Downstream etching of silicon nitride using continuous-wave and pulsed remote plasma sources sustained in Ar/NF3/O2 mixtures
Bibliographic record
Abstract
Remote plasma sources (RPSs) are being investigated to produce fluxes of radicals for low damage material processing. In this computational investigation, the properties of a RPS etching system are discussed where an Ar/NF3/O2 gas mixture is flowed through an inductively coupled plasma source into a downstream chamber containing a silicon nitride coated wafer. The plasma is largely confined in the RPS due to the highly attaching NFx (x = 1–3) and an isolating showerhead although a weak ion-ion plasma maintained by [NO+] ≈ [F−] leaks into the downstream chamber. The etching of silicon nitride proceeds through iterative removal of Si and N subsites by isotropic thermal neutrals. When the fluxes to the wafer are rich in fluorine radicals, the etch rate is limited by the availability of NO molecules and N atoms which remove N subsites. As power deposition increases with continuous-wave excitation, the etch rate increases almost linearly with the increasing fluxes of NO and N atoms, as production of NO through endothermic reactions is aided by increasing gas temperature. Production of N atoms through electron impact dissociation of NO and NFx is aided by the increasing electron density. Similar trends occur when increasing the duty cycle during pulsed excitation. Addition of a plenum between the RPS and the downstream chamber aids in lateral diffusion of radicals before passing through the final showerhead and improves the uniformity of etching.
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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) | 0.001 | 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".