Continuous pilot plant–scale immobilization of yeast in κ‐carrageenan gel beads
Bibliographic record
Abstract
Abstract A novel continuous two‐phase dispersion process was developed to produce κ‐carrageenan gel microspheres, using static mixers. It was shown that yeast‐loaded carrageenan beads, with controlled diameter and tight size distribution, can be produced on a continuous basis, in a scalable mixer, at production rates appropriate to both pilot plant–scale and, potentially, industrial‐scale operations. Immobilized yeast are intended to be used in continuous brewing operations. The effects of the static mixer diameter (D), the number of mixing elements (N e ), the fluid linear velocity (V), and the volumetric fraction (ϵ) of κ‐carrageenan, on the mean diameter and size distribution of the resulting gel microspheres, were studied. Image analysis showed that mean diameter was strongly influenced by the average linear fluid velocity through the mixer, and by the mixer diameter. The number of mixer elements and the mixer diameter governed bead size dispersion. A productivity of 10 L h −1 of beads was attained using a 1.27‐cm‐diameter static mixer. Because the productivity is proportional to the mixer diameter squared, this process, although suited for the production of small‐size beads (down to 50 μm), would be technically and economically feasible for a large industrial immobilization process. However, because the coefficient of variability increased with mixer diameter, and thus with scale‐up, operational improvements are suggested, such as the use of smaller‐diameter mixers operating in parallel, to reduce the size dispersion. © 2004 American Institute of Chemical Engineers AIChE J, 50: 1599–1605, 2004
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".