MétaCan
Menu
Back to cohort
Record W2132894115 · doi:10.1002/pola.27216

Tuning amphiphilicity/temperature‐induced self‐assembly and in‐situ disulfide crosslinking of reduction‐responsive block copolymers

2014· article· en· W2132894115 on OpenAlexafffund
Nicky Chan, Nathan Yee, So Young An, Jung Kwon Oh

Bibliographic record

VenueJournal of Polymer Science Part A Polymer Chemistry · 2014
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsCopolymerAmphiphilePolymer chemistryMethacrylateEthylene glycolEthylene oxideChemistryDisulfide bondMaterials scienceOrganic chemistryPolymer

Abstract

fetched live from OpenAlex

ABSTRACT New poly(ethylene oxide)‐based block copolymers (ssBCs) with a random copolymer block consisting of a reduction‐responsive disulfide‐labeled methacrylate (HMssEt) and a thermoresponsive di(ethylene glycol)‐containing methacrylate (MEO 2 MA) units were synthesized. The ratio of HMssEt/MEO 2 MA units in the random P(MEO 2 MA ‐co‐ HMssEt) copolymer block enables the characteristics of well‐defined ssBCs to be amphiphilic or thermoresponsive and double hydrophilic. Their amphiphilicity or temperature‐induced self‐assembly results in nanoaggregates with hydrophobic cores having different densities of pendant disulfide linkages. The effect of disulfide crosslinking density on morphological variation of disulfide‐crosslinked nanogels is investigated. In response to reductive reactions, the partial cleavage of pendant disulfide linkages in the hydrophobic cores converts the physically associated aggregates to disulfide‐crosslinked nanogels. The occurrence of in‐situ disulfide crosslinks provides colloidal stability upon dilution. © 2014 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2014 , 52 , 2057–2067

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 score0.004
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
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.245
Teacher spread0.237 · 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

Citations10
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Polymer Science Part A Polymer ChemistrySame topicAdvanced Polymer Synthesis and CharacterizationFrench-language works237,207