed that the root cause of etch rate variation after the wet cleaning was desorption of hydrogen from the cleaned parts as hydrogen combined with fluorine and decreased etchant density and etch rate.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.551-552
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• 2006

Plasma-induced charging damage was been measured during TaN gate electrode of MISFET(TaN/$HfO_2$/Si) or interconnection metal etching step using large antenna structures. The results of these experiments were obtained that $HfO_2$ gate dielectric layer was affected about plasma charging effects and damage increased with F-N tunneling. Therefore, the etching conditions should be optimized to avoid the defects caused by plasma charging.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.07a
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• pp.930-933
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• 2000

To understand the behavior of electron, ions and radicals on radio-frequency non-equilibrium plasma, it is necessary to know the basic information about its fundamental properties and reactions. Especially, the transient response of radio-frequency plasma has an important means of controlling selective etch rates and investigating the stability of a plasma chemical process. In this paper, we present the results of periodic steady-state behavior and transient behavior carbon Tetrafluoride(CF$_4$) discharge at 0.2 Torr in a 2 cm gap parallel-plate. After the number densities of charged particles became steady-state, the applied voltage was increased or decreased in an instant and the transient behavior of charged particles and radicals was investigated from one steady-state to the next steady state.

• Proceedings of the Korean Vacuum Society Conference
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• 2007.02a
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• pp.88-88
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• 2007

• Applied Science and Convergence Technology
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• v.27 no.1
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• pp.5-8
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• 2018

In this paper, plasma treatment effects on a ploy(dimethyl siloxane) substrate were analyzed for the applications of stretchable silver nanowire (Ag NWs) electrodes. The oxygen plasma treated sample shows the best performance compared to nitrogen treated and untreated samples. The lowest sheet resistance and reasonable stretching capability was achieved up to 20% strain condition without open circuit fail for the oxygen plasma treated sample.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.27-30
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• 2022

The plasma process, which has many advantages in terms of efficiency and environment compared to conventional process methods, is widely used in semiconductor manufacturing. Plasma Sheath is a dark region observed between the plasma bulk and the chamber wall surrounding it or the electrode. The Plasma Sheath Monitoring Sensor (PSMS) measures the difference in voltage between the plasma and the electrode and the RF power applied to the electrode in real time. The PSMS data, therefore, are expected to have a high correlation with the state of plasma in the plasma chamber. In this study, a model for predicting the state of nitrogen ions in the plasma chamber is training by a deep learning machine learning techniques using PSMS data. For the data used in the study, PSMS data measured in an experiment with different power and pressure settings were used as training data, and the ratio, flux, and density of nitrogen ions measured in plasma bulk and Si substrate were used as labels. The results of this study are expected to be the basis of artificial intelligence technology for the optimization of plasma processes and real-time precise control in the future.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.473-473
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• 2010

Plasma is widely used in various commercial etchers and chemical vapor deposition. Unfortunately, real-time plasma process monitoring is still difficult. Some methods of plasma diagnosis is improved, however, it is possible for real-time plasma diagnosis to use non-intrusive probe only. In this research, the object is to investigate the suitability of using impedance analysis and optical emission spectroscopy (OES) for real-time plasma process monitoring. It is assumed that plasma system is a equivalent circuit. Therefore, V-I probe is used for measuring impedance, which can be a new non-intrusive probe for plasma diagnosis. From impedance data, we tried to analyse physical properties of plasma. And OES, the other method of plasma diagnosis, is a typical non-intrusive probe for analyzing chemical properties. The amount of the OES data is typically large, so this poses a difficulty in extracting relevant information. To solve this problem, principal component analysis (PCA) can be used. For fundamental information, Ar plasma and $O_2$ plasma are used in this experiment. This method can be applied to real-time endpoint and fault detections.