Scaling-up high internal phase Pickering emulsions in stirred tanks
Bibliographic record
Abstract
This study investigates the effect of the scale-up exponent on droplet size in high internal phase Pickering emulsions (HIPPEs) within the laminar regime. Through systematic analysis, we demonstrate that a scale-up exponent of zero, which maintains a constant shear stress, results in consistent droplet size across all scales. We explore the relationship between droplet size, power-law index, consistency index and Metzner-Otto constant, establishing a correlation that accurately predicts the required power per unit volume for achieving the desired droplet size. Further analysis of the relationship between Droplet size and specific energy reveals that droplet size decreases with increasing specific energy until reaching an equilibrium size. Beyond the equilibrium point, Droplet size correlates with power per volume ( P/V ). These two curves can serve as a predictive tool for estimating the required P/V and revolution number to achieve target droplet sizes. Our findings suggest that emulsion viscosity, rotational speed, and revolution number are crucial parameters for controlling droplet size, thereby optimizing HIPPEs for industrial-scale applications. 3232 • A scale-up exponent of zero ensures the constant droplet size across scales in HIPPEs. • Rheological characteristics of emulsion correlate with droplet size. • Required power per volume for target droplet size is estimated from emulsion rheology. • Droplet size scales with energy and power per volume.
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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) | 0.000 | 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".