TiO <sub>2</sub> –SiO <sub>2</sub> nanocomposite thin films deposited by direct liquid injection of colloidal solution in an O <sub>2</sub> /HMDSO low-pressure plasma
Bibliographic record
Abstract
Abstract TiO 2 nanoparticles (NPs), 3 nm in size, were injected inside a very-low-pressure O 2 plasma reactor using a liquid injector and following an iterative injection sequence. Simultaneously, hexamethyldisiloxane (HMDSO) vapor precursor was added to create a SiO 2 matrix and a TiO 2 –SiO 2 nanocomposite (NC) thin film. Both the liquid injection and vapor precursor parameters were established to address the main challenges observed when creating NCs. In contrast to most aerosol-assisted plasma deposition processes, scanning/transmission electron microscopy (S/TEM) indicated isolated (i.e. non-agglomerated) NPs distributed in a rather uniform way in the matrix. The fraction of the TiO 2 NPs inside the SiO 2 matrix was estimated by SEM, spectroscopic ellipsometry (SE), and x-ray photoelectron spectroscopy. All techniques provided coherent values, with percentages between 12% and 19%. Despite the presence of TiO 2 NPs, SE measurements confirmed that the plasma-deposited SiO 2 matrix was dense with an optical quality similar to the one of thermal silica. Finally, the percentage of TiO 2 NPs inside the SiO 2 matrix and the effective refractive index of the NCs can be tuned through judicious control of the injection sequence.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".