Preparation and Characterization of Microporous Layers on Titanium
Bibliographic record
Abstract
Microporous layers on titanium (Ti) are formed by chemical treatment in highly concentrated alkaline media, and their properties and growth mechanism are examined using electrochemical techniques, in situ resistometry, scanning electron microscopy (SEM), grazing-incident X-ray diffraction (GIXRD), and glow discharge optical emission spectroscopy (GD-OES). Chemical treatment in a 5 M aqueous KOH solution yields results superior to those from the same treatment in a 5 M aqueous NaOH solution, while a 3 M aqueous LiOH solution does not produce porous layers. The cation constituting the solution plays a vital role in the process. An SEM analysis reveals that the KOH solution is the most effective in forming microporosity and that the longer the treatment time, the more porous the near-surface layer. The results of GIXRD analysis show the presence of Na(2)Ti(5)O(11) and K(2)Ti(6)O(13) in the layers formed in the NaOH and KOH solutions, respectively; in the case of the LiOH solution, TiO(2) is formed. Chemical treatment in the NaOH and KOH solutions resembles a general corrosion process with the existence of local cathodic and anodic sites. The reduction reaction produces H(2), some of which becomes absorbed in the near-surface region of Ti, while the oxidation reaction produces the above-mentioned compounds and/or an oxide layer. The presence of hydrogen (H) within the solid is detected using GD-OES. The H-containing near-surface layer partially dissolves, yielding a microporous structure. The development and dissolution of the H-containing near-surface layer of Ti upon chemical treatment in the NaOH and KOH solutions are confirmed by resistometry measurements. They point to the formation of a compact passive layer on Ti upon exposure to the LiOH solution.
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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) | 0.000 | 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".