Examining particle size growth in twin screw granulation up to steady state with acoustic emissions
Bibliographic record
Abstract
The transient evolution of granules was studied to learn new details about the underlying mechanism for continuous wet granulation in a twin-screw extruder. Sieving and a new inline PAT for particle size development was used to gain these insights. The onset for steady state was established based on observing a consistent PSD, which occurred at five times the mean residence time of the process, over a range of degrees of fill (DF; 12–30 %). The early stages of startup for granulation were captured by the inline PAT, showing different stages of granule growth for particle sizes ranging from 102 to 2230 μm. The analysis found that conveying elements have a stronger influence on granule growth at a low DF whereas the kneading zone had a stronger influence on granule growth at a higher DF. This study presents new details on this black-box process while highlighting the unique value of PAT to twin-screw granulation. • Granulation at a higher degree of fill (DF) becoming increasingly dependent on the kneading zone. • Steady state will be reached by 5 times the mean residence time independent of DF. • Inline PAT can output a representative particle size distribution with only 5 s sampling.
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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 | 0.001 |
| 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 | 0.001 |
| 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".