Probing protein colloidal behavior in membrane‐based separation processes using spectrofluorometric Rayleigh scattering data
Bibliographic record
Abstract
One of the primary problems in membrane-based protein separation is membrane fouling. In this study we explored the feasibility of employing Rayleigh light scattering data from fluorescence studies combined with chemometric techniques to determine whether a correlation could be established with membrane fouling phenomena. Membrane flux was measured in a dead-end UF filtration system and the effect of protein solution properties on the flux decline was systematically investigated. A variety of proteins were used as a test case in this study. In parallel, the colloidal behavior of the protein solutions was assessed by employing multiwavelength Rayleigh scattering measurements. To assess the usefulness of Rayleigh scattering measurements for probing the colloidal behavior of proteins, a protein solution of beta-lactoglobulin was used as a base-case scenario. The colloidal behavior of different beta-lactoglobulin solutions was inferred based on published data for this protein, under identical solution conditions, where techniques other than Rayleigh scattering had been used. Using this approach, good agreement was observed between scattering data and the colloidal behavior of this protein. To test the hypothesis that a high degree of aggregation will lead to increased membrane fouling, filtration data was used to find whether the Rayleigh scattering intensity correlated with permeate flux changes. It was found that for protein solutions which were stable and did not aggregate, fouling was reduced and these solutions exhibited reduced Rayleigh scattering. When the aggregation behavior of the solution was favored, significant flux declines occurred and were highly correlated with increased Rayleigh scattering.
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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 | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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 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".