MétaCan
Menu
Back to cohort
Record W3099074595 · doi:10.18280/acsm.440502

Preparation and Characterization of Matrix Hybrid Membranes Polyvinylidene Fluoride/Polyvinylpyrrolidone/Silica Gel/Zinc Oxide for Cr(VI) Removal from Water

2020· article· en· W3099074595 on OpenAlexvenueno aff
Mustapha Chabane, Chikh Melkaoui, B. Dahmani, Sihem Zahia Belalia

Bibliographic record

VenueAnnales de Chimie Science des Matériaux · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsPolyvinylidene fluorideMembraneFourier transform infrared spectroscopyMaterials sciencePolyvinylpyrrolidonePhase inversionZincFluorideChemical engineeringNuclear chemistryHexavalent chromiumPolymer chemistryChemistryChromiumInorganic chemistryMetallurgy

Abstract

fetched live from OpenAlex

Matrix hybrid membranes, based on polyvinylidene fluoride (PVDF), poly (N-vinylpyrrolidone) (PVP), silica gel (SG) and zinc oxide (ZnO) were synthesized by phase inversion via immersion precipitation method. The characterization of membrane samples was performed using Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), optical microscopy, contact angle, porosity, mean pore size and water permeability measurements. The FTIR analysis showed the appearance of new bands attributed to the functional groups of SG and ZnO. The XRD analysis confirmed a modification in the structure of membranes. The prepared membranes were used for the removal of hexavalent chromium (Cr(VI)) from aqueous solution. Membrane filtration experiments show that the water permeability and Cr(VI) rejection ratios increase with increasing the weight ratio ZnO (%)/SG (%). The maximum values of the Cr(VI) rejection rate and water permeability were respectively 85% and 685 L/m2hbar for weight ratios (0.75% of ZnO/0.25% of SG).

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)0.000
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 score0.001

Distilled classifier scores by category (both heads)

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 head0.025
GPT teacher head0.272
Teacher spread0.248 · 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

Citations6
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueAnnales de Chimie Science des MatériauxSame topicMembrane Separation TechnologiesFrench-language works237,207