Abstract
In moderate-pressure radio frequency (RF) capacitively coupled plasmas generated in argon-methane mixtures, the density of argon metastable atoms (Ar 1 s5) exhibits a non-monotonic dependence on methane (CH4) concentration. Laser-induced fluorescence (LIF) was used to measure and compare local Ar 1 s5 densities in Ar and Ar-CH4 plasmas at 2.6 Torr and RF powers of 17-117 W. The addition of 1% CH4 increases the metastable density, and 2% CH4 triggers a strong depletion by an order of magnitude, compared to 1% CH4 case. This non-monotonic behavior demonstrates the sensitivity of metastable populations to small gas admixtures, which is critical for processes where metastables drive precursor dissociation. For real-time monitoring of metastable population, broadband optical emission spectroscopy (OES) is augmented with a feedforward neural network (NN) to predict Ar s15 densities from spectral features. When trained on LIF data, the NN replicates the absolute densities and the dynamic trends of Ar 1 s5 density variation. The NN-augmented broadband OES approach can be used as a simple and cost-effective tool for tracking Ar metastables in Ar-rich plasmas, facilitating industrial-scale optimization.
| Original language | English (US) |
|---|---|
| Article number | 035007 |
| Journal | Plasma Sources Science and Technology |
| Volume | 35 |
| Issue number | 3 |
| DOIs | |
| State | Published - Mar 1 2026 |
All Science Journal Classification (ASJC) codes
- Condensed Matter Physics
Keywords
- RF capacitively coupled plasma
- argon metastables
- laser-induced fluorescence
- machine learning
- methane plasma chemistry
- optical emission spectroscopy
- real time plasma diagnostics
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