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Record W4411322514 · doi:10.1002/mame.202500129

Preparation and Characterization of Biobased Polyamide 36,10 Elastomer and Its Foam

2025· article· en· W4411322514 on OpenAlexfundno aff
Lauren Harley, Zahra Rahmatpanah, Biqiong Chen

Bibliographic record

VenueMacromolecular Materials and Engineering · 2025
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsnot available
FundersEngineering and Physical Sciences Research CouncilQueen's UniversityQueen's University Belfast
KeywordsMaterials sciencePolyamideCharacterization (materials science)ElastomerPolymer scienceComposite materialThermoplastic elastomerPolymerCopolymerNanotechnology

Abstract

fetched live from OpenAlex

ABSTRACT Biobased recyclable elastomers are interesting sustainable alternatives to existing fossil fuel‐based and/or non‐recyclable elastomers in diverse applications. Herein, a novel biobased thermoplastic elastomer, polyamide 36,10 (PA36,10), is synthesized by one‐pot condensation polymerization without the use of harmful chemicals or solvents. Its chemical structure and molecular weights are characterized using Fourier transform infrared spectroscopy, nuclear magnetic resonance, and gel permeation chromatography. The glass transition temperature and melting temperature of the PA36,10, determined from differential scanning calorimetry, are −4 and 95 °C, respectively. The tensile strength and elongation at break are 16.80 ± 0.18 MPa and 1636 ± 108%, with Shore A and Shore D hardnesses of 97 and 47, as well as relatively good resilience. PA36,10 is foamed by extrusion using a 3 wt.% common blowing agent, ammonium bicarbonate. The resulting foam shows a bulk density of 0.67 ± 0.16 g.cm −3 , with a compressive yield strength of 5.61 ± 0.71 MPa. The new biobased recyclable PA36,10 may find various potential applications in the elastomers industry.

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 score0.004
Threshold uncertainty score0.432

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 head0.006
GPT teacher head0.204
Teacher spread0.198 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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