CdS Quantum Dots Encapsulated in Chiral Nematic Mesoporous Silica: New Iridescent and Luminescent Materials
Bibliographic record
Abstract
Simultaneous integration of light emission and iridescence into a semiconducting photonic material is attractive for the design of new optical devices. Here, a straightforward, one‐pot approach for liquid crystal self‐assembly of semiconductor quantum dots into cellulose nanocrystal‐templated silica is developed. Through a careful balance of the intermolecular interactions between a lyotropic tetraalkoxysilane/cellulose nanocrystal dispersion and water‐soluble polyacrylic acid/mercaptopropionic acid‐stabilized CdS quantum dots, CdS/silica/nanocellulose composites that retain both chiral nematic order of the cellulose nanocrystals and emission of the quantum dots are successfully co‐assembled. Subsequent removal of the cellulose template and organic stabilizers in the composites by controlled calcination generates new freestanding iridescent, luminescent chiral nematic mesoporous silica‐encapsulated CdS films. The pores of these materials are accessible to analytes and, consequently, the CdS quantum dots undergo strong luminescence quenching when exposed to TNT solutions or vapor.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".