Fluorescence Detection of Zinc Oxide Nanoparticles in Water Contamination Analysis based on Surface Reactivity with Porphyrin
Bibliographic record
Abstract
A simple rapid analytical method for determining the concentration of ZnO nanoparticles in aqueous dispersion has been developed by adding porphyrin (TCPP) as a fluorophore into the water sample for fluorescence analysis. Quenching of the emission intensity at 650 nm provides a Stern-Volmer plot with adequate sensitivity for the detection of ZnO nanoparticles from 0.15 mg/mL up to 1.5 mg/mL. A new emission peak at 605 nm can be attributed to the formation of a unique ZnO-TCPP complex. This unique emission peak is good for both identification and quantitation of ZnO nanoparticles at low concentrations down to 0.0015 mg/mL. The new method affords a linear dynamic range up to 1.2 mg/mL.
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How this classification was reachedexpand
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 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".