Inverse Gas Chromatography Study of the Permeability of Aroma through Hydroxypropyl Xylan Films
Bibliographic record
Abstract
Inverse gas chromatography (IGC) was used to study the permeability of a series of aromas through neat hydroxypropyl xylan (HPX) film and HPX films containing sorbitol, a commonly used food grade plasticizer, and cellulose nanocrystal (CNC), a nanosized filler. The aroma used included methanol, ethanol, propanol, and butanol. Also, their solubility and diffusion coefficients at infinite dilution were measured over the temperature range 120–160 ° C, and the corresponding permeability coefficients were calculated. It was observed that the alcohols exhibited lower solubility (3 orders of magnitude) and diffusivity (2–3 orders of magnitude) than those of water in the neat HPX film. Solubility coefficient showed a minimum over the range of the molecular weight of the aforementioned alcohols. However, the diffusion coefficient decreased monotonically with increasing the alcohol’s molecular weight. Adding sorbitol (40 wt %) decreased solubility coefficients slightly but increased diffusion coefficients by about 1 order of magnitude. However, replacing 5 wt % of sorbitol by CNC while maintaining the total additive concentration at 40 wt % did not alter the solubility coefficients much but decreased diffusion coefficients by approximately half of the values of the HPX film containing 40 wt % sorbitol. Permeability, a quantity signifying the combined effect of solubility and diffusivity, was observed to decrease with increasing the alcohol’s molecular weight. This implies that diffusivity controls the permeability of the alcohols at high molecular weights. As expected, sorbitol increases while CNC decreases permeability. However, effects of additives are stronger for methanol and ethanol than for propanol and butanol. Temperature also exerts stronger effects for methanol and ethanol than for propanol and butanol. The above observation is likely due to the differences in the abilities of the low and high molecular weight alcohols to form hydrogen bonds with HPX, sorbitol, and CNC.
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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 | 0.001 |
| 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".