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Record W2064229711 · doi:10.1117/12.715443

Effects of density and cell morphologies on the shape memory effect of a porous shape memory polymer

2007· article· en· W2064229711 on OpenAlexaff
Steven Simkevitz, Hani E. Naguib

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2007
Typearticle
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials sciencePorosityShape-memory polymerComposite materialPolymerActuatorSaturation (graph theory)Foaming agentPorous mediumComputer science

Abstract

fetched live from OpenAlex

This paper investigates the effects of different densities and cellular morphologies on the shape memory effect (SME) of a porous shape memory polymer (SMP). The batch foaming processing technique was employed to obtain the desired foamed cellular structures. A study was conducted where the variable of saturation pressure was varied in order to obtain a reduction in relative density while the variables of saturation time, foaming temperature and foaming time were kept constant. The advantage of foaming the SMP is to reduce the weight of the material while still retaining its mechanical and thermomechanical characteristics. One particular point of interest is to understand how a change in density affects the SME. It is also of importance to determine how the SME is influenced by different amounts of strain and by the cellular morphology of the SMP. The objective is to modify the SMP to have the greatest SME while maintaining weight savings. Focusing on the SME, the area of greatest significance is the time response of the SMP. This approach is vital as it dictates the possibility of using a SMP as an effective actuator.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.023
Threshold uncertainty score0.890

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.007
GPT teacher head0.215
Teacher spread0.207 · 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

Citations1
Published2007
Admission routes1
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicPolymer composites and self-healingFrench-language works237,207