A Hydrogen Plasma Treatment for Soft and Selective Silicon Nitride Etching
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this paper, the development of a soft and selective method to increase the etching rate and control accurately the etched thickness of Si 3 N 4 material is reported. This technique combines the low damage characteristics of wet etching with the anisotropy of plasma etching which is compatible with the requirements of many surface sensitive electronic devices such as MOS transistors. This consists on a local modification of the Si 3 N 4 layer using hydrogen‐based plasma followed by wet chemical etching in buffered oxide etch solution. The plasma conditions are optimized and a relatively high etch rate is demonstrated. FTIR analyses show clear evidence that the formation of N–H and Si–H species in the hydrogenated Si 3 N 4 layer contributes effectively to the increase of the etching rate. Finally, a chemical etching model is proposed to explain the higher etch rate of hydrogenated Si 3 N 4 .
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it