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Record W4391386777 · doi:10.3390/ijms25031720

Ionic Liquids as Designed, Multi-Functional Plasticizers for Biodegradable Polymeric Materials: A Mini-Review

2024· article· en· W4391386777 on OpenAlexaff
Julia L. Shamshina, Paula Bertón

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2024
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPlasticizerBiopolymerMaterials scienceIonic liquidUltimate tensile strengthCellulosePolymerEnvironmentally friendlyPolymer scienceNanotechnologyChemical engineeringComposite materialChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Measures to endorse the adoption of eco-friendly biodegradable plastics as a response to the scale of plastic pollution has created a demand for innovative products from materials from Nature. Ionic liquids (ILs) have the ability to disrupt the hydrogen bonding network of biopolymers, increase the mobility of biopolymer chains, reduce friction, and produce materials with various morphologies and mechanical properties. Due to these qualities, ILs are considered ideal for plasticizing biopolymers, enabling them to meet a wide range of specifications for biopolymeric materials. This mini-review discusses the effect of different IL-plasticizers on the processing, tensile strength, and elasticity of materials made from various biopolymers (e.g., starch, chitosan, alginate, cellulose), and specifically covers IL-plasticized packaging materials and materials for biomedical and electrochemical applications. Furthermore, challenges (cost, scale, and eco-friendliness) and future research directions in IL-based plasticizers for biopolymers are discussed.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.714
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.043
GPT teacher head0.304
Teacher spread0.261 · 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.

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

Citations38
Published2024
Admission routes1
Has abstractyes

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