In Plasma ion beam analysis of polymer layer and adsorbed H monolayer etching
Bibliographic record
Abstract
We present two experiments where a layer is plasma-etched while monitoring its evolution by in plasma ion beam analysis. First, we etch a photoresist with a diffuse O2 plasma at low pressure. Using a 4.335 MeV He beam, Rutherford Backscattering Spectrometry and Elastic Recoil Detection spectra are acquired every minute during 8 h. Etching of most elements follows a linear trend, but H desorbs faster at the beginning of the plasma process, which we ascribe to the ion beam-induced desorption. In addition, we observe a thin Mo layer building up at the surface, likely due to the sputtering of an electrode in the plasma source. Secondly, we etch in HF a crystalline Si (c-Si) sample with <100> surface orientation, which should leave 14 H/nm2 bonded to the c-Si surface. The sample is then introduced in the chamber and exposed to a diffuse Ar plasma at low pressure. During plasma processing, the H surface concentration is monitored using a resonant nuclear reaction with a 15N beam at 6.385 MeV. The initial H concentration is 11.7±1.1 H/nm2, and it decreases over a 3-minute timescale to an equilibrium concentration of 6.0±0.8 H/nm2. Over the range of experimental conditions investigated, the diffuse Ar plasma is therefore not able to entirely sputter the H from the c-Si surface.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".