연도 2018 
저널명 IEEE Transactions on Semiconductor Manufacturing 
232-241 
Abstract—A phenomenological-based virtual metrology (VM) technique is developed for predicting the silicon nitride film thickness in multi-layer plasma-enhanced chemical vapor deposition (PECVD). Particularly, the analysis of optical emission spectroscopy based on the excitation kinetics in nitrogen plasma is used to develop novel variables, named plasma-information (PI) variables. One variable, PIWall, is determined by analyzing the light transmittances of the nitrogen emissions at the contaminated window, representing the drift of reactor-wall condition. The other variable, PIVolume, is determined by analyzing vibrational distribution of N2(C, ν = 0 − 4) states, representing the drift of plasma density and temperature. These PI variables are applied as part of input variables of VM to improve the prediction accuracy. The partial least squares regression is adopted as the statistical method and the contribution of PI variables on the VM are evaluated through the variable influence evaluation on projection. It demonstrates the necessity of PI variables in VM for PECVD and the reactor-wall condition is a major cause of drift in PECVD.

연도 저널명 제목 조회 수
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2020  Physics of Plasmas  Predictive Control of the Plasma Processes in the OLED Display Mass Production Referring to the Discontinuity Qualifying PI-VM 3785
2019  IAEA CRP report  Evaluation of tritium inventory in irradiated tungsten by atomic-scale modeling 599
2019  Current Applied Physics  Characteristics of a plasma information variable in phenomenology-based, statistically-tuned virtual metrology to predict silicon dioxide etching depth 619
2019  Scientific Reports  Quantitation of the ROS production in plasma and radiation treatments of biotargets 930

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