Electrical characterization of metal–oxide–semiconductor capacitors with anodic and plasma-nitrided oxides
Bibliographic record
Abstract
We have studied two novel techniques that should inherently be more uniform than current mainstream processes used to produce silicon dioxide or nitrided-oxide gate insulators. Anodic films were fabricated by anodizing Si wafers in HCl solutions, and thermal oxide films were nitrided in N2O plasmas produced with an electron-cyclotron resonance source. Using typical polysilicon-gate test structures, the electrical characteristics are obtained and compared to thermal oxides. Both techniques can produce thin films (<15 nm thick) with interface state densities and leakage currents initially comparable to their thermal oxide counterparts, if the films are subjected to rapid thermal annealing at temperatures of 950 °C. The annealed films are subjected to high-field (⩾8 MV/cm) Fowler–Nordheim stress and the buildup of trapped charge is monitored as a function of time. Anodic films are found to have moderately higher bulk and interface trap generation rates than the thermal control. Thinner anodic oxides, which were grown at slower rates, had better properties than thicker anodic oxides, suggesting that even slower growth rates could yield anodic oxides with improved electrical properties.
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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 | 0.001 |
| 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 | 0.001 | 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".