Effect of nanostructured MgO directly grown on pure magnesium substrate on its in vitro corrosion and bioactivity behaviour
Bibliographic record
Abstract
This study introduces a nanostructured MgO coating fabricated via anodization in a non-aqueous electrolyte, offering a novel approach to addressing the challenges of corrosion resistance and biofunctionality. The surface was characterized before and after immersion testing using field emission scanning electron microscopy (FESEM), energy-dispersive X-ray spectroscopy (EDX), and X-ray diffraction (XRD). Electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization tests demonstrated a 2-fold reduction in the corrosion resistance compared to untreated magnesium. Biomineralization studies demonstrated the uniform formation of apatite with a Ca/P ratio of 1.35 on the nanostructured surface after 14 days in simulated body fluid (SBF), surpassing that of microstructured MgO. Hydrogen evolution decreased from 912±38 µL cm -2 for untreated Mg to 615±32 µL cm -2 for the Mg/MgO nanostructure and 545±29 µL cm -2 for the Mg/MgO/HA sample. These findings highlight the potential of nanostructured MgO coatings to advance Mg-based implants by providing enhanced corrosion protection, improved biomineralization, reduced hemolysis and increased cell viability, and reduced H 2 generation.
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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) | 0.000 | 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 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".