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Record W2084042507 · doi:10.5539/mas.v1n4p83

Effect of the First Coagulating Bath Composing on the Structure of PES Membrane

2007· article· en· W2084042507 on OpenAlexvenueno aff
Zhenlei Li

Bibliographic record

VenueModern Applied Science · 2007
Typearticle
Languageen
FieldEngineering
TopicMembrane Separation and Gas Transport
Canadian institutionsnot available
Fundersnot available
KeywordsMass fractionMembraneFraction (chemistry)ChemistryMembrane structureFlux (metallurgy)CastingCoagulationChromatographyChemical engineeringMaterials scienceComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

Make PES flat-sheet style membrane through the method of dual-bath coagulation method. Change the composing of the first coagulating bath and make the casting membrane liquid stay in the first coagulating bath for enough time and control the surface and interior structure of the membrane at the same time. Study the interior and exterior structure when the DMAc mass fraction of first coagulating bath is among 0%-70%, and find out with the increase of mass fraction, the interior structure of membrane transits from the form of finger pore to the form of spongy pore, and when the mass fraction of the first coagulating bath achieves 70%, there is no structure with the form of finger pore, but the opening structure on the membrane surface appears when the mass fraction is 60% and increases with the increase of concentration. When the mass fraction of the first coagulating bath is among 0%-50%, the pure water flux of the membrane decreases with the concentration, and the rejection ratio of BSA change less, and when the concentration of the first coagulating bath exceeds 60% and the openings appear on the membrane surface, the pure water flux would ascend but the rejection ratio would markedly decrease.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.006
GPT teacher head0.219
Teacher spread0.213 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2007
Admission routes1
Has abstractyes

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