Toward single‐step anodic fabrication of monodisperse TiO<sub>2</sub> nanotube arrays on non‐native substrates
Bibliographic record
Abstract
Shape irregularity and size dispersion exhibited by TiO2 nanotube arrays (TNAs) is a disadvantage for size‐selective applications such as flow‐through membranes, cell differentiation and drug delivery, and for photonic applications such as photonic crystals and metallodielectric metamaterials, where size and shape dispersity are sources of defects and scattering. We show that achieving extremely smooth Ti films is more critical than a large Ti grain size in attaining highly ordered nanotube arrays with minimal dispersity in shape and size, and obtain the insight that uniform pore nucleation is determinative of the quality of the nanostructures that result following electrochemical anodization. TiO2 nanotubes formed by anodization of highly smooth Ti films on single crystal silicon wafers in electrolytes with high water concentrations had only circular pores with a narrow dispersion of pore diameters, and exhibited uniform cross‐sections along the tube‐axis. Pattern order was evaluated using 2D‐FFT analysis . TiO2 nanotubes on Si wafers with a (a) narrow and (b) wide dispersion in shape and size.
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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".