Synergistic Effect of Nanoclay and Barium Sulfate Fillers on the Corrosion Resistance of Polyester Powder Coatings
Bibliographic record
Abstract
Nanoclay has proven to be an active anti-corrosive additive due to the self-repairing effect from nanoclay swelling and expansion, except for its passive barrier effect due to the high aspect ratio. But it is still uncertain how these effects of nanoclay are intertwined with the other components in a complex coating system in corrosive environments. In this study, we examined the combined effects of nanoclays of two particle sizes with a commonly used cost-reducing filler, BaSO4. By employing neutral salt spray tests, electrochemical analysis, and surface characterization, we identified the optimal conditions for achieving a strong barrier effect. Surprisingly, a relatively low nanoclay dosage of 2% combined with BaSO4 filler exhibited synergistic behavior. Nanoclay not only compensated for the reduction in the barrier effect owing to the addition of BaSO4 by offering self-repairing and barrier effects, but also overcame the delamination issues observed at higher nanoclay dosages (4% and above). The coating panel with 2% larger nanoclay and BaSO4 showed two orders of magnitude higher pore resistance than the coating without nanoclay, remaining at 107 Ω∙cm2 after 25 days of immersion. As a result, this coating panel demonstrated significantly slower corrosion expansion and reached a lifetime of 2500 h when creepage exceeded 2 mm in salt spray tests. This study contributes to a full understanding and proper utilization of nanoclay for high-performance, smart anti-corrosive coatings.
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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 | 0.000 |
| 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 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".