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Record W3152943072 · doi:10.30919/esmm5f458

Advances and Applications of Phase Change Materials (PCMs) and PCMs-based Technologies

2021· article· en· W3152943072 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

VenueES Materials & Manufacturing · 2021
Typearticle
Languageen
FieldEngineering
TopicPhase Change Materials Research
Canadian institutionsUniversity of Alberta
FundersBasic and Applied Basic Research Foundation of Guangdong ProvinceSouth China University of TechnologyKey Laboratory of Polymer Processing EngineeringGuangdong Academy of SciencesXiangtan UniversityNational Natural Science Foundation of China
KeywordsThermal energy storageEnergy storageLatent heatPhase changeRenewable energyProcess engineeringMaterials sciencePhase-change materialWaste heatThermal energyEnvironmental scienceMechanical engineeringEngineering physicsThermodynamicsEngineeringElectrical engineeringHeat exchangerPower (physics)

Abstract

fetched live from OpenAlex

It is necessary to develop new technologies for energy storage and use of renewable energy to improve energy efficiency. Phase change materials (PCMs) are a family of energy storage materials that are among one of the most suitable materials for storing and effectively utilizing renewable thermal energy. PCM-based latent heat storage (LHS) is more advantageous than sensible energy storage because of the high storage energy density per unit volume/mass and the smaller temperature difference between storing and releasing heat. However, PCMs have low a thermal conductivity and a high degree of supercooling that are affecting their efficiency for energy storage. This review article first introduces the principle of phase change energy storage and the classification of phase change energy materials. Then, the improvement of storage methods of PCMs, and the fundamental properties that affect the application of phase change materials are discussed in detail. The applications of PCMs in various fields are also reviewed, including in solar energy utilization, waste heat recovery, construction, and civil and medical use. Finally, it summarizes the research progress of PCMs and provides an outlook for future research.

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 categoriesMeta-epidemiology (narrow)
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 score0.029
Threshold uncertainty score1.000

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 head0.030
GPT teacher head0.296
Teacher spread0.266 · 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