Eco-friendly pyridine-derivatives for corrosion inhibition of carbon steel during acidic treatments: mechanistic insights from electrochemical, surface, and computational studies
Bibliographic record
Abstract
Pyridine and urea derivatives have emerged as valuable corrosion platforms ascribed to exceptional coordination potential, and environmental friendliness. Two novel structures of pyridine-carbamides (MS30 & MS31) were synthesized and used as green corrosion inhibitors for the carbon steel in 1M HCl. Electrochemical measurements determined the increase in efficiency with concentrations, reaching 95.3% and 97.1% at 200 mg L −1 and 298 K for MS30 and MS31. Despite the reduced performance with increasing temperature to 303 and 313 K, results revealed improved inhibition at 323 K. At the highest temperature of 323 K, MS30 and MS31 proved their influence in maintaining 97.6% and 93.4% efficiency, highlighting their suitability for treatments in oilfield downhole regions. The adsorption of both inhibitors fitted the Langmuir model and was attributed to chemisorption, as inferred from thermodynamics. Corrosion kinetics and activation energy also verified the chemical interaction of the Fe–inhibitor complex. Spectroscopic surface evaluation interpreted the surpassed metallic dissolution by MS30 and MS31 through protective barrier formation, and X-ray photoelectron spectroscopy (XPS) determined the existence of the Fe–N bond. The sustained viability of human cells affirmed the nontoxic nature of MS30 and MS31 after treatment with 0.2 mg mL−1 of MS30 and MS31 compounds. DFT calculations revealed that both inhibitors exhibited strong adsorption on the metal surface (− 9.5 eV), classified as chemisorption. Overall, the experimental findings are well supported with surface and computational studies. These pioneering compounds are introduced herein to advance state-of-the-art inhibitors, providing high efficiency under challenging environments.
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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 | 0.001 |
| 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".