A Comparative Study on the Anti-Corrosive Performance of Zinc Phosphate in Powder Coatings
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Powder coatings are gaining popularity for their economic and environmental benefits. Additives (pigments) such as zinc phosphate enhance the anti-corrosive properties of coatings, but their behavior in powder coatings has not been extensively studied. In this study, zinc phosphate was incorporated into three powder coating systems: polyester clearcoat, polyester and epoxy coatings with filler BaSO4. Neutral salt spray and electrochemical tests (OCP, LPR, and EIS) confirmed that the anti-corrosive performance improved with the addition of zinc phosphate. The optimal additive dosage was determined to be 2% for all of the coating systems studied here, based on salt spray tests. Here, the time until failure increased by 1.5 to 2 times. Using electrochemical tests, an optimal additive dosage of 8% was found for the polyester clearcoat, while the other coating systems maintained an optimal additive dosage of 2%. Performance increased by as much as one order of magnitude based on resistance/impedance measurements. This suggested a synergistic effect between the additive and the filler. The passivation layer was confirmed by both X-ray diffraction and Raman spectroscopy. Based on the results and discussion presented in this article, the discrepancy was caused by different features of the two tests, such that the electrochemical tests probe the function of intact coatings, whereas salt spray measures only the corrosion spreading from the scribe. It is proposed that the two test methods characterize different aspects of the coatings, corresponding to their service conditions. This has theoretical and practical significance in the evaluation of anti-corrosive coatings. Other properties of the coatings, including adhesion, gloss, distinctness-of-image, and pencil hardness, were measured as per applicable standards and the conformance was verified.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 it