Colloidal approach to Au-loaded TiO2 thin films with optimized optical sensing properties
Bibliographic record
Abstract
TiO2 and Au nanoparticles are synthesized by the colloidal technique and used for nanocomposite thin film preparation. The effect of thermal treatment and organic template presence is analyzed in order to tailor film microstructure. The Au-TiO2 interfaces as well as the overall porosity of the films are analyzed combining structural and morphological characterization along with spectroscopic ellipsometry and surface plasmon spectroscopy analyses. An efficient surrounding of TiO2 nanoparticles around Au colloids is obtained, leading to an extensive noble metal–metal oxide interface, improving functional properties of the films, while keeping a porous structure. Gas sensing tests are performed on these nanocomposites films: reversible sensing dynamics for CO detection are observed with high sensitivity and a correlation between response and recovery times and microstructure is reported.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".