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Record W3194472171 · doi:10.1088/1361-665x/ac1b3b

Enhancing shape memory properties of multi-layered and multi-material polymer composites in 4D printing

2021· article· en· W3194472171 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSmart Materials and Structures · 2021
Typearticle
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsComposite materialMaterials scienceShape-memory polymerPolymerShape-memory alloy

Abstract

fetched live from OpenAlex

Abstract The shape memory behavior of smart materials is widely used for stimulation or shape-shifting purposes. Shape memory polymers (SMPs) can shape and force recoveries accompanied by attractive attributes such as biocompatibility, biodegradability, and universality. In this paper, a thermoplastic elastomer (TPE) is used as a complementary material for 4D printed polylactic acid (PLA) structures to enhance their shape and force recovery properties and lower the stimulation temperature for more practical implementations. Two approaches are followed to provide SMP composites (SMPCs): multi-layered and multi-material lattices. In multi-layered lattices, specimens are comprised of separate layers and different ratios of SMP and TPE materials. For comparison, PLA-TPE filaments with the same ratios of multi-layered lattices are produced and used to fabricate multi-material lattices. Dynamic mechanical thermal analysis tests showed a reduction in the glass transition temperature of the manufactured PLA-TPE filament. X-ray diffraction test was conducted to prove that the crystallinity of the developed PLA-TPE material increases which explains the better shape memory effect in the multi-material specimens. Phase separation occurred in low ratios of TPE in PLA, discernible in field emission scanning electron microscope (FESEM) images, resultting in low quality in one of the developed PLA-TPE filaments. FESEM images also showed proper miscibility of TPE in PLA in higher ratios. Thermomechanical tests were done on printed specimens to examine and compare the shape and force recovery of the produced SMPCs. While the shape recovery of multi-material samples was not as good as multi-layered samples, both approaches have better shape recovery results than the PLA sample. Due to a lower glass transition temperature in multi-material lattices, their shape recovery process started at lower temperatures widening their potential practical applications. Force recovery of multi-material samples revealed a significant improvement which was due to more oriented crystalline polymer structures.

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.

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 score0.009
Threshold uncertainty score0.845

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.020
GPT teacher head0.238
Teacher spread0.218 · 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