Investigation of local and temporal interfacial shear stress distribution during membrane emulsification
Bibliographic record
Abstract
Abstract The production of high‐quality liquid/liquid emulsions is a key factor in many industrial processes, such as in food or pharmaceutical industries. The premix emulsification process enables the controlled adjustment of fine and narrow distributed droplet sizes. Furthermore, premix emulsification in porous structures is considered a low‐shear process that enables the usage and formulation of shear sensitive media (e.g., proteins). However, the local and time‐dependent stress conditions and stress residence time at the droplet interface during droplet dispersion in micro‐porous structures are still unknown. In this paper, interfacial stress distributions during droplet dispersion in premix membrane emulsification are numerically (computational fluid dynamics, CFD) investigated. Time‐dependent stress conditions and stress residence times at the interface are calculated. The stress conditions are related to the droplet deformation process to identify the main mechanisms for droplet breakup. The results are compared to experimental analysis of the resulting droplet size distribution during emulsion formulation. It has been found that higher shear stresses occur at the pore wall, but lower shear stresses at the liquid/liquid (disperse/continuous) interface are responsible for the droplet dispersion process. The stress residence time shows that lower stresses are present over a longer time compared to higher stresses. This is relevant for the understanding of the dispersion process, but also for the use of shear sensitive media (e.g., proteins as emulsifier).
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.
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) | 0.001 | 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 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".