Nanocomposites of Terbium Sulfide Nanoparticles with a Chitosan Capping Agent for Antibacterial Applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study aims to investigate the effect of alkaline pH on the bottom-up synthesis of nanocomposites (NCs) containing terbium sulfide nanoparticles (Tb2S3 NPs), where chitosan (CS) was employed as a capping agent, along with evaluation of the antibacterial activity of these NCs. The NCs were characterized using spectroscopy (FESEM-EDX, Raman, FTIR, XRD, XPS, and DLS), zeta-potential, and TGA. The results of FE-SEM, XPS, Raman, and FTIR characterization support the formation of CS-Tb2S3 NPs. A pH variation from 9 to 11 during composite formation was shown to affect the size and composition of NCs. The antibacterial activity of CS-Tb2S3 NCs was studied by coating onto commercial contact lenses, where the best loading efficiency of NCs was 48%. The NCs prepared at pH 10 (without contact lenses) had greater antibacterial activity against Staphylococcus aureus, with a zone of inhibition diameter of 7.15 mm. The coating of NCs onto commercial contact lenses was less effective for inhibition of Staphylococcus aureus, in contrast with the greater activity observed for tetracycline. CS-Tb2S3 NCs offer promising antimicrobial properties that can be further optimized by control of the surface loading and accessibility of Tb2S3 NPs through further study of the role of the chitosan capping agent, since steric effects due to CS are likely to attenuate antimicrobial activity via reduced electron transfer in such nanocomposite systems.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it