Carbon Nanotube Reinforced Porous Gels of Poly(methyl methacrylate) with Nonsolvents as Porogens
Bibliographic record
Abstract
We fabricated porous organogels of poly(methyl methacrylate) (PMMA) using nonsolvents as porogens. In contrast to the use of inorganic materials, surfactants, etc., as porogens, we used the nonsolvents for PMMA such as water, methanol, propanol, and cyclohexane. This offers the advantage of not having to extract the porogen after gel formation. The nonsolvent simply evaporates. We find that the pore size can be controlled by matching the solubility parameters of the solvent/nonsolvent mixtures and that of PMMA. Incorporation of CNT itself does not lead to porous morphology in this case, unless a nonsolvent is added. Introducing carbon nanotubes during the addition of nonsolvent for gelation enhances the elongation ratio of the PMMA gel. We show that the CNT forms a network around the pores. Infrared and Raman spectra show no specific interaction between the CNT and PMMA. Hence, the former simply acts as a reinforcing filler.
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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 | 0.000 | 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 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".