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Record W4390989506 · doi:10.1039/d3cc06063b

Recent advances in phase change materials for thermal energy storage

2024· article· en· W4390989506 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

VenueChemical Communications · 2024
Typearticle
Languageen
FieldEngineering
TopicPhase Change Materials Research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPhase changeThermal energy storageThermalMaterials scienceThermal insulationEnergy storagePhase (matter)Phase-change materialWaste heatThermal energyProperty (philosophy)Energy (signal processing)Process engineeringEnvironmental scienceEngineering physicsMechanical engineeringNanotechnologyThermodynamicsChemistryEngineeringPhysicsLayer (electronics)

Abstract

fetched live from OpenAlex

Efficient storage of thermal energy can be greatly enhanced by the use of phase change materials (PCMs). The selection or development of a useful PCM requires careful consideration of many physical and chemical properties. In this review of our recent studies of PCMs, we show that linking the molecular structures of organic molecules to their physical properties can be used to focus attention on the most useful PCMs, including eutectic mixtures. Two of the major limitations concerning broader use of phase change materials are low thermal conductivity, especially for organic phase change materials, and suitable containment. We have addressed both issues in our recent investigations of novel form-stable composite PCMs with a freeze-cast matrix. The use of thorough experimental investigations, including cycling of materials hundreds or thousands of times through the melt-freeze processes, promotes our goals of advancing the use of PCMs for increased energy efficiency and sustainability.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.422
Threshold uncertainty score0.408

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 head0.119
GPT teacher head0.384
Teacher spread0.265 · 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