Ascorbic Acid, Ascorbate, and Dehydroascorbic Acid as Green Corrosion Inhibitors: A Computational Investigation
Bibliographic record
Abstract
Ascorbic acid is widely used as an immunity-enhancing and antioxidant supplement for treating influenza and other virus-based illnesses. The lactone ring and the oxygenated groups make this system and derived structures attractive as possible environmentally friendly green corrosion inhibitors. Thus, we investigate the corrosion inhibition influence of ascorbic acid, ascorbate, and dehydroascorbic acid on the α-Fe(110) surface using density functional theory calculations. The adsorption, density of states, and charge transfer results indicate that dehydroascorbic acid is this series’s most potent corrosion inhibitor. The projected density of states near the Fermi energy reveals notable hybridization between the iron surface and dehydroascorbic acid adsorbed on it. The calculated structural, electronic, and energetic properties obtained in this work pave the way for understanding the corrosion inhibitory performance of the investigated systems.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| 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 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".