MétaCan
Menu
Back to cohort

Enhancing the Properties of Sodium Alginate with a Glycerol–Silicate Plasticizer

2025· article· en· W4408169845 on OpenAlexafffund
Anthony Fasulo, Corradina Towie, Lucie Mouchiroud, Hamza Malik, Daniel A. Foucher, Guerino Sacripante

Bibliographic record

VenuePolysaccharides · 2025
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPlasticizerSodium alginateGlycerolSilicateSodium silicateChemical engineeringChemistrySodiumMaterials scienceOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

The impact of a glycerol–silicate (GS) plasticizer on the mechanical, thermal and hydrophobic properties pertaining to sodium alginate (NaAlg) and calcium alginate (CaAlg) films were investigated. Spectroscopic and physio-chemical analysis were conducted to evaluate the effects of the GS incorporation. The results determine that both NaAlg and CaAlg films exhibited poor mechanical properties which only improved by increasing the GS loading (up to 25 wt%), after which it declined. CaAlg exhibited the highest tensile strength after 25 wt% GS loading was incorporated. The elongation at break varied, with NaAlg films showing a ~10-fold increase, while the CaAlg films remained relatively unchanged. Thermal gravimetric analysis (TGA) revealed that GS reduced the onset decomposition temperature of NaAlg films, whereas CaAlg films maintained a greater onset decomposition temperature. The advancing contact angle measurements indicated a nearly linear decrease (from 54° to 39°) in hydrophobicity for the NaAlg films while the hydrophobicity for CaAlg films initially increased from 65° to 74°, and then became more hydrophilic with greater GS loading. These findings highlight the potential of GS plasticization to enhance and tailor alginate film properties, providing insights into the development of sustainable bioplastics with improved mechanical properties.

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 score0.018
Threshold uncertainty score0.374

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 head0.017
GPT teacher head0.215
Teacher spread0.199 · 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

Citations12
Published2025
Admission routes2
Has abstractyes

Explore more

Same venuePolysaccharidesSame topicbiodegradable polymer synthesis and propertiesFrench-language works237,207