Niobia Nanofiber-Reinforced Protective Niobium Oxide/Acrylate Nanocomposite Coatings
Bibliographic record
Abstract
In the present study, the corrosion resistance of a new niobium oxide/acrylate hybrid nanocomposite coating doped with niobia nanofibers is investigated. Nanofibers were initially synthesized from niobium(V) chloride precursor in a novel autoclave approach before fabricating the base coating from a two-step process involving the syntheses of acrylate resin via free radical polymerization and niobium oxide gel from niobium ethoxide via a sol-gel technique. Variants of the synthesized nanocomposite coating were incorporated with varying concentrations of niobia nanofibers before spin-coating on Q235 steel substrates to inhibit corrosive electrolytic ion percolation and further enhance corrosion resistance when treated with chloride-enriched corrosive media. The corrosion resistance of these nanocomposite coatings increased with nanofiber content up to an optimum concentration due to the corrosion-inhibiting and protective effects of niobium barrier layers within these coatings. The presence of the niobia nanofibers also promoted improved surface contact angle and toughened mechanical strengths.
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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".