Assessment of Performance of Short Cuboid Packed-Bed Devices Based on Simulations and Experiments
Bibliographic record
Abstract
Cuboid packed-bed devices developed for chromatographic separation typically have shorter bed heights and larger cross-sectional areas than their equivalent cylindrical columns. These devices can be operated at low back pressures and give comparable or even better resolution than their equivalent columns. However, the bed height of a cuboid packed-bed device could potentially affect its separation performance. To examine this, three devices having 5, 10 and 19.5 mm bed heights were fabricated and packed with the same resin media. A mathematical model was first developed to predict the effect of bed height on the performance of these cuboid devices. This prediction was performed based on the residence time heterogeneity (RTH) in these devices, which increased slightly as the bed height was decreased. However, this was not likely to affect the separation efficiency very significantly. The relative performances of these three cuboid devices were then compared based on the resolution obtained during ion-exchange chromatography of multi-protein mixtures. As predicted by the mathematical model, the loss in resolution due to the decrease in bed height was relatively small (0.83 to 0.73 in binary protein separation). Also, this loss could easily be compensated for by slightly lowering the flow rate or by extending the elution gradient. The results discussed in this paper demonstrate that with cuboid packed-bed devices, the dimensions could be altered in a reasonably flexible manner without adversely affecting separation performance. Such flexibility is advantageous from the point of view of process design and optimization, which is critically important for developing large-scale processes for the purification of biologics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".