A Study on the Use of Heterocyclic Compounds for Surface Protection in Acidic Environments
Bibliographic record
Abstract
This study aims to assess the potential of two synthesized thiazolidine derivatives (AS3) and (AS4) in the capacity of preventing corrosion on N80 alloy steel in 1M hydrochloric acid medium.The electrochemical behavior, adsorption isotherms, activation energy, and surface morphology were analyzed using Tafel polarization curves, Langmuir adsorption model, Arrhenius equation, and scanning electron microscope (SEM) coupled with energy-dispersive spectroscopy (EDS) techniques.The findings indicate that both compounds function as efficient mixed-type inhibitors, with inhibition efficiency improving proportionally to inhibitor concentration but exhibiting a slight reduction at higher temperatures.This thermal sensitivity points to a predominant physisorption mechanism in the initial adsorption stages.SEM/EDS results confirmed the formation of a compact, protective surface film, validating the adsorption-driven protection mechanism.The significance of this study lies in the growing demand for environmentally safer and economically viable inhibitors for industrial applications involving acid-induced corrosion, especially in oil and gas applications where N80 carbon steel is widely used.Thiazolidine derivatives show strong affinity for steel surfaces, highlighting their suitability, due to their heteroatoms and π-electron system, offer promising coordination ability with metal surfaces.Thus, AS3 and AS4 represent valuable candidates for mitigating acid-induced corrosion, contributing to extended equipment life and reduced maintenance costs in aggressive environments.
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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".