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Record W2953019186 · doi:10.1021/cen-09713-scicon3

Plastic crystals could be solid-state refrigerants

2019· article· en· W2953019186 on OpenAlexaboutno aff
Sam Lemonick

Bibliographic record

VenueC&EN Global Enterprise · 2019
Typearticle
Languageen
FieldEngineering
TopicRefrigeration and Air Conditioning Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsRefrigerantFreonChlorofluorocarbonRefrigerator carPlastic crystalGas compressorOzone layerSolid-stateGreenhouse gasMontreal ProtocolWaste managementEnvironmental scienceProcess engineeringMaterials scienceChemistryPhase (matter)EngineeringMechanical engineeringEngineering physicsOzoneOrganic chemistryGeology

Abstract

fetched live from OpenAlex

Regulators and manufacturers started phasing out chlorofluorocarbon gas refrigerants like Freon in the late 1970s after scientists discovered that they could deplete the ozone layer. But their replacements, hydrochlorofluorocarbons and hydrofluorocarbons, are greenhouse gases. Some scientists and engineers have suggested using solid-state refrigerants to avoid those environmental issues, but their use has yet to be realized. Now researchers propose that so-called plastic crystal materials could be more effective refrigerants than previously studied solid-state materials (Nature 2019, DOI: 10.1038/s41586-019-1042-5). However, experts caution that major engineering challenges stand between these crystals and your fridge. In conventional refrigerators, standard refrigerants change from liquid to gas, absorbing energy from the air inside the refrigerator and cooling it. A compressor then increases the pressure and temperature of the gas, dumping that absorbed energy outside the refrigerator as hot air as the refrigerant returns to the liquid phase. Previously proposed solid-state alternatives could go through similar

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
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)0.0000.001

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 head0.006
GPT teacher head0.238
Teacher spread0.233 · 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 teacher head, not a consensus.

Study designSimulation or modeling
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

Citations0
Published2019
Admission routes1
Has abstractyes

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