Substrate biasing effect on the electrical properties of magnetron-sputtered high-k titanium silicate thin films
Bibliographic record
Abstract
We report on the effect of substrate biasing on the properties of high-dielectric constant (high-k) titanium silicate (TixSi1−xO2) thin films deposited with a room-temperature magnetron-sputtering process. The composition, microstructure, and electrical properties of the TixSi1−xO2 films were systematically characterized, as a function of the substrate bias voltage (VS), by means of various complementary techniques, including x-ray photoelectron spectroscopy, x-ray reflectivity, Rutherford backscattering spectrometry, and appropriate electrical characterizations. We show, in particular, that depositing the TixSi1−xO2 films with a relatively small biasing voltage (VS≈−15 V) leads not only to a significant reduction of their porosity but more interestingly to a marked improvement of their electrical properties. A further increase of the negative bias voltage (from 20 to 110 V) was, however, found to increase progressively the leakage current through the TixSi1−xO2 films. Such a degradation of the electrical properties at high VS values is shown to be associated with some resputtering and defects generation caused by the rather energetic bombardment conditions. In contrast, the “soft hammering” induced by the relatively low-energy ion bombardment densifies the films and improves their properties. Under the optimal substrate biasing conditions (VS∼−15 V), the room-temperature deposited titanium silicate films are shown to exhibit a highly attractive combination of electrical properties, namely a k value as high as ∼17, a dissipation factor <0.01, a leakage current as low as 5×10−9 A∕cm2 at 1 MV/cm, and a breakdown field higher than 4 MV/cm.
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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".