Ti Source Precursors for Atomic Layer Deposition of TiO2, STO and BST
Why this work is in the frame
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Bibliographic record
Abstract
In this study we evaluated several precursors such as tetrakis(dimethylamino) titanium (TDMAT), tetrakis (diethylamino) titanium (TDEAT), tetrakis(ethylmethylamino) titanium (TEMAT) along with novel PrimeTiTM, StarTiTM and TyALDTM for TiO2 ALD application with both water and ozone as the oxidizer. Each precursor is evaluated with respect to some of the important characteristics like growth rate of TiO2 per ALD cycle, range and upper limit of process temperature window, volatility and stability of precursor, chemistry with desired oxidizer etc., that are critical for the selection of the precursor. All amino-compounds had a narrow process window. Precursor decomposition was observed for TDMAT, TDEAT and TEMAT at temperature higher than 225 oC limiting the deposition process at 225 {degree sign}C. On the other hand, TiO2 ALD using PrimeTiTM and StarTiTM is observed up to 325 and 400 {degree sign}C respectively. Finally, photoelectron spectroscopy analysis of some the films will be discussed.
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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