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Record W2616839015 · doi:10.1002/polb.24370

Room temperature deformable shape memory composite with fine‐tuned crystallization induced via nanoclay particles

2017· article· en· W2616839015 on OpenAlexaff
Yu‐Chen Sun, Shenyang Cai, Jie Ren, Hani E. Naguib

Bibliographic record

VenueJournal of Polymer Science Part B Polymer Physics · 2017
Typearticle
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsUniversity of TorontoUniversity of New Brunswick
Fundersnot available
KeywordsMaterials scienceComposite materialMontmorilloniteCrystallinityShape-memory polymerShape-memory alloyThermoplastic polyurethaneComposite numberPolylactic acidElastomerPolymerThermoplastic elastomerCompatibility (geochemistry)CrystallizationNanocompositeChemical engineeringCopolymer

Abstract

fetched live from OpenAlex

ABSTRACT It is known that particular types of semi‐crystalline/elastomer polymer blends exhibit shape memory effects (SME) due to the dispersion of two immiscible phases. In this study, the crystal structure of polylactic acid (PLA)/ thermoplastic polyurethane (TPU) based shape memory polymer (SMP) is altered by incorporating small amounts of montmorillonite (MMT) nanoclay. The results indicate the incorporation of MMT can improve the compatibility of the two different polymers. Moreover, the presence of MMT affects the total crystallinity of the SMP and improves mechanical properties. Lastly, uniaxial stretching deformation can be applied to the SMP at room temperature conditions while maintaining its shape memory properties. With 1 wt % MMT particles, the recovery ratio (Rr) was nearly 95%, which indicated a strong recovery effect. The shape‐fixing ratio (Rf) remained above 95% for all composites due to plastic deformation applied at room temperature. © 2017 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2017, 55, 1197–1206

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 score0.001
Threshold uncertainty score0.003

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)0.0010.000

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 head0.017
GPT teacher head0.253
Teacher spread0.236 · 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

Citations29
Published2017
Admission routes1
Has abstractyes

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