Unraveling the corrosion protection mechanisms of sustainable inhibitors in epoxy coatings: Bridging solution-phase behavior and coating performance
Bibliographic record
Abstract
The corrosion inhibition behaviours of three eco-friendly inhibitors under static and dynamic conditions were investigated to establish a correlation between their performance in aqueous solution and their effectiveness in coating applications. Calcium borosilicate (CBS), zinc calcium strontium aluminum orthophosphate silicate hydrate (ZPS), and strontium phosphosilicate (SPS) pigments were characterized as mixed-type inhibitors, predominantly functioning through physical adsorption mechanisms. Assessment of their performance was conducted using electrochemical impedance spectroscopy, potentiodynamic polarization, and scanning electron microscopy, combined with energy dispersive spectroscopy analysis. Electrochemical measurements revealed that SPS and ZPS offered superior inhibition performance compared to CBS, supported by surface analysis. It was shown that CBS was ineffective in forming a protective layer on mild steel in NaCl solution, whereas ZPS and SPS developed protective films with notable anti-corrosion properties, achieving inhibition efficiencies of approximately 55% and 75%, respectively. The superior ZPS performance was attributed to the formation of a thin zinc- and phosphorous-rich oxide layer, although this layer exhibits instability under hydrodynamic flow conditions. In contrast, SPS forms a compact and robust strontium, phosphorus, and silicon-rich oxide film, maintaining stability in static and dynamic environments. In inhibitor-embedded epoxy coatings, CBS slightly improved barrier properties but demonstrated limited corrosion inhibition under dynamic conditions due to the instability of its protective layer. Conversely, ZPS and SPS significantly mitigated corrosion-induced delamination of the coating in stagnant conditions, with the SPS-pigmented coating demonstrating superior performance under dynamic conditions. Additionally, no sign of initiation of localized undercoating corrosion was observed in the SPS-pigmented coatings.
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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 | 0.000 |
| 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 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".