Influence of ( <i>E</i> )-1-methyl-2-phenylhydrazonopyrrolidine toward the corrosion behavior of C-steel and hydrogen production in acidic aqueous media
Bibliographic record
Abstract
The influence of (E)-1-methyl-2-phenylhydrazonopyrrolidine, MPHP, Schiff base, as an inhibitor for hydrogen production and C-steel destruction, was examined in a dilute hydrochloric acid solution using experimental and theoretical techniques. The rate of metal destruction, rg, and hydrogen production, rH, are suppressed in the presence of the MPHP inhibitor. The inhibition efficacy is increased with higher additions of the MPHP to reach more than 93.00% at 0.005 M and 25 °C. The inhibition process is based on the adsorption of MPHP molecules on the metal surface. The free energies of adsorption, ΔGoads are varied between −34.45 and −36.77 kJ. mol−1 while the adsorption-desorption constants, Kads are varied between 19.73 × 103 and 8.68 × 103 M−1, depending on the temperature, T, which confirms the presence of physico-chemisorption mechanisms. The lowering in the Kads values with T can be related to the desorption of a few MPHP molecules from the metallic surface. The inhibitors’ optimized geometries were determined by the DFT method and conductor-like polarizable continuum (CPCM) model, providing insights into their molecular structure and potential properties. Monte Carlo and molecular dynamics simulations further assessed the inhibitors’ adsorption energy and comprehensive adsorption characteristics. The highest adsorption energy suggests superior corrosion inhibition properties.
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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".