Experimental and Theoretical Studies of α-Linolenic Acid as Green Corrosion Inhibitor for Carbon Steel in 0.5 M Sulfuric Acid
Bibliographic record
Abstract
A component of Salvia hispanica, α-linolenic acid, has been evaluated as a green corrosion inhibitor for 1018 carbon steel in 0.5 M sulfuric acid using weight loss tests, potentiodynamic polarization curves and electrochemical impedance spectroscopy (EIS) measurements. Theoretical calculations using Density Functional Theory (DFT) were used also. The results have shown that this compound is a good corrosion inhibitor, with an efficiency which increased with an increase in its concentration up to 600 ppm, but it decreased with a further increase in the concentration. α-linolenic acid formed protective corrosion products layer because it was chemically adsorbed onto the steel surface according to a Langmuir type of adsorption isotherms. Polarization curves have shown that α-linolenic acid is a good, mixed type of inhibitor with a predominant effect on the cathodic hydrogen evolution reactions. EIS measurements indicated a charge transfer-controlled corrosion process. DFT calculations indicated that α-linolenic acid was more efficient in an acidic environment than in a neutral one because has a high tendency to donate electrons and can be easily protonated. In addition to this, it had the highest EHUMO value, the best chemical reactivity, the greatest tendency to transfer electrons and a greater facility of modifying its electronic configuration in the presence of carbon steel specimens according to its chemical hardness value.
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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 | 0.000 | 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 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".