Exploring the confinement of polymer nanolayers into ordered mesoporous silica using advanced gas physisorption
Bibliographic record
Abstract
Over the last two decades, in parallel to the rise of ordered mesoporous silica, porous nanostructured polymer-silica composites have attracted the interest of material scientists due to their promising perspectives of application as sorbents, ion-exchangers, supports, and catalysts. While knowledge is available regarding their synthesis and applications, understanding and controlling their pore properties in order to rationalize their performances remain challenging tasks. Greater knowledge is therefore needed regarding their precise characterization, especially using gas adsorption. To this aim, mesoporous polymer-silica nanocomposites were synthesized from two ordered mesoporous silica materials using a pore-surface restricted polymerization technique. Hydrophobic polystyrene, PS, and hydrophilic poly(2-hydroxyethyl methacrylate), PHEMA, were specifically confined and polymerized in the pores of high-quality SBA-15 and KIT-6 silicas of different pore sizes. The physico-chemical characteristics of the resulting hybrid materials were probed in detail using gas physisorption at cryogenic temperatures (Ar at 87 K and N2 at 77 K). The polymer loadings and the interactions between the silica host and the polymer were investigated using thermogravimetric analysis coupled with differential thermal analysis (TGA-DTA) and attenuated total reflection infrared spectroscopy (ATR-FTIR). The effects of the pore structure, mode pore size and presence or absence of intra-wall pores in the silica hosts on the final composite characteristics were assessed as a function of the polymer type and loading. Two different polymer filling mechanisms were identified as a function of the polymer-silica interactions, resulting in important changes on the pore topology of the composites. The results of this study allow a better understanding of the nature of the confined interactions between hydrophilic and hydrophobic polymers and large pore mesoporous silicas and shed some light on fundamental aspects regarding the design of silica-based composites.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 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 teacher head, 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".