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Record W7117773734 · doi:10.3390/polym18010130

The Stiffness for Viscous Deformation in the Interlamellar Amorphous Region of Polyethylene

2025· article· en· W7117773734 on OpenAlexafffund
P.-Y. Ben Jar, Na Tan, Salman Obaidoon, Arash Alizadeh, João B. P. Soares

Bibliographic record

VenuePolymers · 2025
Typearticle
Languageen
FieldMaterials Science
TopicPolymer crystallization and properties
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Alberta
KeywordsStiffnessDeformation (meteorology)Amorphous solidWork (physics)Relaxation (psychology)Drop (telecommunication)

Abstract

fetched live from OpenAlex

A spring-dashpot model, consisting of a spring branch and two Maxwell (named long- and short-term) branches, was used to simulate stress drop during the relaxation stages of multi-relaxation (MR) tests. This work shows that the stress drop at relaxation in a deformation range around the peak stress could be closely simulated without changing the parameter values for the short-term branch. This possibility was confirmed using three ethylene/1-hexene copolymers and one ethylene homo-polymer, among which the main differences are mass density and short-chain branch (SCB) content. The work examined the influence of SCB content and mass density on the stiffness of the two Maxwell branches, and the results showed that, unlike the long-term branch counterpart, stiffness of the short-term branch is not a monotonic function of the SCB content or the mass density. This led to a discussion on the possible relationship between the stiffness of the two Maxwell branches and the deformation resistance of the amorphous phase at different locations of the microstructure, i.e., in the interlamellar region and as part of the network structure. The paper concludes that a combination of the MR test and the spring-dashpot model could provide information that is related to the stiffness in different parts of PE's amorphous phase, though further work is needed to verify this conclusion.

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 score0.188
Threshold uncertainty score0.167

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 head0.016
GPT teacher head0.256
Teacher spread0.240 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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