Synthesis and Spectroscopic Characterization of Manganese Doped Zinc Sulfide Quantum Dot Nanocrystals
Bibliographic record
Abstract
Zinc sulphide quantum dots were synthesized in aqueous media using sodium polyphosphate as the stabilizer. The nanoparticles were 2.5 ± 0.5 nm and 5.0 ± 0.5 nm diameter depending on the synthetic procedure employed and the amount of Mn doped varied from 0.003 to 0.32% (w/w). The nanoparticles were characterized by UV-Vis absorption, luminescence, EPR, near edge x-ray absorption fine structure (NEXAFS), and x-ray photoelectron spectroscopy (XPS), and x-ray diffraction (XRD), and transmission electron microscopy (TEM). These quantum dots show a strong emission at 590 nm due to the 4T1 -6A1 transition characteristic of Mn occupying Zn positions in the lattice in a slightly distorted Td site. The intensity of the emission at 590 nm increases asymptotically with the concentration of Mn(II) while the lifetime of this emission decreases. The EPR data reveal that Mn2+ exists in at least three different types of environments: a slightly distorted Td site, a highly distorted site near the surface of the nanoparticle and surface sites where Mn2+ is adsorbed. The sites responsible for the luminescence of ZnS:Mn are the Td sites inside the nanoparticle. The 590 nm emission is enhanced when the nanoparticles photo-react with cysteine. This change in intensity could be employed for the design of nanosensors.
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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".