A facile synthesis of nontoxic luminescent carbon dots for detection of chromium and iron in real water sample and bio‐imaging
Bibliographic record
Abstract
Abstract In this study, we have reported the synthesis of luminescent carbon dots (CDs) from indigenous potato sources by simple heating reactions. The as‐synthesized CDs exhibited an average size of ~ 5.97 nm with a quantum yield (QY) of 6.08%. Furthermore, the CDs possessed high water‐solubility, possibly due to the presence of ─COOH and ─OH groups on their surfaces. The quenching of luminescence of the CDs specifically by Cr6+ and Fe3+ ions was used to detect chromium and iron in the water sample. The minimum limit of detection (LOD) for Cr6+ and Fe3+ ions was found to be 0.012 μM and 0.000549 μM, respectively, in a linear range of 0.5 μM‐100 μM and 0.5 μM‐5 μM for Cr6+ and Fe3+, respectively, which was well below the concentration specified by WHO. We used our sensing system to detect the metal ions in water from the Brahmaputra River as well as in tannery water. In addition, the MTT‐based cell viability experiments showed that the CDs were nontoxic within 200 μg/mL. High quantum yield and the easy uptake of CDs enabled the quick labelling of cytoplasm of the HeLa cells, which can be further attributed to bioimaging applications.
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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".