Distance-Dependent Plasmon-Enhanced Singlet Oxygen Production and Emission for Bacterial Inactivation
Bibliographic record
Abstract
Herein, we synthesized a series of 10 core-shell silver-silica nanoparticles with a photosensitizer, Rose Bengal, tethered to their surface. Each nanoparticle possesses an identical silver core of about 67 nm, but presents a different silica shell thickness ranging from 5 to 100 nm. These hybrid plasmonic nanoparticles thus afford a plasmonic nanostructure platform with a source of singlet oxygen ((1)O2) at a well-defined distance from the metallic core. Via time-resolved and steady state spectroscopic techniques, we demonstrate the silver core exerts a dual role of enhancing both the production of (1)O2, through enhanced absorption of light, and its radiative decay, which in turn boosts (1)O2 phosphorescence emission to a greater extent. Furthermore, we show both the production and emission of (1)O2 in vitro to be dependent on proximity to the plasmonic nanostructure. Our results clearly exhibit three distinct regimes as the plasmonic nanostructure moves apart from the (1)O2 source, with a greater enhancement for silica shell thicknesses ranging between 10 and 20 nm. Moreover, these hybrid plasmonic nanoparticles can be delivered to both Gram-positive and Gram-negative bacteria boosting both photoantibacterial activity and detection limit of (1)O2 in cells.
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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".