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Record W2898127216 · doi:10.1002/gch2.201800023

Ionic Liquids as Environmentally Benign Electrolytes for High‐Performance Supercapacitors

2018· review· en· W2898127216 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

VenueGlobal Challenges · 2018
Typereview
Languageen
FieldMaterials Science
TopicSupercapacitor Materials and Fabrication
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsSupercapacitorElectrolyteIonic liquidCapacitorMaterials scienceElectrochemistryEnergy storageThermal stabilityIonic conductivityPower densityNanotechnologyVoltageElectrical engineeringChemical engineeringPower (physics)ChemistryElectrodeEngineering

Abstract

fetched live from OpenAlex

Electrochemical capacitors (ECs) are a vital class of electrical energy storage (EES) devices that display the capacity of rapid charging and provide high power density. In the current era, interest in using ionic liquids (ILs) in high-performance EES devices has grown exponentially, as this novel versatile electrolyte media is associated with high thermal stability, excellent ionic conductivity, and the capability to withstand high voltages without undergoing decomposition. ILs are therefore potentially useful materials for improving the energy/power performances of ECs without compromising on safety, cyclic stability, and power density. The current review article underscores the importance of ILs as sustainable and high-performance electrolytes for electrochemical capacitors.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.044
GPT teacher head0.290
Teacher spread0.246 · 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