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Record W4388418008 · doi:10.1021/bk-2023-1454.ch003

Polyurethanes for Shape Memory Foams

2023· book-chapter· en· W4388418008 on OpenAlexaff
Mohammad Nourany, Majid Mollavali, Narges Mohammad Mehdipour

Bibliographic record

VenueACS symposium series · 2023
Typebook-chapter
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPolyurethaneMicrostructureMaterials scienceShape-memory alloyNanotechnologyCell structureComposite materialBiological system

Abstract

fetched live from OpenAlex

Shape memory polyurethane (SMPU) foams with cellular and porous structure are considered as promising multi-functional polymeric structures that have been used for a wide-spectrum of applications and industries. Numerous studies have focused on the chemistry, formulation and production processes of polyurethane foams (PUFs) and their microstructure-mechanical performance correlation. Despite the extensive early study on the microstructure and the mechanisms involved in the evolution of the PUF cells and their structures, little study and investigation have been made on their shape memory performance (SMP). In this chapter, the general chemistry of PUFs will be briefly discussed, and since the cell opening mechanisms plays a central role on the final PUF structure, application and tuning its mechanical performance, it will be covered in detail. The microstructural evolution of PUFs, the impact of nanoparticles on cell structure and mechanical behavior will also be discussed in detail. Finally, the SMP of polyurethanes (PUs) in general, PUFs and its future prospects will be studied and discussed in detail.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.334
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
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)0.0000.001

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 head0.024
GPT teacher head0.238
Teacher spread0.215 · 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.

Study designBench or experimental
Domainnot available
GenreOther

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

Citations4
Published2023
Admission routes1
Has abstractyes

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