Disinfection mechanism of the photocatalytic activity of SnO<sub>2</sub> thin films against <i>Candida albicans</i>, proposed from experimental and simulated perspectives
Bibliographic record
Abstract
Nosocomial infections are an important health problem and cause of complications and death in hospitalized patients. This problem should be solved from the preventive angle, avoiding the spread of infections by designing disinfection methods based on the photocatalytic activity of semiconductor materials such as tin oxide (SnO2). The antimicrobial activity of UV light was tested by using inoculation with Candida albicans ATCC10231 on SnO2 thin films and counting colony forming units (CFU). The interaction of UV light with SnO2 was analyzed by density functional theory (DFT) and the extension to the Hubbard model (DFT+U) schemes to predict the electron behavior at the subatomic level. After exposure to UV light, C. albicans showed a reduction of 36.5% in viable cells, and when SnO2 was included, cell viability was reduced by 60.2%. Measurements of the electronic structure obtained by the first-principle calculations under the DFT and DFT+U schemes showed that the O-p orbitals mediate the oxidation process in the bulk semiconductor. By including the surface effects when cleaving the (1 0 0) plane, the three orbitals O-p, Sn-p, and Sn-s are the mediators. SnO2 films are promising antimicrobial coatings because UV light has a synergic activity with thin films, resulting in faster disinfection.
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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".