A method of electron density of positive column diagnosis—Combining machine learning and Langmuir probe

Langmuir probe data obtained during the storm period March 20–23, 1990, on board the MAGION-2 subsatellite of the ACTIVNY experiment are analyzed to study the plasmaspheric and ionospheric response to a magnetic storm. The data indicate a well-pronounced equatorward edge of the electron density trough in the afternoon (18:15 LT) at about 800 km height that moves towards lower latitudes during the course of the storm. It is interesting to note that the electron density inside the plasmasphere is increased by more than 20% in the morning shortly after sunrise (07:30 LT). This is due to enhanced O+ densities in the lower plasmasphere during the growth phase of the geomagnetic storm as measured by the ion mass spectrometer NAM-5 onboard the main satellite. It is suggested that the source for the increased density is thermospheric Joule heating at auroral latitudes with a commensurate increase in thermospheric pressure. This increased pressure causes the local thermosphere to expand both upward and equatorward. The increased atomic-oxygen scale height coupled with equatorward motion of fhermospheric perturbations results in an increased O density and resulting O+ density within the lower plasmasphere. The observations indicate a storm-induced compression of the plasmasphere that favourizes an enhanced outflow of plasma into the ionosphere leading to an increased nighttime F2-layer ionization and a depletion of the plasmasphere during the following hours.

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

Coatings ◽

10.3390/coatings11101221 ◽

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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Diagnostics of low-pressure capacitively coupled RF discharge argon plasma

Iraqi Journal of Physics (IJP) ◽

10.30723/ijp.v13i27.266 ◽

2019 ◽

Vol 13 (27) ◽

pp. 76-82

Author(s):

Kadhim A. Aadim

Keyword(s):

Electron Temperature ◽

Electron Density ◽

Langmuir Probe ◽

Gas Flow ◽

Low Pressure ◽

Gas Pressure ◽

Rf Discharge ◽

Electrode Gap ◽

Probe Characteristic ◽

Capacitively Coupled

Low-pressure capacitively coupled RF discharge Ar plasma has been studied using Langmuir probe. The electron temperature, electron density and Debay length were calculated under different pressures and electrode gap. In this work the RF Langmuir probe is designed using 4MHz filter as compensation circuit and I-V probe characteristic have been investigated. The pressure varied from 0.07 mbar to 0.1 mbar while electrode gap varied from 2-5 cm. The plasma was generated using power supply at 4MHz frequency with power 300 W. The flowmeter is used to control Argon gas flow in the range of 600 standard cubic centimeters per minute (sccm). The electron temperature drops slowly with pressure and it's gradually decreased when expanding the electrode gap. As the gas pressure increases, the plasma density rises slightly at low gas pressure while it drops little at higher gas pressure. The electron density decreases rapidly with expand distances between electrodes.

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Comparison between Langmuir Probe and Microwave Electron Density Measurements in an Arc-Heated Low-Density Wind Tunnel

The Physics of Fluids ◽

10.1063/1.1706773 ◽

1963 ◽

Vol 6 (4) ◽

pp. 559 ◽

Cited By ~ 5

Author(s):

L. Talbot ◽

J. E. Katz ◽

C. L. Brundin

Keyword(s):

Wind Tunnel ◽

Electron Density ◽

Langmuir Probe ◽

Low Density ◽

Density Measurements

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Identifying possible Stratification phenomenon in ionospheric F2 Layer using the data observed by the Demeter satellite: Method and Results

10.5194/angeo-2019-55 ◽

2019 ◽

Author(s):

Xiuying Wang ◽

Dehe Yang ◽

Dapeng Liu ◽

Wei Chu

Keyword(s):

Statistical Method ◽

Electron Density ◽

Langmuir Probe ◽

Geomagnetic Equator ◽

Density Data ◽

Demeter Satellite ◽

Summer Hemisphere ◽

First Time ◽

Different Altitudes

Abstract. Many studies have revealed the stratification phenomenon of the topside ionospheric F2 layer using ground-based or satellite-based ionograms, which can show direct signs of this phenomenon. However, it is difficult to identify this phenomenon using the satellite-based in situ electron density data. Therefore, a statistical method, using the shuffle resampling skill, is adopted in this paper. For the first time, in situ electron density data, recorded by the same Langmuir probe onboard the Demeter satellite at different altitudes, are analyzed and a possible stratification phenomenon is identified using the proposed method. Our results show that the nighttime stratification, possibly a permanent phenomenon, can cover most longitudes near the geomagnetic equator, which is not found from the daytime data. The arch-like nighttime stratification decreases slowly on the summer hemisphere and thus extends a larger latitudinal distance from the geomagnetic equator. All results, obtained by the proposed method, indicate that the stratification phenomenon is more complex than what has previously been found. The proposed method thus is an effective one, which can also be used on similar studies of comparing fluctuated data.

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Identifying a possible stratification phenomenon in ionospheric F2 layer using the data observed by the DEMETER satellite: method and results

Annales Geophysicae ◽

10.5194/angeo-37-645-2019 ◽

2019 ◽

Vol 37 (4) ◽

pp. 645-655 ◽

Cited By ~ 1

Author(s):

Xiuying Wang ◽

Dehe Yang ◽

Dapeng Liu ◽

Wei Chu

Keyword(s):

Electron Density ◽

Langmuir Probe ◽

Geomagnetic Equator ◽

Density Data ◽

Demeter Satellite ◽

Summer Hemisphere ◽

Electro Magnetic ◽

First Time ◽

Different Altitudes

Abstract. Many studies have revealed the stratification phenomenon of the topside ionospheric F2 layer using ground-based or satellite-based ionograms, which can show direct signs of this phenomenon. However, it is difficult to identify this phenomenon using the satellite-based in situ electron density data. Therefore, a statistical method, using the shuffle resampling skill, is adopted in this paper. For the first time, in situ electron density data, recorded by the same Langmuir probe aboard the DEMETER (Detection of Electro-Magnetic Emission Transmitted from Earthquake Regions) satellite at different altitudes, are analyzed, and a possible stratification phenomenon is identified using the proposed method. Our results show that the nighttime stratification, possibly a permanent phenomenon, can cover most longitudes near the geomagnetic equator, which is not found from the daytime data. The arch-like nighttime stratification decreases slowly on the summer hemisphere and thus extends a larger latitudinal distance from the geomagnetic equator. All results, obtained by the proposed method, indicate that the stratification phenomenon is more complex than what has previously been found. The proposed method is thus an effective one, which can also be used in similar studies of comparing fluctuated data.

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