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Record W2279807588 · doi:10.1002/macp.201500530

Induced Microphase Separation in Hybrid Composite Polymer Electrolytes Based on Poly(acrylonitrile‐<i>r</i>‐butadienes) and Ionic Liquids

2016· article· en· W2279807588 on OpenAlexaff
Michael Wirey, Marcus Hunt, Tyler Blensdorf, Barry Stein, Ulrike Werner‐Zwanziger, Margaret A. Hanson, Waleed E. Mahmoud, Ahmed A. Al‐Ghamdi, John P. Carini, Lyudmila M. Bronstein

Bibliographic record

VenueMacromolecular Chemistry and Physics · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsTrifluoromethanesulfonateAcrylonitrileIonic liquidIonic conductivitySubstituentElectrolytePolymer chemistryMaterials sciencePhase (matter)PolymerComposite numberConductivityIonic bondingChemical engineeringCopolymerChemistryIonPhysical chemistryOrganic chemistryComposite materialElectrode

Abstract

fetched live from OpenAlex

Novel hybrid, composite polymer electrolytes (HCPEs) based on poly(acrylonitrile‐r‐butadiene) (PAN‐r‐PB), CN‐modified silica nanoparticles (CN‐MSNs), Li triflate, and ionic liquids (ILs) are synthesized. Using a combination of methods, it is demonstrated that these materials segregate into PAN‐rich and PB‐rich phases, the behavior of which changes depending on the IL type. The incorporation of ILs containing hexyl and octyl substituents at the imidazolium rings leads to a higher mobility of the PB‐rich phase and a decrease of the density of the neighboring PAN‐rich phase, allowing an improvement of the Li ion conductivity. However, with an increase of the substituent length from decyl to dodecyl, ordering of the hydrophobic tails in the PB‐rich phase leads to both stiffening of the latter and corresponding ordering of the ionic pairs of ILs, resulting in a decreased conductivity. The results of this work are broadly applicable for controlling the structure and properties of polymeric materials exhibiting microphase segregation. image

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.004
GPT teacher head0.204
Teacher spread0.200 · 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 source (direct Gemma or distilled Codex), 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

Citations57
Published2016
Admission routes1
Has abstractyes

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