Enhancing the antibacterial properties of zinc sulfide thin films by substrate patterning
Bibliographic record
Abstract
To investigate the porosity and substrate effects on the antibacterial properties of ZnS thin films, sculptured structures were considered. Two types of uncoated glass and primary coated glass were used as different substrates. Since the porosity percentage is dependent on the shadow of grains, spiral structures with different numbers of pitches were formed on the different substrates. The cross-section and morphology of the samples were investigated by means of FESEM images. To evaluate the antibacterial properties of the samples under light irradiation, the absorption spectra of the structures at different wavelengths were obtained and investigated. The results showed that most adsorption of structures occurs at wavelengths less than 400 nm. Finally, antibacterial properties of this thin film were investigated in two cases of without light and with light irradiation, for two types of Escherichia coli and Staphylococcus aureus bacteria. The results showed that the structures with higher porosity have better antibacterial properties. The results also showed that light radiation increases the antibacterial properties of structures.
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) | 0.001 | 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".