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Record W2126540076 · doi:10.1002/app.27098

Nonfouling biomaterials based on polyethylene oxide‐containing amphiphilic triblock copolymers as surface modifying additives: Synthesis and characterization of copolymers and surface properties of copolymer–polyurethane blends

2008· article· en· W2126540076 on OpenAlexaff
J. S. Tan, John L. Brash

Bibliographic record

VenueJournal of Applied Polymer Science · 2008
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Surface Interaction Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsCopolymerMaterials sciencePolyurethanePolymer chemistryAmphiphilePolyethylenePolymerChemical engineeringComposite material

Abstract

fetched live from OpenAlex

Abstract The objective of this work is to develop nonfouling biomaterials by blending polyethylene oxide (PEO)‐containing block copolymers with a polyurethane (PU) matrix; it is expected that the PEO component will migrate to the tissue‐material interface. Three amphiphilic triblock copolymers, PEO‐PU‐PEO, in which the PEO MW was 550 (copolymer 1), 2000 (copolymer 2), and 5000 (copolymer 3), respectively, were synthesized. XPS data showed that the polymer/vacuum interfaces of copolymers 2 and 3 were enriched in the PU block, whereas that of copolymer 1 was enriched in the PEO block. In contact with water, the PEO blocks for all three copolymers migrated to the surface as indicated by water contact angles. Blends of the copolymers with a segmented polyurethane were investigated. Surface enrichment of the copolymers occurred and increased over time up to a limit; the degree of enrichment was dependent on PEO block size and copolymer content. At copolymer content <10%, enrichment decreased with increasing PEO block size. For the copolymer 2 and copolymer 3 blends, enrichment increased with increasing copolymer content; at 20% copolymer the surfaces consisted essentially of pure copolymer. For the copolymer 1 blends, the surface was completely covered by copolymer at content ≥ 1%. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
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 score0.004
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0000.001
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 head0.024
GPT teacher head0.249
Teacher spread0.225 · 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

Citations30
Published2008
Admission routes1
Has abstractyes

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