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Record W4313519693 · doi:10.3390/mi14010128

Membrane Surface Modification via In Situ Grafting of GO/Pt Nanoparticles for Nitrate Removal with Anti-Biofouling Properties

2023· article· en· W4313519693 on OpenAlexaff
Mohammad Khajouei, Mahsa Najafi, Seyed Hamed Jafari, Mohammad Latifi

Bibliographic record

VenueMicromachines · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsPolytechnique Montréal
FundersBabol Noshirvani University of Technology
KeywordsBiofoulingMembraneNanofiltrationPolysulfoneChemical engineeringContact angleNanoparticlePhase inversionPermeationMaterials scienceSurface modificationGraftingChemistryNanotechnologyComposite material

Abstract

fetched live from OpenAlex

Nanofiltration processes for the removal of emerging contaminants such as nitrate are a focus of attention of research works as an efficient technique for providing drinking water for people. Polysulfone (PSF) nanofiltration membranes containing graphene oxide (GO)/Pt (0, 0.25, 0.5, 0.75, 1 wt%) nanoparticles were generated with the phase inversion pathway. The as-synthesized samples were characterized by FTIR, SEM, AFM, and contact angle tests to study the effect of GO/Pt on hydrophilicity and antibacterial characteristics. The results conveyed that insertion of GO/Pt dramatically improved the biofouling resistance of the membranes. Permeation experiments indicated that PSF membrane embracing 0.75 wt% GO/Pt nanoparticles had the highest nitrate flux and rejection ability. The membrane's configuration was simulated using OPEN-MX simulating software indicating membranes maintaining 0.75 wt% of GO/Pt nanoparticles revealed the highest stability, which is well in accordance with experimental outcomes.

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 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 score0.427

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 studies0.0000.000
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 head0.029
GPT teacher head0.254
Teacher spread0.225 · 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 teacher head, 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

Citations15
Published2023
Admission routes1
Has abstractyes

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