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Record W2417362156 · doi:10.1021/acsami.6b03006

Development of Membrane-Based Desiccant Fiber for Vacuum Desiccant Cooling

2016· article· en· W2417362156 on OpenAlexaff
Yifan Yang, Dipak Rana, Christopher Q. Lan, Takeshi Matsuura

Bibliographic record

VenueACS Applied Materials & Interfaces · 2016
Typearticle
Languageen
FieldEngineering
TopicAdsorption and Cooling Systems
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsDesiccantMaterials scienceMembraneWater vaporHollow fiber membraneAbsorption (acoustics)FiberComposite materialMass transferChromatographyChemistry

Abstract

fetched live from OpenAlex

A novel hydrophobic membrane-based desiccant fiber (MDF) was developed by loading lithium chloride into hydrophobic hollow fiber membranes. The MDF thus made was then tested for vapor absorption under controlled conditions. Furthermore, an MDF pad, which was made by weaving MDF into a piece of garment, was built into a laboratory vacuum desiccant cooling (VDC) setup, which included the MDF pad as the desiccant layer and a cooling towel saturated with water as the water reservoir, to test the cooling effects at atmospheric pressure and vacuum of 25 in. of Hg. Results indicate that MDF is suitable for applications such as in VDC. Mass and heat transfer of vapor absorption by MDF were also analyzed.

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 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 score0.012
Threshold uncertainty score0.652

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 head0.020
GPT teacher head0.225
Teacher spread0.205 · 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.

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

Citations12
Published2016
Admission routes1
Has abstractyes

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