Kinetics of 12-Hydroxyoctadecanoic Acid SAFiN Crystallization Rationalized Using Hansen Solubility Parameters
Bibliographic record
Abstract
Changes in solvent chemistry influenced kinetics of both nucleation and crystallization of 12-hydroxyoctadecenoic, as determined using differential scanning calorimetry and applying a modified Avrami model to the calorimetric data. Altering solvent properties influenced solvent–gelator compatibility, which in turn altered the chemical potential of the system at the onset of crystallization, the kinetics of gelation, and the resulting 12HOA crystal fiber length. The chemical potential at the onset of crystallization was linearly correlated to both the hydrogen-bonding Hansen solubility parameter and the solvent–gelator vectorial distance in Hansen space, R a . Our work suggests that solvent properties can be modulated to affect the solubility of 12HOA, which in turn influences the kinetics of crystallization and the self-assembly of this organogelator into supramolecular crystalline structures. Therefore, modulation of solvent properties during organogelation can be used to control fiber length and thus engineer the physical properties of the gel.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".