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Record W2889597049 · doi:10.1021/acs.iecr.8b02233

Fabrication of Novel Open-Cell Foams of Poly(ε-caprolactone)/Poly(lactic acid) Blends for Tissue-Engineering Scaffolds

2018· article· en· W2889597049 on OpenAlexaff
Zirui Lv, Na Zhao, Zeming Wu, Changwei Zhu, Qian Li

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2018
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsVale (Canada)
FundersChina Postdoctoral Science FoundationMinistry of Science and Technology of the People's Republic of ChinaNational Natural Science Foundation of China
KeywordsMaterials scienceUltimate tensile strengthCaprolactoneScaffoldTissue engineeringPlastics extrusionLactic acidComposite materialBiodegradable polymerPolyesterChemical engineeringPolymerPolymerizationBiomedical engineering

Abstract

fetched live from OpenAlex

Poly(ε-caprolactone)/poly(lactic acid) (PCL/PLA) blends are very promising materials with biodegradable characteristics and tailorable performance for many applications. In this study, PCL and PLA were compounded at various ratios using a co-rotating twin-screw extruder. The morphology showed that they were immiscible but were dispersed well in each other. Very interesting and peculiar open-cell structures were obtained through a batch-foaming process. Interconnected holes with flexible PCL fibrils were created by high tensile stress during cell expansion, which contributed to the rapid diffusion of CO2. No cells collapsed at high foam expansion under all foaming conditions. Moreover, a small-diameter tubular PCL/PLA foamed scaffold had a tensile toe region of approximately 40%, which indicated a potential application for vascular tissue engineering. The human umbilical vein endothelial cells cultured on the surfaces of PCL/PLA blend foams showed high viability and migration.

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 score0.029
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.132
GPT teacher head0.335
Teacher spread0.203 · 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

Citations30
Published2018
Admission routes1
Has abstractyes

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