Effect of Humidity on the Permeability of Alcohols in Hydroxypropyl 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 30%, 50%, and 70% of the carrier gas (helium). Permeability was then calculated using the measured diffusivity and solubility. Solubility coefficients of the alcohols were more or less insensitive to the RH. Increasing humidity from dry to 50% RH increased diffusion coefficients of the alcohols due to plasticization and swelling of the films whereas at higher RH, diffusion coefficient of the alcohols decreased. Based on the water contents of the films estimated from the weight-fraction-based Henry’s constant, at 70% RH, water clustering was the reason for the reduced diffusion coefficient in the neat HPX films while alcohol–water clustering was suggested for HPX/sorbitol and HPX/Sorbitol/CNC films. Permeability coefficients of the alcohols exhibited a maximum at around 50% RH as well suggesting that diffusion, not dissolution, dominated the permeability behavior. The findings suggest that due to sensitivity of the films to humidity, films should be used along with water barrier films to control humidity of the environment for applications used as barrier to alcohols.
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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".