Continuous production of miniemulsions using in‐line SMX elements
Bibliographic record
Abstract
Abstract The preparation and stabilization of miniemulsion systems using SMX static mixers (in line with a pump and reservoir tank) and in situ generated surfactants is presented. Neutralization of a water‐soluble base with an oil‐soluble long chain acid, generating a in situ surfactant at the interface, results in rapid stabilization and emulsification compared to preformed surfactant that must diffuse to, then adsorb on the droplets. As the flow rates (50–75 g/s) and number of mixing elements (7–21 SMX mixers) in series increase, the emulsification time reduces by ∼30‐folds (14 vs. 0.5 min). The reduction in the emulsification time required to produce a stable emulsion at 75 g/s and 21 mixing elements more than compensated for the higher pressure in the emulsification loop, consuming five times less energy than what would be consumed when working at 50 g/s and 7 SMX elements. Subsequently, with the rapid emulsification step, it was possible to test the feasibility of a continuous process for direct emulsification followed by polymerization. Comparing this process with a batch process, similar results for the number of particles/number of droplets ratio and conversion were obtained, but the continuous process was accomplished in a single step. © 2010 American Institute of Chemical Engineers AIChE J, 2011
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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 | 0.000 | 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 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".