Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Topical disinfection protocols to inactivate organisms, particularly on high contact surfaces, have become increasingly important. A classical oxidative agent, sodium hypochlorite (bleach), has many benefits, but can be problematic during applications because of its ability to oxidize the organic polymers in which it is contained. We demonstrate that bleach-containing elastomeric sponges are readily created in one step at room temperature from thiopropyl-modified silicone oils; sodium hypochlorite induces disulfide cross-linking and a foam structure due, in part, to the concomitant formation of sulfonates. No surfactants are required. The morphology of the bleach-containing silicone sponge is tunable by the aqueous bleach solution concentration and the water/silicone ratio used. The resulting silicone sponge contains excess bleach that can be released gradually, as shown by its ability to oxidize organic molecules in aqueous solution, either directly or after dehydration/rehydration; the latter process provides a way to store the bleach-containing material in dry form. Such foams exhibit enhanced sustainability as, we show, they can be converted back to thiopropylsilicone oils by reduction using hydrosilicones. The resulting oils can be re-cross-linked, completing the life cycle.
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 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) | 0.002 | 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".