High-<i>k</i> titanium silicate thin films grown by reactive magnetron sputtering for complementary metal–oxide–semiconductor applications
Bibliographic record
Abstract
Titanium silicate (TiSixOy) thin films have been successfully deposited by means of radio-frequency magnetron sputtering of a TiO2/SiO2 composite target in a reactive gas atmosphere. The deposition of the films was investigated as a function of the [O2]/([Ar]+[O2]) flow ratio in the 0%–30% range. The bonding states and the dielectric properties of the sputter-deposited TiSixOy films were systematically investigated as a function of the O2 flow ratio. For all the O2 flow ratios studied, Fourier-transform infrared and x-ray photoelectron spectroscopy analyses have clearly revealed the presence of Ti–O–Si type of local environments, which are the fingerprint of the titanium silicate phase. Increasing the O2 proportion in the sputtering chamber was found to cause a significant decrease of the deposition rate and a drastic improvement in the dielectric properties of the films. TiSixOy films exhibiting excellent dielectric properties (i.e., a dielectric constant as high as ∼20, a dissipation factor as low as 0.01, and a low leakage current density of 10−3 A/cm2 at 1 MV/cm) were indeed achieved under high O2 flow ratio conditions (⩾20%). In contrast, films deposited under low O2 flow ratio conditions (⩽5%) have exhibited poor dielectric properties. The presence of oxygen vacancies in the films is invoked as a possible explanation for the observed variations of their dielectric properties with the O2 flow ratio.
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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".