Physicochemical Evaluation of Carbamazepine Microparticles Produced by the Rapid Expansion of Supercritical Solutions and by Spray-Drying
Bibliographic record
Abstract
PURPOSE: To compare the physical and physicochemical characteristics of carbamazepine microparticles prepared using two different methods: (1) the rapid expansion of supercritical solutions (RESS) and (2) the spray-drying process. METHODS: For both processes, microparticles were produced over a range of different temperatures (35 to 100 degrees C). For the RESS method, carbon dioxide was the solvent used over a pressure range of 2500 to 3500 psi. As for the spray-drying method, different organic solvents were used at atmospheric pressure. Comparison was based on morphology, crystalline structure, mean particle size, and size distribution of processed particles. The influence of process parameters on microparticles' characteristics was also investigated. Particles were analyzed using scanning electron microscopy (SEM), X-ray powder diffraction (XRPD), thermogravimetric analyzer (TGA), and differential scanning calorimetry (DSC). RESULTS: The carbamazepine particles used as unprocessed starting material had a mean diameter of approximately 85 microm with a size distribution range between 15 and 336 microm. Microparticles produced by either the RESS or spray-drying method had a mean diameter smaller than 2 microm and a narrower size distribution range between 0.25 and 2.5 microm. SEM photomicrographs, X-ray diffractograms, and DSC spectra revealed that modification of crystal morphology was dependent on the operating conditions. CONCLUSIONS: Significant reduction in mean particle size and size distribution range of carbamazepine particles was observed by RESS and spray-drying methods. The results also demonstrate that the crystalline nature of carbamazepine particles depends on the method of production and on the operating parameters of pressure and temperature.
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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) | 0.000 | 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 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".