On the development of a continuous methodology to fractionate microfibriallated cellulose
Bibliographic record
Abstract
Abstract The focus of this study is the development of a methodology to mechanically separate or fractionate micro-fibrillated fibre suspensions (MFC) into different size classes. We extend the principle outlined by Madani et al. (2010) and create a continuous separation in an annular gap undergoing spiral Poiseuille flow (solid body rotation superimposed on pressure driven flow). Achieving hydrodynamic stability of this flow was the main scientific challenge for scale-up. This work is presented in two different studies. In the first study, we perform a series of batch-wise centrifugation tests to develop the criteria for motion of the individual classes of particles which compose a Eucalyptus MFC suspension. Here, we suspend the MFC in a weak gel and demonstrate a linear reduction in average particle size with increasing centrifugal force; motion is initiated in heavier particles before the lighter ones. In the second study, we use this batch-wise data to design a continuous prototype and we successfully demonstrate a continuous separation with performance similar to that achieved in the batch-wise tests.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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; both teacher heads agree on what is shown here.
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".