Synthetic Routes to the Encapsulation of II–VI Semiconductors in Mesoporous Hosts
Bibliographic record
Abstract
Abstract Ordered mesoporous silicate materials, such as MCM‐41 and SBA‐15, offer a nanometre‐sized environment for the inclusion of quantum‐confined materials. The channel walls of the framework hinder cluster‐cluster interactions thereby restricting particle growth and thus limiting the size of the enclosed particles to the nanometre‐size regime. In particular, the past decade has seen substantial progress in the synthesis and encapsulation of II–VI nanoparticles within MCM‐41 and SBA‐15. This microreview highlights the recent developments in this area, with notable emphasis on the synthetic routes used in the growth and anchoring of CdS, CdSe and ZnS nanoparticles within a mesoporous host. Of relevance are the methods of ion‐exchange, interior pore wall modification, quantum‐dot doping, incorporation of preformed nanoparticles and clusters and external surface passivation through organic functionalization. In addition to synthetic methods employed, the interesting photochemical properties of the composite materials are discussed. (© Wiley‐VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2005)
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".