Evidence of Critical Cooling Rates in the Nonisothermal Crystallization of Triacylglycerols: A Case for the Existence and Selection of Growth Modes of a Lipid Crystal Network
Bibliographic record
Abstract
The isoconversional method, a model-free analysis of the kinetics of liquid-solid transformations, was used to determine the effective activation energy of the nonisothermal crystallization of melts of pure and complex systems of triacylglycerols (TAGs). The method was applied to data from differential scanning calorimetry (DSC) measurements of the heat of crystallization of purified 1,3-dilauroyl-2-stearoyl-sn-glycerol (LSL) and commercially available cocoa butter melts. The method conclusively demonstrated the existence of specific growth modes and critical rates of cooling at specific degrees of conversion. The existence of critical rates suggests that the crystallization mechanism is composed of growth modes that can be effectively treated as mutually exclusive, each being predominant for one range of cooling rates and extent of conversion. Importantly, the data suggests that knowledge of the critical cooling rates at specific rates of conversion can be exploited to select preferred growth modes for lipid networks, with concomitant benefits of structural organization and resultant physical functionality. Differences in transport phenomena induced by different cooling rates suggest the existence of thresholds for particular growth mechanisms and help to explain the overall complexity of lipid crystallization. The results of this model-free analysis may be attributed to the relative importance of nucleation and growth at different stages of crystallization. A mechanistic explanation based on the competing effects of the thermodynamic driving force and limiting heat and transport phenomena is provided to explain the observed behavior. This work, furthermore, offers satisfactory explanations for the noted effect of cooling-rate-induced changes in the physical functionality of lipid networks.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 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".