Surface Modification To Alleviate PVDF Membrane Fouling During Milk Protein Microfiltration
Bibliographic record
Abstract
The interest in using polyvinylidene fluoride (PVDF) membrane in order to separate casein and serum proteins has been raised due to its significant stability. However, the high hydrophobicity of PVDF membrane causes severe fouling during filtration processes. Ozonation, a surface modification process in which polar groups would be formed on the membrane surface, is widely known for its high efficiency. In the present study, the main objective was to optimize the ozonation parameters to reach the minimum fouling while the maximum mechanical strength could be retained. The contact angle of a water droplet on the membrane surface decreased from 73.5° to 50.4° after the treatment of the membrane at the optimal gaseous phase ozonation. This indicates an increase in the hydrophilicity of the treated membrane. Also, filtration performance demonstrated a lower fouling occurrence on the treated membrane as compared to the untreated one. Although gaseous ozonation yielded a slightly better performance in comparison to the aqueous treatment, the membrane treated with aqueous phase ozonation was benefited from conserving its mechanical strength. Activated carbon helped decreasing the contact angle and fouling as compared to the non-catalytic aqueous treatment while the tensile strength was not affected
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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 | 0.000 | 0.000 |
| 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".