Inactivation of Bacterial Spores on Polystyrene Substrates Pre-exposed to Dry Gaseous Ozone: Mechanisms and Limitations of the Process
Bibliographic record
Abstract
Some polymers can both absorb dry gaseous ozone and release it efficiently. This occurs, for example, with polystyrene (PS) surfaces, which acquire biocidal properties: bacterial spores are indeed inactivated when deposited wet on polystyrene exposed to ozone. Two main features need to be examined in relation with these assertions: PS surfaces pre-exposed to dry ozone can release O3 molecules, possibly solubilized in water, and thus bacterial spores can be inactivated when present in a suspension. We used Bacillus atrophaeus spores, which are the recommended bio-indicators in sterilization processes. Efficiency of the inactivation mechanism requires an optimized water volume to provide maximal concentration of active molecules. We find that the sporicidal effect increases: i) with the dimensions of the O3 pre-exposed PS surfaces and ii) with the contact time of the spore suspension with the released ozone, while it decreases iii) with time elapsed after ozone pre-exposure of PS. A numerical model, accounting for decomposition of ozone in water, predicts the existence of many different molecules, the main concentrations of which being (besides ozone) those of hydrogen peroxide and hydroxyl radical. Experimentally, under our conditions, the concomitant presence of ozone and hydrogen peroxide in water is observed; the participation of these chemical species to the inactivation process is investigated.
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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".