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Record W2778104658 · doi:10.1139/cjc-2017-0578

Molecular structure and melting: implications for phase change materials

2017· article· en· W2778104658 on OpenAlexafffundvenue
John A. Noël, Samer Kahwaji, Mary Anne White

Bibliographic record

VenueCanadian Journal of Chemistry · 2017
Typearticle
Languageen
FieldEngineering
TopicPhase Change Materials Research
Canadian institutionsDalhousie University
FundersDalhousie UniversityNatural Sciences and Engineering Research Council of CanadaQueen's UniversityMcGill University
KeywordsEnthalpyAlkylMelting temperatureChemistryThermodynamicsMelting pointPhase changeEntropy (arrow of time)Phase (matter)Entropy of fusionEnthalpy of fusionOrganic chemistryMaterials science

Abstract

fetched live from OpenAlex

Phase change materials (PCMs) offer a promising technology for thermal energy storage, load leveling, and peak shifting applications. A desirable PCM has a melting temperature within the temperature boundaries of its application and a high change in enthalpy on melting. Knowledge of the relationships between these thermodynamic properties and molecular structure would advance informed selection of PCM candidates for a given application. In the present investigation, the relationship between structure (length of alkyl chains) and melting properties has been investigated for isomeric esters, showing that esters containing longer individual alkyl chains have higher melting temperatures and higher enthalpy changes on melting. The melting entropy changes, however, are relatively independent of the alkyl chain distribution.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.055
GPT teacher head0.322
Teacher spread0.267 · 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

Citations28
Published2017
Admission routes3
Has abstractyes

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