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Record W4409002075 · doi:10.3390/nano15070525

Hyperbranched Polyethylene Ionomers Containing Quaternary Ammonium Ions and Their Functionalization of Nanomaterials

2025· review· en· W4409002075 on OpenAlexaff
Zhibin Ye, Jalal Rahmatinejad, Bahareh Raisi, Peiyao Dai

Bibliographic record

VenueNanomaterials · 2025
Typereview
Languageen
FieldMaterials Science
TopicDendrimers and Hyperbranched Polymers
Canadian institutionsConcordia University
Fundersnot available
KeywordsSurface modificationPolyethyleneNanomaterialsMaterials sciencePolymerPolymerizationIonic bondingPolymer chemistryChemical engineeringChemistryOrganic chemistryNanotechnologyIon

Abstract

fetched live from OpenAlex

Ionomers containing a small number of ionic side groups are a unique class of polymers with some valuable properties and distinct applications. To date, commercially important ionomers are exclusively anionomers that contain covalently bonded anions and are synthesized commonly by radical polymerization. The catalytic synthesis of polyethylene-based cationomers is challenging, while it is attractive due to the low cost of ethylene stocks and less stringent polymerization conditions, along with their desirable properties and broadened scope of commercial applications. Advances in catalyst technology-specifically, Pd-diimine catalysts-have recently enabled the synthesis of a class of hyperbranched polyethylene cationomers that are designed to contain quaternary ammonium cations. With their unique hydrophobic hyperbranched polyethylene backbone, this class of ionomers enables the successful functionalization of negatively surface-charged nanomaterials, thus improving the processing and application of the latter. This review summarizes the developments of this class of ionomers, including their synthesis, properties, and functionalization of various nanomaterials.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.625
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.028
GPT teacher head0.291
Teacher spread0.263 · 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
GenreReview

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

Citations0
Published2025
Admission routes1
Has abstractyes

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