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Record W2054751332 · doi:10.1680/gmat.13.00014

CO<sub>2</sub>-triggered fast micellization of a liposoluble star copolymer in water

2014· article· en· W2054751332 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGreen Materials · 2014
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsMcMaster University
Fundersnot available
KeywordsCopolymerMicelleMethacrylateMaterials sciencePolymer chemistryAcrylateAtom-transfer radical-polymerizationStar (game theory)Ethyl acrylatePolymerizationChemical engineeringPolymerChemistryOrganic chemistryAqueous solutionComposite material

Abstract

fetched live from OpenAlex

This study reports a green and efficient strategy using CO 2 to trigger fast micellization of a liposoluble star copolymer in water. The star copolymers consisting of a hyperbranched polyethylene (HBPE) core and multiple poly(2-(dimethylamino)ethyl methacrylate) (PDMAEMA) arms were synthesized through a sequential Pd-catalyzed chain walking copolymerization of ethylene and 2-(2-bromoisobutyryloxy)ethyl acrylate followed by an atom-transfer radical polymerization of DMAEMA. The star copolymers with large HBPE cores and low PDMAEMA arm numbers or short arms can be easily dissolved in aliphatic hydrocarbon solvents. The copolymers could be quickly dispersed in water and form micelles after CO 2 bubbling. A N 2 -mediated switching process following the CO 2 treatment is shown to reverse the micelles back to their neutral state without causing additional micelle aggregation. The CO 2 switchability of PDMAEMA prompted fast micellization of such liposoluble star copolymers. This article contains supporting information that will be made available online once the issue is published.

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.

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 categoriesInsufficient payload (model declined to judge)
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 score0.003
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.000

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 head0.007
GPT teacher head0.210
Teacher spread0.202 · 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