Study of miniemulsion formulation containing 1-octyl-3-methylimidazolium hexafluorophosphate for its application in low-emitting coating products
Bibliographic record
Abstract
Room temperature ionic liquids (RTILs) are non-volatile organic salts, and few of them with low melting point may replace the conventional coalescing agents in waterborne coatings, thus preventing volatile organic compounds (VOCs) emission, caused by coalescing agents. The formation of waterborne coating containing RTILs can be achieved by the encapsulation of RTILs inside latexes via miniemulsion polymerization. Achieving a stable miniemulsion is a crucial step for further polymerization. In this study, 1-octyl-3-methylimidazolium hexafluorophosphate (C8mimPF6) was chosen, and various factors which might affect droplet size and its stability, including surfactant type, surfactant concentration, and C8mimPF6 concentration, were investigated. It was found that the presence of a small amount of C8mimPF6 coupled with the surfactant would offer marked effects on the droplet size reduction and droplet stability. Such effect may reach its maximum from 1 to 5 wt% C8mimPF6. Above the critical concentration, adding more C8mimPF6 to the oil phase may cause a larger initial droplet size as well as weaken the droplet stability. Such observations were consistent with the zeta potential measurements for miniemulsions prepared under similar conditions.
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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) | 0.000 | 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".