Molecular sorption and diffusion of organic solvents through maleated rubber/layered silicate nanocomposites
Bibliographic record
Abstract
The aim of the study is to investigate barrier properties of a nanocomposite material against organic solvents. Molecular transport phenomena of three alcohols, namely methanol, ethanol and isopropanol, through a nitrile rubber-based nanocomposite, are carried out in temperatures ranging from 23 to 70°C. For each configuration, mass transfer kinetics are investigated for three different types of clay nanoparticles using mass uptake experiments. Maleated nanocomposites with enhanced dispersion morphology are also examined. Results show that all molecular transport parameters are generally susceptible to temperature variations. Sorption and diffusion coefficients noticeably increased as temperatures increased. Polymer/solvent interaction seems to be similarly affected. Molecular volume of the penetrant is observed to have an influence on molecule migration. Diffusion coefficients are likewise affected and decrease with the linear increase of molecular volume. The diffusion mechanism is slightly altered by this factor and the Fickian mode is maintained. When filling the rubbery matrix with layered silicates, sorption decreases at equilibrium. Its level drops even lower with the maleation of the nanocomposite. However, the diffusion coefficient exhibits a less systematic trend. Randomly filled nanocomposites appear to have higher diffusivity than neat rubber, but diffusion parameter considerably decreases after maleation, which emphasizes the nanoclay’s dispersion effect.
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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".