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Record W2530958243

Gas permeation through water-swollen sericin / PVA membranes

2007· dissertation· en· W2530958243 on OpenAlex
Se Jin Kim

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueUWSpace (University of Waterloo) · 2007
Typedissertation
Languageen
FieldEngineering
TopicMembrane Separation and Gas Transport
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPermeationSericinMembraneChemical engineeringPolymer scienceMaterials sciencePolymer chemistryChemistryComposite materialEngineeringSILK
DOInot available

Abstract

fetched live from OpenAlex

Silk sericin, a protein obtained from cocoons, is a highly hydrophilic macromolecular material with many hydroxyl, carboxyl and amino acid groups. Sericin has been used for cosmetics, medical, polymer materials and other applications due to its antioxidative, antibacterial, UV resistant and moisture-absorbing and -desorbing properties. On the other hand, polyvinyl alcohol (PVA) has been used as a membrane material because of its good film forming properties. In this study, sericin was blended with PVA to form membranes that are permselective to gases. Due to their hydrophilic properties a novel water-swollen sericin / PVA membrane was investigated for the gas permeation of carbon dioxide and nitrogen. 
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\nSilk sericin with molecular weights 26 - 170 kDa was obtained from cocoons by extraction with water. At 95 the yield of sericin was found to be 22.8% after 9 hrs of extraction. The sericin / PVA membranes were prepared by blending sericin and PVA followed by crosslinking with glutaradehyde. After drying, the membranes were heat treated at 120 for 1 hr. The membranes containing 0 to 30.3% sericin showed that the permeability was 2.7-4.0 Barrer for O2, 1.3-2.3 Barrer for N2 and 66.5- 28.8 Barrer for CO2, corresponding to a separation factor in the range of 48.3 to 60 for CO2/N2 and 1.4 to 2.2 for O2/N2. The membranes showed a favourable selectivity for CO2/N2 separation, which is relevant to CO2 capture from flue gas for green house gas emission control. 
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\nIn addition, the effects of water in the membrane on the membrane properties were evaluated. It was shown that the swelling of the membranes with water tended to improve the permeability and selectivity of the membranes due to the increased free volume available for gas transport in the membrane. The water vapor sorption and desorption were also studied, and the diffusion coefficient was determined. It was found that the membrane permeability depended on the water sorption uptake in water-swollen membranes.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.576
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)0.0010.000

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 head0.010
GPT teacher head0.211
Teacher spread0.201 · 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