Adsorption Aspects, Inhibitory Properties and a Study of Surface Corrosion of Carbon Steel in Acidic Media
Bibliographic record
Abstract
The impact of cupral compound on steel in presence of deaerated 0.25 M H2SO4 and 0.5M HClacidic solutions at 298.15K was examined by employing electrochemical measurements. It has been observed that the corrosion efficiency increased by increasing of cupral concentration of the corrosion inhibitor and this enhanced the inhibitory action as mixed type inhibitor. Several different adsorption models were examined which indicate the adsorption of cupral compound as inhibitor on the carbon steel electrode surface follows the Langmuir isotherm equation. The thermodynamic factors governing adsorption, as well as the parameters of kinetics corrosion have been estimated. The role of nanosilica has been observed to reduce the values of current density of corrosion process and this was confirmed by study the surface morphology of electrode via SEM-EDX and AFM techniques by formation a protective layer on carbon steel electrode.
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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 | 0.001 |
| 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".