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Record W4410877639 · doi:10.1016/j.crgsc.2025.100460

Innovative membrane engineering: Polyphenylsulfone/silver-doped zinc oxide for high-efficiency protein rejection

2025· article· en· W4410877639 on OpenAlexaff
H. R. Panchami, Arun M. Isloor, A.M. Vijesh, Ramin Farnood

Bibliographic record

VenueCurrent Research in Green and Sustainable Chemistry · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsUniversity of Toronto
FundersVision Group on Science and TechnologyNational Institute of Technology Karnataka, Surathkal
KeywordsZincDopingMembraneMaterials scienceOxideMetallurgyNanotechnologyEngineeringChemical engineeringChemistryOptoelectronicsBiochemistry

Abstract

fetched live from OpenAlex

: In the present study, the nanocomposite polyphenylsulfone (PPSU) flat sheet membranes containing silver-doped zinc oxide (Ag-ZnO) was synthesized by the dry/wet phase inversion technique. Spectroscopic characterizations confirmed the nanoparticle incorporation into the membrane matrix. Microscopic characterization validates that, Ag-ZnO nanoparticles were distributed uniformly throughout the membrane. The Ag-ZnO modified PPSU membranes were evaluated for their protein rejection performances against BSA, egg albumin and pepsin from their aqueous solutions. PPSU composite membranes with 1.5 wt.% Ag-ZnO nanoparticles showed enhanced pure water permeability and protein rejection properties compared to the neat membrane. Increased permeability, antifouling nature and rejection of proteins were attributed to the cumulative effects of adding Ag-ZnO nanoparticle into the membrane.The highest protein rejection was exhibited by the membrane AZM-2 for BSA, egg albumin and pepsin were 92.1%, 86.8% and 73.4%, 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.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.016
Threshold uncertainty score0.709

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.026
GPT teacher head0.318
Teacher spread0.292 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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