A New Route to Monolithic Methylsilsesquioxanes: Gelation Behavior of Methyltrimethoxysilane and Morphology of Resulting Methylsilsesquioxanes under One-Step and Two-Step Processing
Bibliographic record
Abstract
Polymerization of methyltrimethoxysliane (MTMS) results in methylsilsesquioxane (MSQ), which has found important applications in recent years including use as low- k dielectric materials in the semiconductor industry, superhydrophobic materials, monolithic columns, and hybrid matrixes for immobilizing proteins. For polycondensation of MTMS in ethanolic solutions, we report the sol−gel behavior under two different sets of conditions. First, we examined one-step polymerization over a wide range of pH and show that the initial pH is important in determining both the gelation behavior of MTMS-derived sols and the morphology of the resulting MSQ materials. In the one-step method, we obtained either transparent precipitates and/or macroscopically phase-separated resins when the pH was below the isoelectric point (IEP) of the silanols; either macroscopically phase-separated resins or macroporous monolithic gels with pH > IEP; and homogeneous solutions when the pH was close to the IEP. We also report on the use of a two-step catalysis method using an initial acid catalysis step followed by a base-catalyzed condensation step (denoted as B2), which is able to produce bimodal micro/meso or trimodal micro/meso/macroporous MSQ monoliths, depending on the specific conditions employed. The resulting materials are shown to be more resistant to exposure to base relative to macroporous silica. These results indicate that MSQ materials derived by the two-step processing method should be useful for the development of chromatographic stationary phases and as porous materials for protein entrapment.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".