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Record W2757412571 · doi:10.1039/c7cp04825d

The ionic versus metallic nature of 2D electrides: a density-functional description

2017· article· en· W2757412571 on OpenAlexafffund
Stephen G. Dale, Erin R. Johnson

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2017
Typearticle
Languageen
FieldChemical Engineering
TopicAmmonia Synthesis and Nitrogen Reduction
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsExfoliation jointIonic bondingDensity functional theoryElectronDipoleValence electronMetalValence (chemistry)Dispersion (optics)Chemical physicsCore electronMaterials scienceElectron densityLondon dispersion forceCondensed matter physicsChemistryMolecular physicsIonGrapheneComputational chemistryNanotechnologyPhysicsMoleculevan der Waals force

Abstract

fetched live from OpenAlex

). Examination of the valence states during exfoliation identifies intercalated electrons in the bulk and weakly-bound surface-states in the fully-expanded case. The calculated exfoliation energies for the 2D electrides are found to be much higher than for typical 2D materials, which is attributed to the ionic nature of the electrides and the strong Coulomb forces governing the interlayer interactions. Conversely, the calculated sliding barriers are found to be quite low, comparable to those for typical 2D materials, and are effectively unchanged by exclusion of dispersion. We conjecture that the metallic nature of the interstitial electrons allows the atomic layers to move relative to each other without significantly altering the interlayer binding. Finally, comparison with previous works reveals the importance of a system-dependent dispersion correction in the density-functional treatment.

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 score0.010
Threshold uncertainty score0.895

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 head0.019
GPT teacher head0.243
Teacher spread0.224 · 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

Citations21
Published2017
Admission routes2
Has abstractyes

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