Formation of group 12 [Zn, Cd] mixed-chalcogen nanoparticles from the reagent Me<sub>3</sub>Si-SeS-SiMe<sub>3</sub>
Bibliographic record
Abstract
Mixed-chalcogen metal chalcogenide nanoparticles (MSexS1-x; M = Zn, Cd) have been synthesized using Me3Si-SeS-SiMe3 as a delivery source of Se2– and S2– to the metal core. This method demonstrates the ease with which mixed-chalcogen particles can be fabricated at low temperature using colloidal techniques. Reaction with Me3Si-SeS-SiMe3 occurs via a redox pathway resulting in Se–S bond cleavage and ultimately contributing to the nonequivalent Se:S ratio observed in the isolated particles. Subsequent thermolysis of ZnSe0.57S0.43 and CdSe0.28S0.72 in hexadecylamine gives rise to controlled particle growth while maintaining the observed stoichiometry. Particles are characterized by EDX, TEM, and powder X-ray diffraction analysis in conjunction with UV–vis absorption and photoluminescence (PL) spectroscopy.Key words: nanoparticles, semiconductors, mixed-chalcogen, quantum confinement, Group 12.
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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".