Time-resolved Optical Emission Spectroscopy measurements of electron density and temperature in CO2 Nanosecond Repetitively Pulsed discharges

2022 ◽  
Author(s):  
Jean Maillard ◽  
Erwan Pannier ◽  
Christophe O. Laux
Keyword(s):  
Electron Density ◽  
Emission Spectroscopy ◽  
Optical Emission Spectroscopy ◽  
Optical Emission ◽  
Time Resolved ◽  
Pulsed Discharges ◽  
Electron Density And Temperature

Time-resolved optical emission spectroscopy in CO2 nanosecond pulsed discharges

2021 ◽  
Author(s):  
Matteo Ceppelli ◽  
Antoine Salden ◽  
Luca Matteo Martini ◽  
Giorgio Dilecce ◽  
Paolo Tosi
Keyword(s):  
Emission Spectroscopy ◽  
Optical Emission Spectroscopy ◽  
Optical Emission ◽  
Time Resolved ◽  
Pulsed Discharges

Spatiotemporal optical emission spectroscopy to estimate electron density and temperature of plasmas in solution

2020 ◽  
Vol 53 (23) ◽  
pp. 235202 ◽  
Author(s):  
Kenichi Inoue ◽  
Shion Takahashi ◽  
Noritaka Sakakibara ◽  
Susumu Toko ◽  
Tsuyohito Ito ◽  
...  
Keyword(s):  
Electron Density ◽  
Emission Spectroscopy ◽  
Optical Emission Spectroscopy ◽  
Optical Emission ◽  
Electron Density And Temperature

scholarly journals Machine Learning Prediction of Electron Density and Temperature from Optical Emission Spectroscopy in Nitrogen Plasma

Coatings ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 1221
Author(s):  
Jun-Hyoung Park ◽  
Ji-Ho Cho ◽  
Jung-Sik Yoon ◽  
Jung-Ho Song
Keyword(s):  
Machine Learning ◽  
Electron Temperature ◽  
Real Time ◽  
Electron Density ◽  
Emission Spectroscopy ◽  
Optical Emission Spectroscopy ◽  
Optical Emission ◽  
Plasma Parameters ◽  
Plasma Nitridation

We present a non-invasive approach for monitoring plasma parameters such as the electron temperature and density inside a radio-frequency (RF) plasma nitridation device using optical emission spectroscopy (OES) in conjunction with multivariate data analysis. Instead of relying on a theoretical model of the plasma emission to extract plasma parameters from the OES, an empirical correlation was established on the basis of simultaneous OES and other diagnostics. Additionally, we developed a machine learning (ML)-based virtual metrology model for real-time Te and ne monitoring in plasma nitridation processes using an in situ OES sensor. The results showed that the prediction accuracy of electron density was 97% and that of electron temperature was 90%. This method is especially useful in plasma processing because it provides in-situ and real-time analysis without disturbing the plasma or interfering with the process.

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