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Record W4391300814 · doi:10.2514/6.2024-2149

3D Printing of TPU-PLA Shape Memory Polymers and Nanocomposites for Deployable Structures

2024· article· en· W4391300814 on OpenAlexaff
Michael B. Jakubinek, Yu Sun, Michael Barnes, Kyra McLellan, Hani E. Naguib

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsUniversity of TorontoNational Research Council Canada
Fundersnot available
KeywordsShape-memory polymerNanocomposite3D printingMaterials sciencePolymerComposite materialNanotechnology

Abstract

fetched live from OpenAlex

Shape memory polymer blends were produced based on thermoplastic polyurethane (TPU) with poly(lactic acid) (PLA), including with the addition of single-walled carbon nanotubes or MXene nanoparticles as a reinforcing filler, and extruded to produce filaments for 3D printing by fused deposition modeling. A series of simple structures were printed and evaluated in terms of their shape memory effect, displaying large deformation and nearly complete shape recovery. The filaments printed similarly to commercial flexible filaments, although improvements in the filler integration and consistency of the filament diameter are needed to reduce print failures in larger prints with more flexible blends as well as to improve print quality. Addition of MXene or SWCNTs improved the stiffness and strength of the material. This improvement was associated with improved shape memory effect and increased recovery force, which are important for the use of SMPCs for actuation. The 3D/4D printed structures show large scale deformation capability, such as would be required for a deployable structure.

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 score0.030
Threshold uncertainty score0.436

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 head0.011
GPT teacher head0.250
Teacher spread0.239 · 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
Published2024
Admission routes1
Has abstractyes

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