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Record W2957603603 · doi:10.1002/adhm.201900245

One‐Pot Synthesis of Unsaturated Polyester Bioelastomer with Controllable Material Curing for Microscale Designs

2019· article· en· W2957603603 on OpenAlexafffund
Locke Davenport Huyer, Dawn Bannerman, Yufeng Wang, Houman Savoji, Ericka J. Knee‐Walden, Amanda Brissenden, Bess Yee, Mohammad Shoaib, Erin R. Bobicki, Brian G. Amsden, Milica Radisic

Bibliographic record

VenueAdvanced Healthcare Materials · 2019
Typearticle
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsUniversity of TorontoQueen's UniversityUniversity Health Network
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchNational Institutes of HealthNational Science Foundation
KeywordsElastomerMaterials scienceMicroscale chemistryPolyesterCuring (chemistry)PolymerMonomerComposite materialChemical engineeringNanotechnology

Abstract

fetched live from OpenAlex

Synthetic polyester elastomeric constructs have become increasingly important for a range of healthcare applications, due to tunable soft elastic properties that mimic those of human tissues. A number of these constructs require intricate mechanical design to achieve a tunable material with controllable curing. Here, the synthesis and characterization of poly(itaconate-co-citrate-co-octanediol) (PICO) is presented, which exhibits tunable formation of elastomeric networks through radical crosslinking of itaconate in the polymer backbone of viscous polyester gels. Through variation of reaction times and monomer molar composition, materials with modulation of a wide range of elasticity (36-1476 kPa) are generated, indicating the tunability of materials to specific elastomeric constructs. This correlated with measured rapid and controllable gelation times. As a proof of principle, scaffold support for cardiac tissue patches is developed, which presents visible tissue organization and viability with appropriate elastomeric support from PICO materials. These formulations present potential application in a range of healthcare applications with requirement for elastomeric support with controllable, rapid gelation under mild conditions.

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)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.014
GPT teacher head0.274
Teacher spread0.259 · 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
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

Citations43
Published2019
Admission routes2
Has abstractyes

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