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Record W2126995323 · doi:10.1142/s0219581x11008228

A REVIEW OF ASSEMBLED POLYACRYLONITRILE-BASED CARBON NANOFIBER PREPARED ELECTROSPINNING PROCESS

2011· review· en· W2126995323 on OpenAlex
Agung Mataram, Ahmad Fauzi Ismail, Mohd Sohaimi Abdullah, Be Cheer Ng, T. MATSUURA

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

VenueInternational Journal of Nanoscience · 2011
Typereview
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPolyacrylonitrileElectrospinningMaterials scienceNanofiberPolymerVolumetric flow rateFiberComposite materialNanotechnologyNanometrePolymer solutionChemical engineering

Abstract

fetched live from OpenAlex

Electrospinning is a very simple and versatile process by which polymer nanofibers with diameters ranging from a few nanometers to several micrometers can be produced using an electrostatically driven jet of polymer solution (or polymer melt). Significant progress has been made in this process throughout the last decade and the resultant nanostructures have been exploited to a wide range of applications. An important feature of the electrospinning process is that electrospinning nanofibers are produced in atmospheric air and at room temperature. This paper reviews the assembled polyacrylonitrile (PAN)-based carbon nanofibers with various processing parameters such as electrical potential, distance between capillary and collector drum, solution flow rate (dope extrusion rate), and concentration of polymer solution. The average fiber diameter would increase with increasing concentration of the polymer solution and the flow rate. Therefore, the screen distance could also increase but the average electrical potential of the fibers diameter decreases. Electrospinning process can be conducted at higher electrical potentials, lower flow rate, nearer screen distance, and higher concentrations of dope.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.708
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0040.000
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 head0.032
GPT teacher head0.375
Teacher spread0.343 · 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