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Record W3101650989

Graphene electronic structure in charge density waves

2017· article· en· W3101650989 on OpenAlexaff

Bibliographic record

VenueLanzhou University Institutional Repository · 2017
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsUniversity of British ColumbiaUniversity of ManitobaWinnipeg Institute for Theoretical Physics
Fundersnot available
KeywordsGrapheneCharge (physics)Charge densityCondensed matter physicsCharge density waveElectronic structureMaterials sciencePhysicsNanotechnologyQuantum mechanicsSuperconductivity
DOInot available

Abstract

fetched live from OpenAlex

We introduce the idea that the electronic band structure of a charge density wave system may mimic that of graphene. In that case, a class of materials quite different from graphene might be opened up to exploit graphene's remarkable properties. For such materials, their dynamical rather than static properties are crucial. The charge density wave system requires a wave geometry simply related to graphene and self-consistency among the electrons which requires the net Coulomb and phonon-mediated parts of the electron-electron interactions to be attractive. Our model leads to an analytical expression for the total energy in terms of the effective electron mass mu, the electron density rho(0), and the strength (v) over tilde (K) of the net electron-electron interaction. We examine the limitations set upon (v) over tilde (K) by self-consistency, stability, and the approximation in the electronic state calculation and find them to be mutually compatible.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.009
GPT teacher head0.227
Teacher spread0.217 · 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 designTheoretical or conceptual
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
Published2017
Admission routes1
Has abstractyes

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