Heterogeneous Nucleation of 1,3-Distearoyl-2-oleoylglycerol on Tristearin Surfaces
Bibliographic record
Abstract
The following work investigates the heterogeneous nucleation of 2-oleodistearin (SOS) triglycerides on surfaces formed by crystals of tristearin triglyceride (SSS). This work shows, through computer simulations and nucleation kinetics, that SOS may heterogeneously nucleate on SSS surfaces. Atomic-scale molecular dynamics showed that SOS molecules exhibited an affinity to a simulated SSS surface. Nucleation kinetics using differential scanning calorimetry showed that the inclusion of minor amounts of SSS (from 1 to 4%) in an SOS melt resulted in an increase in the isothermal nucleation rate of crystallizing SOS. Using a model based on the Fisher-Turnbull approach, estimates of the surface free energy, activation free energy, and the critical radius were calculated from the nucleation rates. The estimated parameters demonstrate the heterogeneous nucleation of SOS on SSS surfaces: reduced surface free energies, activation free energies, and critical radii with the inclusion of SSS in an SOS melt. This may point to strategies to enhance the nucleation of one of the three major triglycerides present in cocoa butter and the one that crystallizes first from the melt for better control of the chocolate tempering process.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".