Micromixing in two‐phase (G‐L and S‐L) systems in a stirred vessel
Bibliographic record
Abstract
Abstract The literature on micromixing and local‐specific energy dissipation rate, (on which it depends), for two‐phase systems is limited and conflicting. Here, the competitive iodide/iodate reaction scheme has been used to study the effect of particles and gas flow rate on micromixing in a Rushton turbine agitated vessel. Gassing rates up to 1.5 vvm did not show any effect on product distribution compared to the ungassed at constant mean‐specific energy dissipation rate for a feeding near the impeller. Near the upper liquid surface, micromixing improved with increasing flow rate because it increased fluid turbulence. These results confirm the limited literature. With 500 µm glass beads at concentrations up to 2.5 wt.%, micromixing was unaffected near the impeller and near the surface. The related literature is very unclear and it is difficult to draw any precise conclusions. At ∼12 wt.% when cloud formation was observed, micromixing was significantly worse, especially, it is shown for the first time, in the clear layer above the cloud. The latter finding is significant for processes such as precipitation where micromixing determines the particle characteristics.
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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 | 0.001 |
| 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".