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Record W4381742905 · doi:10.1021/acs.jpcc.3c01602

Ionic Liquid–Graphene Interface: Effect of Anions on the Fermi Level

2023· article· en· W4381742905 on OpenAlexaff
Gangamallaiah Velpula, Jian Xiang Lian, David Cornil, Roberto Lazzaroni, Kunal S. Mali, Steven De Feyter

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2023
Typearticle
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsUniversity of Calgary
FundersFonds Wetenschappelijk OnderzoekVlaamse regeringFonds De La Recherche Scientifique - FNRSKU LeuvenWaalse Gewest
KeywordsGrapheneIonic liquidElectrolyteRaman spectroscopyMaterials scienceElectrochemistryDopingChemical physicsElectrodeFermi levelIonIonic bondingGraphene nanoribbonsNanotechnologyChemical engineeringChemistryPhysical chemistryOptoelectronicsCatalysisOrganic chemistry

Abstract

fetched live from OpenAlex

Since energy conversion and storage processes take place at the electrolyte–electrode interface, it is important to develop experimental and theoretical procedures to understand the interfacial nanostructure in graphene-based electrochemical storage devices where ionic liquids (ILs) are used as electrolytes. In this contribution, the impact of the anions of imidazolium-based ILs on the IL–graphene interface as well as on the electronic structure of graphene is investigated. Raman spectroscopy unveils that 1-butyl-3-methylimidazolium ILs having smaller anions induce n-type doping, while ILs with larger anions have a negligible effect on the doping. Molecular modeling simulations reveal that changes in the electrostatic potential at the IL–graphene interface are responsible for the n-type doping.

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 score0.003
Threshold uncertainty score0.295

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 science0.0010.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.280
Teacher spread0.264 · 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

Citations10
Published2023
Admission routes1
Has abstractyes

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