CO<sub>2</sub> sorption and diffusion in polymethyl methacrylate–clay nanocomposites
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Bibliographic record
Abstract
Abstract This study reports the glass transition temperature ( T g ), and sorption and diffusion of subcritical CO 2 gas in polymethyl methacrylate (PMMA) nanocomposites containing organically modified smectite clay, Cloisite 20A (C20A). A range of methods for preparing the PMMA‐clay nanocomposites was investigated and a solution coprecipitation method was selected as the most appropriate. Using this method, PMMA nanocomposite containing 2, 4, 6, and 10 wt% nanoclay loadings were prepared. Wide‐angle X‐ray diffraction (XRD) analysis and scanning electron microscopy (SEM) indicated that the 2 wt% nanocomposite materials had a well‐dispersed intercalated clay structure. The T g for PMMA‐C20A nanocomposites, as measured by differential scanning calorimetry (DSC), was found to be independent of the clay loading. CO 2 solubility studies from 0 to 65°C and pressures up to 5.5 MPa using an in situ gravimetric technique were performed on compression‐molded films. The organoclay was found to have no effect on the solubility of CO 2 in PMMA, and therefore the solubility of CO 2 in the nanocomposite can be determined from the solubility of CO 2 in the matrix polymer alone. Diffusion coefficients were determined using the appropriate transport models for these test conditions and the diffusion coefficients for CO 2 in PMMA‐C20A composites were found to increase with organoclay loading. It is believed that the processing path taken to prepare the nanocomposites may have resulted in the agglomeration of the C20A organoclay, thereby preventing the polymer chains from fully wetting and intercalating a large number of clay particles. These agglomerations are responsible for the formation of large‐scale holes within the glassy nanocomposite, which behave as low resistance pathways for gas transport within the PMMA matrix. POLYM. ENG. SCI., 45:904–914, 2005. © 2005 Society of Plastics Engineers
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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 | 0.000 | 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 it