Direct Synthesis of Hybrid Organic−Inorganic Nanoporous Silica Microspheres. 1. Effect of Temperature and Organosilane Loading on the Nano- and Micro-Structure of Mercaptopropyl-Functionalized MSU Silica
Bibliographic record
Abstract
The preparation of a series of organically functionalized wormhole-motif microspherical MSU-X silicas mesostructures was achieved by a direct synthesis process involving the addition of tetraethoxysilane (TEOS) and 3-mercaptopropyltrimethoxysilane (MPTMS) to mildly acidified solutions of a structure-directing nonionic surfactant (Igepal CA-720), followed by fluoride-mediated hydrolysis/cross-linking and surfactant extraction. The influence of organosilane content (MPTMS/TEOS ratio) and synthesis temperature on the framework order, pore structure, and particle size of the resulting mesostructures was investigated. The lattice spacings, pore volumes, and pore diameters were found to systematically increase as a function of increasing synthesis temperature. Although very poorly ordered and microporous when prepared at lower synthesis temperatures, the framework ordering and pore channel diameters of the microspheres dramatically improved when these were synthesized at temperatures above 40−45 °C. Moreover, increasing the synthesis temperature reduced the average particle sizes of the microspheres, although a sudden swelling of the particle sizes was observed in the threshold temperature zone where improved framework order and mesoporosity in the microspheres was evidenced. Incorporation of organic functional groups (MPTMS) inside the structures appeared to have little influence on the structure and morphology of the mesostructures, save for slight lattice and pore diameter contractions upon increasing organosilane group loading. By systematically varying the organosilane content and the synthesis temperature of the microspheres, functional MSU-X materials with accurately fine-tuned pore dimensions and particle diameters could therefore be obtained.
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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".