Fabrication of Nanostructured TiO2 Fibers on TiO2 Coatings Produced from a Nanostructured Feedstock
Bibliographic record
Abstract
Abstract Titania (TiO2) coatings were produced using the high velocity oxy-fuel (HVOF) technique on Ti-6Al-4V substrates. The titania feedstock powder exhibited nanostructured morphology, formed by the agglomeration of individual nanostructured titania particles (spray-drying) smaller than 100 nm. The resulting coatings were dense (porosity <1%) and exhibited rutile and anatase as phases with percentages of ~75% and ~25%, respectively. These coatings were heat-treated in a H2/N2 environment at 700oC for 8 h. During the heat-treatment, nanostructured titania fibers were formed on specific surface regions of the coatings. The nanofibers formed by this “chemical or reaction-based texturing” exhibited diameters of 50-400 nm and lengths in the order to 1-5 µm. It is thought that engineering these surfaces at nano and microscales may lead to interesting applications of titania coatings related to cell attachment/growth (for biomedical applications).
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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) | 0.000 | 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 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".