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Record W1899041869 · doi:10.1002/mame.201400122

Characterization of Viscoelasticity and Self‐Healing Ability of VHB 4910

2014· article· en· W1899041869 on OpenAlexaff
Fan Fan, Jerzy A. Szpunar

Bibliographic record

VenueMacromolecular Materials and Engineering · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicHigh-pressure geophysics and materials
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsViscoelasticityMaterials scienceHydrogen bondFourier transform infrared spectroscopyComposite materialSelf-healingRaman spectroscopyCovalent bondUltimate tensile strengthShear modulusMoleculeChemical engineeringOptics

Abstract

fetched live from OpenAlex

The mechanisms responsible for the viscoelasticity and self‐healing ability of VHB 4910 are studied. The type of chemical bonds is confirmed using Fourier transform infrared and Raman spectroscopy. The tensile tests demonstrate that the material has viscoelastic behavior that depends on the deformation speed and changes in the hysteresis area with different tensile strains. The shear modulus of entangled networks increases with the deformation speed. This behavior confirms that the viscoelasticity is due to the dissociation and re‐association of non‐covalent bonding. The hydrogen bonding initiates the healing process and the diffusion of molecular chains strengthens the self‐healing ability.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.157
Teacher spread0.154 · 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 source (direct Gemma or distilled Codex), 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

Citations34
Published2014
Admission routes1
Has abstractyes

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