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Record W2018270339 · doi:10.1021/la8035665

Solvent-Modulated Nucleation and Crystallization Kinetics of 12-Hydroxystearic Acid: A Nonisothermal Approach

2009· article· en· W2018270339 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLangmuir · 2009
Typearticle
Languageen
FieldMaterials Science
TopicCrystallization and Solubility Studies
Canadian institutionsUniversity of GuelphUniversity of Saskatchewan
Fundersnot available
KeywordsNucleationKineticsCrystallizationSolventChemistryChemical engineeringThermodynamicsMaterials scienceOrganic chemistryPhysical chemistryPhysics

Abstract

fetched live from OpenAlex

The solvent type strongly affects the nucleation behavior of 12HSA and therefore strongly influences the peak nucleation rate, fiber length, spatial distribution of mass, and degree of branching. Using nonisothermal kinetic models, a correlation was established among the activation energy of nucleation, fiber length, and induction time of 12HSA nucleation in different solvents. However, there was no correlation between any measurable parameter and solvent polarity. Activation energies varied from 2.2 kJ/mol in methyl oleate to 15.8 kJ/mol in glycerol. Nucleation behavior and structure were strong functions of the cooling rate, with distinct regions observed above and below 5-7 degrees C/min for fiber length, induction time, rate constant, and peak nucleation rate. The abrupt changes in the rate of nucleation, crystal growth rate constant, and degree of branching around this cooling rate are related to whether the nucleation and crystal growth processes are governed by mass transfer or thermodynamics. Furthermore, the Avrami equation accurately predicted several structural features of the fibrillar network such as fiber length and, to a lesser extent, induction time.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.635
Threshold uncertainty score0.327

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 head0.016
GPT teacher head0.234
Teacher spread0.218 · 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