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Record W2032983009 · doi:10.1109/ias.2010.5615276

Investigation of the Optimum Electric Field for a Stable Electrospinning Process

2010· article· en· W2032983009 on OpenAlexaff
Chitral J. Angammana, Shesha Jayaram

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsElectrospinningElectric fieldMaterials scienceJet (fluid)ElectrohydrodynamicsVoltageElectrodeComposite materialProcess (computing)Work (physics)PolymerNanotechnologyMechanicsMechanical engineeringElectrical engineeringComputer sciencePhysicsEngineering

Abstract

fetched live from OpenAlex

Electrospinning is an easy and inexpensive process that produces continuous nanofibres through an electrically charged jet of polymer solution consisting of sufficiently long chain molecules. As reported in the literature, the entire electrospinning process is governed by the external electric field caused by the applied voltage between the electrodes and the induced electric field caused by free and induced charges on the fluid surface. Therefore, the electric field is the most critical parameter in electrospinning. In the present work, a comprehensive analysis was carried out to investigate the effects of external and induced electric fields on the electrospinning process which include the Taylor cone formation, the straight jet portion, and the unstable or whipping jet region. It was observed that the all regions are highly influenced by the applied and induced electric fields which result a considerable variation in the morphology of the nanofibres.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.009
GPT teacher head0.260
Teacher spread0.251 · 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 designSimulation or modeling
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

Citations3
Published2010
Admission routes1
Has abstractyes

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