Effect of <i>ortho</i>-substituted aniline on the corrosion protection of aluminum in 2 mol/L H<sub>2</sub>SO<sub>4</sub> solution
Bibliographic record
Abstract
Corrosion protection of aluminum in 2 mol/L H2SO4 solution is examined in the presence of ortho-substituted aniline derivatives using potentiodynamic polarization and electrochemical impedance spectroscopy measurements. Density function theory (DFT) calculations are performed to investigate the aluminum–electrolyte interface relationship in the absence and presence of both ortho-substituted aniline derivatives and sulphate anions, as well as their roles in the protection efficiency at the atomic level. Our results show that ortho-aniline derivatives are good inhibitors and that their efficiencies improved as the concentration increased. SEM–EDX analysis is used to confirm the adsorption thermodynamics of the studied compounds on the aluminum surface. The best inhibitory effect is exhibits in the presence of the methyl group in ortho-position followed by ortho-carboxilic compared to aniline. The adsorption of these compounds on the aluminum surface is well described by Langmuir adsorption isotherm as well as the experimental and the theoretical adosrption energies are in a good agreement. DFT calculations also show that the interaction between the inhibitors and the aluminum surface is mainly electrostatic and depends on the type of the ortho-substituted group in addition to the sulphate anions.
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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".