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Record W2335483295 · doi:10.1021/ie3016472

Lubricating and Waxy Esters II: Synthesis, Crystallization, and Melt Behavior of Branched Monoesters

2012· article· en· W2335483295 on OpenAlexafffund
Laziz Bouzidi, Shaojun Li, Steve Di Biase, Syed Q. A. Rizvi, Peter Dawson, Suresh S. Narine

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2012
Typearticle
Languageen
FieldMaterials Science
TopicPolymer crystallization and properties
Canadian institutionsTrent University
FundersTrent UniversityGrain Farmers of Ontario
KeywordsCrystallizationCrystallinityWaxBranching (polymer chemistry)Materials scienceMolar massGlass transitionPhase transitionChemical engineeringChemistryCrystallographyOrganic chemistryThermodynamicsPolymer

Abstract

fetched live from OpenAlex

A comprehensive study of branched derivatives of four pure jojoba wax-like esters (JLEs), having 36, 40 (two isomers), and 44 carbons was conducted to elucidate their crystallization and melting behavior. Crystallization and melting characteristics depended strongly on the number of branches, molar mass, and symmetry. The derivatives demonstrated a very strong tendency to form glassy liquids rather than crystal phases and remain liquid-like at very low temperatures. As the number of branches increased, their crystallinity decreased drastically while their glassy phase increased concomitantly with the depression of the onset of crystallization and/or glass transition temperature. A variety of possible transformation paths, ranging from very little polymorphic activity to extremely polymorphic behavior, depending on number of branches, mass, and symmetry were revealed. It is shown that asymmetry plays a large role in the low temperature behavior, rendering the branched derivatives of the asymmetrical JLEs much better candidates for lubricant formulations.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.088
GPT teacher head0.306
Teacher spread0.217 · 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 source (direct Gemma or distilled Codex), 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

Citations24
Published2012
Admission routes2
Has abstractyes

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