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Record W4391876360 · doi:10.1063/5.0194144

On the clustering of triacylglycerols in the molten state

2024· article· en· W4391876360 on OpenAlexafffund
Gianfranco Mazzanti, Antonio De Nicola, David A. Pink, Antonio Pizzirusso, Philipp L. Fuhrmann, N. L. Green, R. Liu, C. P. Adams, Giuseppe Milano, Dérick Rousseau, Alejandro G. Marangoni

Bibliographic record

VenuePhysics of Fluids · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Chemistry and Fat Analysis
Canadian institutionsToronto Metropolitan UniversityUniversity of GuelphSt. Francis Xavier UniversityDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaNational Institute of Standards and TechnologyU.S. Department of Commerce
KeywordsPhysicsCluster analysisState (computer science)Statistical physicsThermodynamicsMechanicsAlgorithmArtificial intelligence

Abstract

fetched live from OpenAlex

The liquid–solid phase transition of triacylglycerols (TAGs), the main components of edible fats and oils is central to the production and sensory properties of many processed foods. While there has been extensive research on the nucleation and growth of fats, there remains a dearth of knowledge regarding the structural organization of TAGs in the liquid state. From a molecular perspective, TAGs consist of three alkyl chains esterified to a glycerol backbone. Several models based on experiment and simulation have helped to unveil TAG organization in the molten state. However, more evidence for their structural organization is necessary. Here, we provide simulation and experimental insights on the structural organization of molten tripalmitin using small-angle neutron and x-ray scattering, and wide-angle x-ray scattering. In agreement with recent work, we also propose a model in which TAGs associate as clusters via glycerol-glycerol interactions, with their alkyl chains extending outwards in a loose shell. Our model, however, highlights and demonstrates the dynamic nature of clusters, where TAGs can transfer from one cluster to another via diffusion. The average number of TAG molecules per cluster varies from 5 to 9 and decreases with increasing temperature, which results in a smaller average distance between clusters. Overall, this study strongly suggests that prior to the onset of nucleation, TAGs are associated as dynamic clusters formed via intermolecular interactions between neighboring glycerol cores.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.172
Threshold uncertainty score0.049

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.028
GPT teacher head0.237
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2024
Admission routes2
Has abstractyes

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