MétaCan
Menu
Back to cohort
Record W2472800391 · doi:10.1021/acssuschemeng.6b01144

Engineering Green Lubricants IV: Influence of Structure on the Thermal Behavior of Linear and Branched Aliphatic Fatty Acid-Derived Diesters

2016· article· en· W2472800391 on OpenAlexafffund
Latchmi Raghunanan, Suresh S. Narine

Bibliographic record

VenueACS Sustainable Chemistry & Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicLubricants and Their Additives
Canadian institutionsTrent University
FundersNatural Sciences and Engineering Research Council of CanadaIndustry CanadaTrent UniversityGrain Farmers of Ontario
KeywordsThermogravimetric analysisChemistryBranching (polymer chemistry)Saturation (graph theory)EvaporationThermal decompositionFatty acidOrganic chemistryLubricantChemical engineeringPolymer chemistryThermodynamics

Abstract

fetched live from OpenAlex

Fatty acid-derived aliphatic diesters and their branched derivatives are lubricating compounds that demonstrate predictable viscosity temperature profiles and remain fluid at extremely low temperatures. In this work, the influence of molecular structure on the high temperature thermal behavior of several series of aliphatic fatty acid-based diesters was investigated using thermogravimetric analyses (TGA). Evaporation behavior was determined as a function of molecular weight, saturation, symmetry and double bond position, and decomposition behavior as a function of molecular weight, branching, saturation and symmetry. The results revealed that the diol-derived diesters underwent predictable molecular weight-mediated evaporation, and that further refinement of the predicted evaporation temperatures could be obtained by accounting for saturation in the fatty acid moieties. Double bond position and symmetry did not measurably influence the evaporation temperatures of the diesters. Evaporation was successfully suppressed with increasing molecular weight, with the fatty acid chain length and the nature of the branched group being most important in the linear and branched diesters, respectively. Overall, these results are fundamentally significant because they provide the background necessary to make informed changes to molecular structure so as to effect the desired high temperature behavior in renewably sourced specifically engineered materials for lubricant applications.

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 score0.002

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 head0.004
GPT teacher head0.175
Teacher spread0.172 · 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

Citations11
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueACS Sustainable Chemistry & EngineeringSame topicLubricants and Their AdditivesFrench-language works237,207