Pomegranate arils extract as a green corrosion inhibitor for mild steel: effect of concentration and temperature in hydrochloric acid
Bibliographic record
Abstract
Abstract Corrosion inhibitors generated from plants and organic compounds are critical for achieving a greener environment. In this work we investigated the corrosion inhibition of pomegranate arils extract (PAE) for mild steel in 1M HCl by potentiodynamic polarization (PDP), electrochemical impedance spectroscopy (EIS), and profilometry measurements. The effects of PAE concentration (100, 200, 400 mg l –1 ) and temperature (298, 313, and 333 K) on the PAE inhibition efficiency were evaluated. Polarization measurements revealed that PAE was a mixed anodic-cathodic inhibitor. Corrosion inhibition efficiency was around 74% at a PAE concentration of 400 mg l –1 at 298K. However, at 333 K, the corrosion current density in the solution containing 400 mg l –1 of PAE was measured to be 1.28 mA cm −2 , which was higher than that in the blank solution (0.92 mA cm −2 ). This increase in corrosion rate at 333 K demonstrates the negative influence of high temperatures on PAE inhibition efficiency. The PAE green inhibitor was discovered to have a physical adsorption characteristic and to obey the Langmuir adsorption isotherm.
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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) | 0.001 | 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 | 0.001 |
| 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".