Mechanistic models for liquid binder evaporation in wet granulation
Bibliographic record
Abstract
Abstract In this study, binder evaporation as a significant microscale phenomenon in fluidized bed wet granulation has been investigated in three situations: a single droplet, a sessile droplet, and a liquid bridge. Single droplet evaporation has been analytically modelled by mass transfer analysis from a spherical droplet subjected to the relative velocity of the medium and considering evaporation rate variations versus droplet diameter. Then, the sessile droplet evaporation model has been used from the literature. Finally, the liquid bridge evaporation has been modelled, and the rupture time of the bridge has been computed. The local temperature dependence of air physicochemical properties has been considered in all models. The single and sessile droplet evaporation rates have been successfully validated by the experimental data of the air–water system. The effects of operational conditions and liquid/particle properties on each evaporation event have been evaluated and quantified. The results indicate that both the higher relative velocity between the air and a single droplet and the smaller equilibrium contact angle in a constant volume of sessile droplets increase the evaporation rate. Also, increasing the length of the binder bridge reduces the rupture time.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".