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Record W3101147436 · doi:10.3390/membranes10110335

Impacts of Multilayer Hybrid Coating on PSF Hollow Fiber Membrane for Enhanced Gas Separation

2020· article· en· W3101147436 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

VenueMembranes · 2020
Typearticle
Languageen
FieldEngineering
TopicMembrane Separation and Gas Transport
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMaterials scienceCoatingMembranePolydimethylsiloxaneGas separationLayer (electronics)Chemical engineeringPolysulfoneComposite materialLayer by layerPolymerChemistry

Abstract

fetched live from OpenAlex

One of the most critical issues encountered by polymeric membranes for the gas separation process is the trade-off effect between gas permeability and selectivity. The aim of this work is to develop a simple yet effective coating technique to modify the surface properties of commonly used polysulfone (PSF) hollow fiber membranes to address the trade-off effect for CO2/CH4 and O2/N2 separation. In this study, multilayer coated PSF hollow fibers were fabricated by incorporating a graphene oxide (GO) nanosheet into the selective coating layer made of polyether block amide (Pebax). In order to prevent the penetration of Pebax coating solution into the membrane substrate, a gutter layer of polydimethylsiloxane (PDMS) was formed between the substrate and Pebax layer. The impacts of GO loadings (0.0–1.0 wt%) on the Pebax layer properties and the membrane performances were then investigated. XPS data clearly showed the existence of GO in the membrane selective layer, and the higher the amount of GO incorporated the greater the sp2 hybridization state of carbon detected. In terms of coating layer morphology, increasing the GO amount only affected the membrane surface roughness without altering the entire coating layer thickness. Our findings indicated that the addition of 0.8 wt% GO into the Pebax coating layer could produce the best performing multilayer coated membrane, showing 56.1% and 20.9% enhancements in the CO2/CH4 and O2/N2 gas pair selectivities, respectively, in comparison to the membrane without GO incorporation. The improvement is due to the increased tortuous path in the selective layer, which created a higher resistance to the larger gas molecules (CH4 and N2) compared to the smaller gas molecules (CO2 and O2). The best performing membrane also demonstrated a lower degree of plasticization and a very stable performance over the entire 50-h operation, recording CO2/CH4 and O2/N2 gas pair selectivities of 52.57 (CO2 permeance: 28.08 GPU) and 8.05 (O2 permeance: 5.32 GPU), respectively.

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 score0.060
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 head0.022
GPT teacher head0.267
Teacher spread0.245 · 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