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Record W2333640861 · doi:10.1021/nn401357p

States Modulation in Graphene Nanoribbons through Metal Contacts

2013· article· en· W2333640861 on OpenAlexaff
Chloé Archambault, Alain Rochefort

Bibliographic record

VenueACS Nano · 2013
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsPolytechnique MontréalRegroupement Québécois sur les Matériaux de Pointe
Fundersnot available
KeywordsGraphene nanoribbonsGrapheneMaterials scienceChemisorptionCondensed matter physicsBand gapMetalChemical physicsDensity functional theoryElectrostaticsNanometreNanotechnologyAdsorptionOptoelectronicsChemistryComputational chemistryPhysics

Abstract

fetched live from OpenAlex

We are reporting the results of density functional calculations of the electronic structure of finite graphene nanoribbons adsorbed on Au, Pd, and Ti electrodes. While the interaction of nanoribbons with the Au contact is more characteristic of a physisorbed state, the adsorption of Pd and Ti involves much stronger state mixing as in chemisorption. Metal-induced gap states, which can potentially short-circuit the device, are clearly revealed for the first time, allowing us to evaluate their penetration length. The evanescence of MIGS is primarily governed by the band gap of the nanoribbon, and we can estimate an acceptable minimal length for an effective transport channel to a few nanometers. Different impacts of the presence of metal-induced gap states on the properties of graphene nanoribbons are discussed in terms of charge transfer and electrostatics.

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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.278
Teacher spread0.257 · 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

Citations22
Published2013
Admission routes1
Has abstractyes

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