Physical Phenomena Facilitating the Penetration of Solutions of TiO2 Nanoparticles through Protective Gloves
Bibliographic record
Abstract
Titanium dioxide nanoparticles (nTiO2) are found in numerous manufactured products such as sunscreens and paints. Nevertheless, some studies have expressed concern about their likely harmful effects on health. Application of the precautionary principle has led to the recommendation for the use of protective gloves by numerous Health & Safety agencies. However, recent work has shown that solutions of nTiO2 can penetrate the protective materials of gloves under conditions simulating occupational use. This study has been designed to identify some of the physical phenomena that may facilitate the penetration of nTiO2 through elastomer membranes subjected to mechanical deformations (such as those produced by flexing the hand). Nitrile rubber and latex gloves were brought into contact with two solutions of nTiO2. Mechanical deformations were applied to samples of protective gloves during their exposure to nanoparticles. Repetitive mechanical deformations affected both the physical and mechanical properties of protective materials. Moreover, the elastomers used in protective gloves were also shown to be sensitive to the action of the nTiO2 solutions. Elastomer swelling was observed, leading to a modification of the mechanical and chemical properties of the gloves.
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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".