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Record W4414302562 · doi:10.1016/j.jece.2025.119283

Review on electrospinning of recycled polymer-derived fibers: A road towards sustainability, production and applications

2025· article· en· W4414302562 on OpenAlexafffund
Haleh Naeim, Faezeh Mahdavian, Denis Rodrigue

Bibliographic record

VenueJournal of environmental chemical engineering · 2025
Typearticle
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsUniversité Laval
FundersConsortium de Recherche et d’innovation en Aérospatiale au Québec
KeywordsElectrospinningProduction (economics)Process (computing)Nanofiber

Abstract

fetched live from OpenAlex

In recent decades, the substantial growth in the production of non-biodegradable plastics led to a striking increase in environmental pollution. Conventional methods to manage these wastes, such as landfilling, incineration or physical recycling, are in many cases not only inefficient, but also costly and environmentally damaging. In these cases, the need for innovative and sustainable methods to reduce and reuse plastics waste is mandatory. One of the new and efficient approaches is the use of electrospinning and similar technology to directly convert plastics waste into thin fibers as an upcycling method. This process allows the production of micro- and nano-scale fibers from recycled polymers. These fibers can then be used in various applications, such as filtration, medicine, packaging and advanced engineering materials and composites (as reinforcements). This is related to their interesting properties, such as high contact surface area, tunable porosity and good strength depending on the original polymer. In this review, potential applications for this technology are presented in using polymer wastes and to describe its role as a sustainable solution in reducing the negative impacts of plastics on the environment. The scientific basis and functional advantages of this method are described first and experimental studies conducted in the field of electrospinning of recycled polymers are reviewed next. Finally, some conclusions are reported with openings for future developments.

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 score0.084
Threshold uncertainty score0.453

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.003
GPT teacher head0.230
Teacher spread0.227 · 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

Citations13
Published2025
Admission routes2
Has abstractyes

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