Effect of Humidity on the Permeability of Alcohols in Hydroxylpropyl Xylan Films
Bibliographic record
Abstract
Inverse gas chromatography (IGC) was used to study the effect of humidity on the permeability of selected low molecular weight alcohols (methanol, ethanol, propanol and butanol) through films made up of a hydrophilic polymer hydroxypropyl xylan (HPX).The thin films used consisted of a neat HPX film and a HPX film with sorbitol, a commonly used food grade plasticizer, (HPX/Sorbitol) and a HPX film with sorbitol and cellulose nanocrystal (CNC) (HPX/Sorbitol/CNC).Diffusivity and solubility of the alcohols at infinite dilution were measured at relative humidity (RH) values of 0%, 30%, 50% and 70% of the carrier gas (helium).Permeability was then calculated using the measured diffusivity and solubility.Diffusion coefficients of the alcohols showed a maximum at about 50% RH in all films.And solubility coefficients of the alcohols were more or less insensitive to the RH.Permeability coefficients of the alcohols exhibited a maximum at around 50% RH as well suggesting that diffusion, not dissolution, dominated the permeability behaviour.The RH dependence of diffusion, thereby permeability, was attributed to the combined effects of plasticizing, swelling, water clustering and alcohol-water clustering.The measured weight-fraction-based Henry's constants suggested that water contents in the films were relatively low, suggesting that water clustering might only take place in the neat HPX film at 70% RH.
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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) | 0.000 | 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 | 0.001 |
| 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".