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Record W4411421752 · doi:10.3390/polym17121695

Electrospinning of Miscanthus x giganteus Organosolv Lignin in Dimethyl Sulfoxide (DMSO)

2025· article· en· W4411421752 on OpenAlexafffund
Roland Jacks Ekila, Tatjana Stevanovic, Denis Rodrigue

Bibliographic record

VenuePolymers · 2025
Typearticle
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsUniversité Laval
FundersConsortium de Recherche et d’innovation en Aérospatiale au QuébecUniversité Laval
KeywordsOrganosolvLigninElectrospinningMiscanthusMaterials scienceChemical engineeringNanofiberDimethyl sulfoxidePolymerChemistryOrganic chemistryComposite materialBioenergyBiofuel

Abstract

fetched live from OpenAlex

Electrospinning is a simple technique to produce fibers with small diameters. These fibers can be made from different polymers, but the focus is now on biobased materials. In this work, the lignin obtained from Miscanthus x giganteus, an herbaceous plant, was isolated by an Organosolv process leading to a high purity (90%), which is essential for its electrospinning. This lignin also had a carbon content of 72.2% with 24.8% oxygen and a low nitrogen content (1%). The isolated lignin was then solubilized in dimethyl sulfoxide (DMSO). Finally, an optimization step showed that a stable process was possible using a 62% lignin solution in DMSO with a needle-to-collector distance of 20 cm, a flow rate of 0.3 mL/h, a voltage of 25 kV, and a humidity of 35%. Nevertheless, lignin concentrations between 55 and 63% were studied to determine the effect of this parameter on the final fibers. A morphological analysis (SEM-EDX) enabled us to understand both the evolution of the diameter and the effect of dimethyl sulfoxide on the electrospun fibers. This study showed that electrospinning of the lignin obtained from Miscanthus x giganteus was possible, even without any additives.

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)0.000
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 score0.017
Threshold uncertainty score0.636

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.003
GPT teacher head0.252
Teacher spread0.249 · 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

Citations3
Published2025
Admission routes2
Has abstractyes

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