Binder–Block Copolymer Micelle Interactions in Bactericidal Filter Paper
Bibliographic record
Abstract
We previously produced a bactericidal filter paper loaded with PAA47-b-PS214 block copolymer micelles containing the biocide triclosan (TCN), using cationic polyacryamide (cPAM) as a binder. However, we encountered a very slow filtration, resulting in long bacteria deactivation times. Slow drainage occurred only when the filter paper was left to dry. It appears that the filter paper with cPAM and micelles develops hydrophobic properties responsible for this very slow filtration. Three approaches were taken to accelerate the very slow drainage all based on modification of binder-micelle interactions: (i) keeping the micelles wet, (ii) modification of the corona, and (iii) replacing cPAM with smaller and more highly charged cationic poly(isopropanol dimethylammonium) chloride (PIDMAC). In all cases, the drainage time of bactericidal filter paper became close to that of untreated filter paper, without decreasing its efficiency. Moreover, replacing cPAM with PIDMAC led to a much more efficient bactericidal filter paper that reduced bacteria viability by more than 6 orders of magnitude. In addition to resolving the hydrophobic drainage hurdle, the three solutions also offer a better understanding of the interaction between cPAM and micelles in the filter paper.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; 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".