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Record W3113442200 · doi:10.1016/j.apsadv.2020.100051

Explication of hydrophobic silica as effective pore former for membrane fabrication

2020· article· en· W3113442200 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

VenueApplied Surface Science Advances · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsUniversity of Ottawa
FundersUniversiti Teknologi PetronasMinistry of Higher Education
KeywordsHydrophobic silicaMembraneContact angleChemical engineeringHydrophobeFiltration (mathematics)PermeanceMaterials scienceHydrophobic effectChemistryChromatographyPolymer chemistryOrganic chemistryPermeation

Abstract

fetched live from OpenAlex

Membrane development is one of the key aspects to enhance the productivity of a filtration process. This study evaluates a hydrophobic silica as pore former for fabrication of polyvinylidene difluoride (PVDF) membrane for liquid based filtration and compare it with a hydrophilic silica. Membranes incorporated with hydrophobic (M-series) and hydrophilic silica (N-series) with loadings of 1, 2 and 3 wt% in the dope solution were fabricated, characterized and subjected to filtration tests using feeds of pure water, raw wastewater, secondary effluent, microalgae solution and activated sludge. Results show that the hydrophobic silica remained within the membrane matrix (7.24% of elemental Si by EDS), almost three-fold higher than the hydrophilic silica (2.48%). It turned the membrane surface to be more hydrophobic ascribed by increasing water contact angle from 87° from the pristine PVDF membrane up to 97° for the membrane with the highest loading of hydrophobic silica. On the other hand, the addition of hydrophilic decreased the contact angle down to 67° for the membrane with the highest loading. Loading hydrophobic silica enhanced the dope solution viscosities up to 1825–2000 cP, upon dropwise addition of nonsolvent (water), whereas the viscosity remained at 880–950cP for the hydrophilic silica. Addition of hydrophobic silica increased the number of surface pore without significantly altering the pore size of about 0.12 µm. On the other hand, an increase in the pore size (up to 0.33 µm) was observed when hydrophilic silica was added. Despite the smaller pore size, the pure water permeance of the hydrophobic silica loaded membranes (450–984 L/m2hbar) outperformed the hydrophilic silica loaded membranes (420–600 L/m2hbar) due to their higher surface porosities thanks to the higher number of surface pores. The filtration results of multiple feeds showed the advantages of loading more hydrophobic silica in improving the hydraulic performance. The findings demonstrate the efficacy of hydrophobic silica as pore former in PVDF membrane fabrication.

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 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 score0.018
Threshold uncertainty score0.525

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.011
GPT teacher head0.264
Teacher spread0.254 · 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