MétaCan
Menu
Back to cohort
Record W27384442 · doi:10.1021/acsami.6b03261

Kautz Gyula Faculty of Economics - Welcome

2016· article· en· W27384442 on OpenAlexfundno aff
welcome

Bibliographic record

VenueACS Applied Materials & Interfaces · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicHungarian Social, Economic and Educational Studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEconomics

Abstract

fetched live from OpenAlex

Imidazolium cations derived from ionic liquids were demonstrated as effective linker molecules for the layer-by-layer (LbL) deposition of polyoxometalates (POMs) to increase the charge storage of multi-walled carbon nanotube (MWCNT) electrodes. MWCNTs modified with GeMo12O40(4-) (GeMo12) via an imidazolium cation linker demonstrated highly reversible redox reactions and a capacitance of 84 F cm(-3), close to 4 times larger than bare CNT. Compared to CNT-GeMo12 composites fabricated with a conventional polyelectrolyte linker poly(diallyldimethylammonium chloride), (PDDA), the imidazolium cations resulted in lower POM loading, but higher conductivity and in turn superior performance at fast charge-discharge conditions. A polymerized imidazolium linker (PIL) was also synthesized based on the ethyl-vinyl-imidazolium monomer. CNT-GeMo12 composites fabricated with this PIL achieved high POM loading comparable to PDDA, while still maintaining the good conductivity and high rate capabilities shown by the monomer imidazolium units. The high conductivity imparted by the PIL is especially valuable for the fabrication of multilayer POM composites. Dual-layer GeMo12 O40(4-)-SiMo12O40(4-) (GeMo12-SiMo12) electrodes built with this PIL demonstrated a combined contribution of the individual POMs resulting in a capacitance of 191 F cm(-3), over nine times larger than bare MWCNT. The PIL dual layer composites also maintained 72% of this capacitance at a fast rate of 2 V s(-1), compared to just over 50% retention for similar electrodes fabricated with PDDA.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.633
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.042
GPT teacher head0.301
Teacher spread0.259 · 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
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

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueACS Applied Materials & InterfacesSame topicHungarian Social, Economic and Educational StudiesFrench-language works237,207