Deactivation Efficiency of Stabilized Bactericidal Emulsions
Bibliographic record
Abstract
Biocide emulsions stabilized with various stabilizing agents were prepared and characterized, and their efficiency in bacteria deactivation was evaluated. A number of stabilizing agents were tested for their stabilizing effect on emulsions of thiocyanomethylthiobenzothiazole (TCMTB) biocide. Two agents, the most successful in stabilizing the biocide, were chosen for further studies: high molecular weight polyethyleneimine (PEI) and an amphiphilic block copolymer of poly(caprolactone)-b-poly(acrylic acid) (PCL(33)-b-PAA(33)). The emulsion droplet sizes varied between 325 and 500 nm. Deactivation of bacteria was studied by exposing E. coli ATCC 11229 bacteria dispersions to emulsions stabilized by positively charged PEI or negatively charged PCL-b-PAA micelles and by measuring their absorbance; E. coli do not grow with time in the presence of biocide emulsions. PEI molecules alone act as biocide and deactivate the bacteria. PCL-b-PAA micelles as stabilizing agent do not affect the growth of the E. coli ; bacteria are deactivated by TCMTB released from the emulsion droplets. The kinetics of emulsion dissolution studies revealed for both stabilizing agents a decrease in droplet size with time while the emulsions were subjected to dialysis. The biocide was released from the emulsions within ∼250 min; the droplet shells consist mostly of PEI or PCL-b-PAA insoluble complexes with the biocide, which do not dissolve during dialysis. SEM images confirm the presence of residual crumbled shells with holes after 24 h of dialysis.
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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) | 0.003 | 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".