MétaCan
Menu
Back to cohort
Record W1964811855 · doi:10.1007/s10853-014-8481-z

Electrospun green fibres from lignin and chitosan: a novel polycomplexation process for the production of lignin-based fibres

2014· article· en· W1964811855 on OpenAlexafffund
Makoto Schreiber, Singaravelu Vivekanandhan, Peter Cooke, Amar K. Mohanty, Manjusri Misra

Bibliographic record

VenueJournal of Materials Science · 2014
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPolyelectrolyteLigninChitosanMaterials scienceBiopolymerChemical engineeringElectrospinningFourier transform infrared spectroscopyCationic polymerizationSpinningCellulosePolymerPolymer chemistryComposite materialOrganic chemistryChemistry

Abstract

fetched live from OpenAlex

Novel lignin-chitosan polyelectrolyte fibres were produced through a reactive electrospinning process. Polyelectrolyte formation between the anionic lignin and cationic chitosan was controlled through the pH of the solution. Through manipulating the polyelectrolyte complex formation, fibres could be effectively produced from two biopolymers, which are normally very difficult to electrospin on their own. Though minimal amounts of the petroleum-derived polyethylene oxide were introduced into the solution to enhance the spinnability of the polyelectrolyte solution, it could be easily removed from the fibres post spinning by washing with water. Thus, pure biopolymer fibres could be produced. The optimum composition of lignin to chitosan was identified through SEM, FTIR and TGA analysis of the electrospun fibres. Fluorescence spectra of the electrospun fibres reveal the homogeneous distribution of lignin and chitosan components throughout the fibre network.

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)0.000
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 score0.003
Threshold uncertainty score0.225

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.012
GPT teacher head0.234
Teacher spread0.222 · 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

Citations62
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Materials ScienceSame topicLignin and Wood ChemistryFrench-language works237,207