Engineering the nucleation of edible fats using a high behenic acid stabilizer
Bibliographic record
Abstract
A stabilizer high in behenic acid (HBS) was used to control nucleation of edible fats. The addition of HBS led to an enhanced nucleation of anhydrous milk fat (AMF) and palm oil (PO) which had lower levels of high melting triacylglycerols (HMTs) (melting point >30°C, relative to the temperature used to crystallize samples) compared to other fats. With the addition of 1.5% HBS, there was an increase in crystallization onset temperatures and density of the microstructure in these two fats. Further studies were conducted to investigate the interactions between HBS and specific homogeneous triacylglycerols (TAGs) or a mixture of triacylglycerols. HBS displayed solid‐state incompatibility (eutectic behavior) with tripalmitin and tristearin, whereas it displayed compatibility (monotectic partial solid solution formation) behavior when mixed with the high‐melting milk fat fraction (HMF). This suggests two mechanisms for nucleation enhancement of HBS. One mechanism would involve surface nucleation on top of pre‐formed TAG surfaces, for tripalmitin and tristearin, while the other mechanism would involve additionally co‐crystallization with the nucleating agent, for the case of milkfat's HMF. Practical application: HBS may be used to accelerate the nucleation of PO, AMF, and HMF. A slow crystallization behavior of PO often leads to post‐hardening problems and a long α‐lifetime. Thus, HBS has a potential to solve these issues. Our results showed that HBS is more effective on fats with relatively low amounts of HMTs (20–50%). In addition, the nucleation enhancing mechanism of HBS was more effective in a mixture of TAGs, rather than in pure TAGs. High behenic acid stabilizers (HBS) are used to stabilize fat‐structured and oil‐rich food products. It is shown that HBS interacts with high‐melting triacylglycerols (HMTs) present in the fats and oils to be stabilized and reduces their free energy of nucleation, as shown in the graphical abstract. This leads to the formation of large numbers of smaller, stabilizing crystals in the system. Moreover, it also shown that HBS interacts differently with different HMTs. It displays incompatibility with tristearin and tripalmitin but displays compatibility with the high melting fraction of milkfat. A greater molecular compatibility is postulated to lead to greater stabilization.
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 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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".