Chiral Hybrid Mesoporous Silicas: Assembly of Uniform Hollow Nanospheres and Helical Nanotubes with Tunable Diameters
Bibliographic record
Abstract
Uniform helical silica nanotubes and hollow silica nanostructures with adjustable diameters have been prepared through the self-assembly of sodium dodecyl sulfate (SDS) as the surfactant, N -trimethoxysilylpropyl- N,N,N -trimethylammoniumchloride (TMAPS) as a costructure directing agent (CSDA), a binapthyl-based chiral dopant, and TEOS (Si(OEt) 4 ) as the bulk silica constituent. Depending on the ratio of anionic surfactant to cationic costructure directing agent, the morphology can be tuned from hollow spheres to hollow nanotubes. At a 1:1 ratio of TMAPS/SDS, in the presence of the axially chiral dopant molecule, uniformly helical structures are obtained. The chirality of the dopant is shown to affect the sense of helicity. Under identical conditions, a monosilylated chiral dopant only leads to the formation of well dispersed uniform hollow spheres rather than helical nanotubes, which further demonstrates the importance of incorporating the chiral dopant as an integral component of the siloxane network, rather than merely as a surface group.
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".