Ultrasound-assisted theophylline polymorphic transformation: Selective polymorph nucleation, molecular mechanism and kinetics analysis
Bibliographic record
Abstract
In this paper, the ultrasound-assisted solvent-mediated polymorphic transformation of theophylline was explored in detail. The induction time and reconstruction time were significantly decreased by ultrasound, thereby decreasing the total transformation time and promoting the transformation process. The ultrasound-promoted efficiency of nucleation was different in three alcoholic solvents, which was difficult to explain by traditional kinetic effects. To resolve the above confusion, binding energies calculated by Density Functional Theory were applied to explore the relationship between the ultrasound-promoted efficiency of nucleation and solute-solvent interactions. Then, a possible molecular self-assembly nucleation pathway affected by ultrasound was proposed: the ultrasound could change and magnify the crucial effect of the specific sites of solute-solvent interactions in the nucleation process. Finally, the transformation kinetics with different effective ultrasonic energies was quantitatively analyzed by Avrami-Erofeev model, indicating that the dissolution element in the rate-limiting step was gradually eliminated by higher ultrasonic energy. Fortunately, the elusive crystal form V could be easily obtained by the ultrasound-assisted polymorph transformation. This proved to be a robust method to produce high purity form V of theophylline. The outcome of this study demonstrated that the proper ultrasonic irradiation had the potential to produce specific polymorphs selectively.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".