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Highly Hydrophilic Electrospun Polyacrylonitrile/ Polyvinypyrro-lidone Nanofibers Incorporated with Gentamicin as Filter Medium for Dam Water and Wastewater Treatment

2016· article· en· W2500220813 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Membrane and Separation Technology · 2016
Typearticle
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsnot available
FundersOffice of Experimental Program to Stimulate Competitive ResearchKansas NSF EPSCoRWichita State UniversityNational Science Foundation
KeywordsPolyacrylonitrileNanofiberElectrospinningGentamicinWastewaterChemistryPulp and paper industryChemical engineeringMaterials scienceComposite materialEnvironmental scienceEnvironmental engineeringPolymerOrganic chemistryAntibioticsEngineering

Abstract

fetched live from OpenAlex

The need for advancement in filtration technology has spurred attention to advanced materials, such as electrospun nanofiber membranes, for providing clean water at a low cost with minimum initial investment. Polymer nanofibers can be fabricated by using different techniques, such as template synthesis, self-assembly, drawing, phase separation, and electrospinning. Due to its distinctive properties, electrospinning has become a method of choice for fabricating nanofiber membranes quickly with minimal investment. In this study, polyacrylonitrile (PAN) was dissolved in dimethylformamide (DMF), and different weight percentages of polyvinylpyrrolidone (PVP) and gentamicin sulfate powder were added to the solution to fabricate nanomembranes via the electrospinning process. Gentamicin was added to remove bacteria and viruses and prevent fouling, while PVP was added to make the surface of the membrane hydrophilic for enhancing the filtration rate and efficiency. Two water samples were chosen for the filtration processes: dam water and city wastewater. For the dam water sample, PH, turbidity, TDS, Ca++, Mg++, sulfates, nitrates, fluoride, chloride, alkalinity and silica were reduced to +3.64%, 89.6%, 6.52%, 10.5%, 9.96%, 5.16%, 17%, 19.5%, 6.63%, 1.43% and 63.5% respectively. The total coliforms and E. coli content were reduced to 4.1 MPN/100ml and 0 MPN/100ml, respectively with PAN containing 10 wt. % PVP and 5 wt. % Gentamicin. For wastewater sample, PH, turbidity, TDS, TSS, BODs, phosphate, ammonia, oil-greases and DO were reduced to + 3.62%, 79%, 6.33%, 84%, 68%, 1.70%, 15.8%, 0% and 6% respectively. The total coliforms and E. coli content were also lowered to 980 MPN/100ml and 1119.9 MPN/100ml, respectively with PAN containing 10 wt. % PVP and 5 wt. % Gentamicin. The morphology and dimensions of the nanofibers were observed using a scanning electron microscope (SEM). Both SEM and microscopic images of the nanomembrane before and after filtration proved that electrospun PAN nanofibers have superior water filtration performance.

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 score0.019
Threshold uncertainty score0.455

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 head0.007
GPT teacher head0.246
Teacher spread0.239 · 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