Accessing Binary CdE [E = S, Se, Te] and Ternary Cd<i><sub>x</sub></i>Zn<sub>1-</sub><i><sub>x</sub></i>E [E = S, Se] Materials in Mesoporous Architectures Using Silylated-Chalcogen Reagents
Bibliographic record
Abstract
Binary cadmium chalcogenide materials (CdS, CdSe, and CdTe) have been successfully synthesized at room temperature in the mesoporous environments of MCM-41 and MCF (mesocellular foam) by utilizing silylated-chalcogen reagents [E(SiMe 3 ) 2, E = S, Se, Te] as an efficient delivery source of E 2- . The encapsulated materials are easily prepared by the initial complexation of anhydrous cadmium acetate to ethylenediamine functionalized mesoporous material. The subsequent addition of E(SiMe 3 ) 2 leads to the preferential formation of CdE materials within the host. The observed blue shift in absorption maximum is in agreement with the expected quantum confinement of these materials given the nanometer dimensions of the mesoporous architecture. Mild thermal treatment of CdS and CdSe composites demonstrates the ability to control particle growth under specified thermal conditions, ultimately leading to a red shift in absorption maximum upon increasing thermolysis temperature. The utility of silylated-chalcogen reagents was further demonstrated in the formation of ternary Cd x Zn 1- x E (E = S, Se) encapsulated in MCF. The addition of the molecular precursor, ( N, N ‘-TMEDA) Zn(ESiMe 3 ) 2 (TMEDA = N, N, N ‘, N ‘-tetramethylethylenediamine), to Cd−MCF yields Cd 0.33 Zn 0.76 S− and Cd 0.34 Zn 0.6 Se−MCF materials, where the absorption maximum lies between that of the respective parent binary composites. All materials have been characterized by 13 C CP-MAS NMR and UV−vis spectroscopy, high-resolution transmission electron microscopy, energy-dispersive X-ray, and nitrogen sorption analysis.
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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".