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Record W4376505724 · doi:10.1002/pssr.202200302

Gap Opening in Graphene via Locally Introduced Electric Field

2023· article· en· W4376505724 on OpenAlexaff
Hamed Abbasian

Bibliographic record

Venuephysica status solidi (RRL) - Rapid Research Letters · 2023
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsGrapheneElectric fieldScanning tunneling microscopeFermi energyFermi levelMaterials scienceGatingBand gapCondensed matter physicsDipoleBilayer grapheneNanotechnologyOptoelectronicsPhysicsQuantum mechanics

Abstract

fetched live from OpenAlex

Utilizing first‐principle calculations, two systems of graphene/overlay are investigated. The overlays are made up of a self‐assembling molecular network (SAN) that introduces local electric fields in opposite directions on graphene. It is demonstrated that the patterned electric field via dipolar SAN, in addition to gating, can create a gap in graphene's band structure. Also, linearly dispersing bands of graphene are retained intact in a certain energy window in the vicinity of the Dirac point. Electronic gaps of 254 and 263 meV appear in the band structure of graphene. And the Fermi levels fall in the middle of the generated electronic gaps. The occurred shift through gating in the density of the state of graphene is detected by means of scanning tunneling microscope images, where the images distinguish the intact density of states from those affected by the dipolar overlay.

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 score0.002
Threshold uncertainty score0.007

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 studies0.0000.001
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 head0.055
GPT teacher head0.357
Teacher spread0.302 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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Same venuephysica status solidi (RRL) - Rapid Research LettersSame topicGraphene research and applicationsFrench-language works237,207