Moisture Transport Coefficients Determination on a Model Pharmaceutical Tablet
Bibliographic record
Abstract
In this work, a novel methodology to determine moisture transport coefficients for MMC PH101 tablets is presented. Absolute permeability, moisture diffusion, moisture transfer, and water vapor permeability coefficients were estimated on compressed powder tablets produced with different compression pressures (20 MPa to 200 MPa with an interval of 20 MPa). The ASTM D6539 standard test was used to measure the absolute permeability. The moisture transfer coefficient was determined from measured absolute permeability. The moisture diffusion coefficient was obtained with the tablet average pore radius, which was determined with the water droplet penetration method. Descriptive and phenomenological models derived from the measurements were confronted with existing and adopted models, and a good agreement was found. The obtained models are of the function of the microstructural properties of the tablet (average pore radius and average porosity). The tablet average porosity was found to be the principal parameter that governs the behavior of the moisture transport coefficients. The findings of this study might be applicable to obtain a series of input parameters for modelling software, such as COMSOL Multiphysics®, to infer delamination, sticking, and failure propensity from the effect of moisture.
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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 | 0.001 |
| 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) | 0.001 | 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".