Direct Synthesis of Functional Mesoporous Silica by Neutral pH Nonionic Surfactant Assembly: Factors Affecting Framework Structure and Composition
Bibliographic record
Abstract
The preparation of a wide range of organically functionalized wormhole-motif and hexagonal mesoporous MSU-X silicas was achieved by a one-step synthesis process involving the simultaneous addition of tetraethoxysilane (TEOS) and 3-mercaptopropyltrimethoxysilane (MPTMS) to solutions of structure-directing nonionic surfactant micelles, followed by fluoride-mediated hydrolysis/cross-linking and surfactant extraction. The effect of various synthesis parameters, including relative reagent concentration (MPTMS/TEOS ratio), temperature, and surfactant type, on the structure and composition of the mesostructures was investigated. Generally, higher MPTMS/TEOS ratios resulted in materials with higher functional group loadings, while increasing temperature also produced more highly functionalized materials. Although increasing synthesis temperature produced materials with greater pore diameters and lattice spacings, an increased organosilane content in the mesostructures produced materials with diminished pore diameters and lattice spacings. Thus, MSU-X materials with fine-tuned composition and pore dimensions were produced by systematically varying these synthesis parameters. We propose that the amphiphilic character of the nonionic surfactants is affected both by temperature and by the addition of the comparatively hydrophobic organosilane constituent in the micelle, thus forming mesostructures with corresponding compositional and structural features.
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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) | 0.000 | 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".