Control of Metal‐Ion Composition in the Synthesis of Ternary II‐II′‐VI Nanoparticles by Using a Mixed‐Metal Cluster Precursor Approach
Bibliographic record
Abstract
The ternary molecular nanoclusters [Zn(x)Cd(10-x)Se4(SePh)12(PnPr3)4] (x = 1.8, 1 a; x = 2.6, 1 b) were employed as single-source precursors for the synthesis of high-quality hexagonal Zn(x)Cd(1-x)Se nanocrystals. The tellurium clusters [Zn(x)Cd(10-x)Te4(TePh)12(PnPr3)4] (x = 1.8, 2 a; x = 2.6, 2 b) are equally convenient precursors for the synthesis cubic Zn(x)Cd(1-x)E nanoparticles. The thermolysis of the cluster molecules in hexadecylamine provides an efficient system in which the inherent metal-ion stoichiometry of the clusters is retained in the nanocrystalline products, whilst also affording control of particle size within the 2-5 nm range. In all cases, the nanoparticles are monodisperse, and luminescence spectra exhibit emission energies close to the absorption edge. Analysis of the optical spectra and X-ray diffraction patterns of these materials indicates a metal-ion concentration gradient within the structures of the nanocrystals, with Zn(II) ions predominantly located near the surface of the particles.
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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 | 0.001 | 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".