Metal Oxide Porous Coatings for Implantant Materials
Bibliographic record
Abstract
The paper presents the results of survey, dedicated to synthesis of metal oxide coatings on porous materials applied for implant surgery (stainless steel 12X18H9T, titanium alloy and high-purity niobium VT5). This article examines kinetic features of electrochemical formation of anodic oxide coatings on steel, niobium and titanium. It is shown that for steel anodic treatment method does not provide a reliable surface passivation (no current decay, the surface indicates the transition to the passive state).Analysis of polarization dependences obtained on niobium and titanium in electrolytes with an activator (F-), indicates surface passivation (current slump), and at potentials above 2 on the surface of a transition curves in transpassive state (as evidenced by the current increase). Consequently, it can be concluded that presence of F- results surface activation of titanium and niobium electrode (F- oxide reacts to form water-soluble complexes) that promotes nucleation and formation of pores of the porous structure of the oxide coating.SEM results verify the presence of self-organized porous oxide film synthesized on titanium and niobium in solutions containing F-.
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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 | 0.001 | 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) | 0.002 | 0.001 |
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".