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Record W2497519892 · doi:10.1002/app.44172

Morphologies of electrospun fibers of lignin in poly(ethylene oxide)/N,N‐dimethylformamide

2016· article· en· W2497519892 on OpenAlexafffund
Samira Aslanzadeh, Behzad Ahvazi, Yaman Boluk, Cagri Ayranci

Bibliographic record

VenueJournal of Applied Polymer Science · 2016
Typearticle
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsNational Institute for NanotechnologyAlberta InnovatesUniversity of Alberta
FundersAlberta Innovates Bio SolutionsAlberta Innovates - Technology FuturesNational Institute for Nanotechnology
KeywordsEthylene oxideElectrospinningMaterials scienceNanofiberMorphology (biology)Polymer chemistryFiberChemical engineeringVolume fractionMolar mass distributionOxidePolymerComposite materialCopolymer

Abstract

fetched live from OpenAlex

ABSTRACT The effects of polyethylene oxide (PEO) molecular weight (Mv), and volume fraction ( ) on the morphology of electrospun sulfur free softwood lignin nanofibers were investigated. Small amounts of PEO were used during preparations of the solutions to aid the electrospinning process. It was found that tripling the PEO volume fraction resulted in a transition from semi‐dilute un‐entangled to semi‐dilute entangled solutions. Conversely, the solution remained in the semi‐dilute un‐entangled regime as the molecular weight was increased by five times. The effects of molecular weight and volume fraction of PEO both on entanglement density and fiber morphology were unified by scaling PEO viscosities as a function of . We investigated and discussed conditions that would produce smooth fibers and conditions that would produce fibers with beads. In the case of beads‐on‐a‐string formation, bead widths remained constant regardless of the molecular weight and concentration of PEO, but the bead length changed. Additionally, we observed a decrease in the diameter of the fibers and the dimension of beads (length and width of beads) with an increase in the electric field used for electrospinning. The aspect ratio of beads increased with increases to both the electric field and the PEO molecular weight or concentration. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133 , 44172.

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)0.002
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 score0.029
Threshold uncertainty score0.897

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.006
GPT teacher head0.244
Teacher spread0.237 · 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

Citations20
Published2016
Admission routes2
Has abstractyes

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