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Record W2903634476 · doi:10.1002/ijch.201800123

Photopolymerization of Ionic Liquids – A Mutually Beneficial Approach for Materials Fabrication

2018· article· en· W2903634476 on OpenAlexfundno aff
Ryan Guterman, Christene A. Smith

Bibliographic record

VenueIsrael Journal of Chemistry · 2018
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsnot available
FundersWestern University
KeywordsPhotopolymerIonic liquidPolymerizationFabricationChemistryMonomerElectrolyteSolventPolymerIonic bondingNanotechnologyChemical engineeringPolymer chemistryOrganic chemistryMaterials scienceIonPhysical chemistryElectrode

Abstract

fetched live from OpenAlex

Abstract Photopolymerization is a convenient fabrication technique with the power to control the polymerization in both time and space, be solvent free, and use simple equipment to initiate the polymerization reaction. These features are conditional on use of liquid monomers and crosslinkers that do not require solvent for processing. One class of compounds that provides these opportunities are ionic liquid (IL) monomers, which possess negligible vapour pressure and are free‐flowing liquids at room temperature. For these reasons, ILs and photopolymerization are complementary to each other towards the fabrication of electrolyte materials by circumventing the innate difficulty in processing PILs as melts. Instead, the electrolyte polymer is formed as a crosslinked material directly where it will be used. In this review, we outline recent work demonstrating the key benefits of this unlikely marriage, including formulation design, applications in coatings, membranes, and others.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.042
Threshold uncertainty score0.600

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)0.0000.000

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 head0.010
GPT teacher head0.245
Teacher spread0.234 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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