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Record W2755561259 · doi:10.1021/acs.jpcc.7b06107

Long Vertical Distance Bonding of the Hexagonal Boron Nitride Monolayer on the Cu(111) Surface

2017· article· en· W2755561259 on OpenAlexfundno aff
Christine Brülke, Timo Heepenstrick, Niklas Humberg, Ina Krieger, M. Sokołowski, Simon C. Weiss, F. Stefan Tautz, Serguei Soubatch

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2017
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsnot available
FundersDeutsche ForschungsgemeinschaftDeutscher Akademischer AustauschdienstDiamond Light SourceUniversité du Québec à Montréal
KeywordsMonolayerScanning tunneling microscopeSuperstructureMaterials scienceCrystallographyBoron nitrideLayer (electronics)DiffractionNitrideHexagonal boron nitrideLow-energy electron diffractionElectron diffractionCondensed matter physicsNanotechnologyChemistryOpticsGraphenePhysics

Abstract

fetched live from OpenAlex

The hexagonal boron nitride (hBN) monolayer on the Cu(111) surface has recently been considered an example of an extremely weak hBN/metal interaction, as indicated, e.g., from the presence of an only electronic Moiré-like superstructure that was observed in scanning tunneling microscopy images. From these results, a large bonding distance of the hBN sheet to the topmost Cu layer can be envisaged but has not been proven so far. We report a structural analysis of the hBN/Cu(111) interface based on high resolution low energy electron diffraction and normal incidence X-ray standing wave experiments. We find that both the boron and nitrogen atoms are located at very large vertical distances of d B = 3.25 ± 0.02 Å and d N = 3.22 ± 0.03 Å with respect to the nominal position of the topmost Cu(111) layer. Significant vertical buckling and lateral distortions of the hBN layer can be excluded. These results demonstrate that the hBN monolayer on the Cu(111) surface is indeed well described by a rigid and geometrically well separated sheet.

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)0.001
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 score0.007
Threshold uncertainty score0.404

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.024
GPT teacher head0.298
Teacher spread0.275 · 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

Citations32
Published2017
Admission routes1
Has abstractyes

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