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Record W2166931966 · doi:10.1088/1367-2630/13/6/063011

Low-energy electron point projection microscopy of suspended graphene, the ultimate ‘microscope slide’

2011· article· en· W2166931966 on OpenAlexafffund
J. Mutus, Lucian Livadaru, Jeremy T. Robinson, R. Urban, Mark Salomons, Martin Cloutier, Robert A. Wolkow

Bibliographic record

VenueNew Journal of Physics · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Electron Microscopy Techniques and Applications
Canadian institutionsNational Institute for NanotechnologyUniversity of Alberta
FundersAlberta Innovates - Technology Futures
KeywordsGraphenePhysicsElectronElectron holographyOpticsElectron microscopeTransmission electron microscopyGraphene nanoribbonsOptoelectronicsMaterials scienceNanotechnology

Abstract

fetched live from OpenAlex

Point projection microscopy (PPM) is used to image suspended graphene by using low-energy electrons (100–205 eV). Because of the low energies used, the graphene is neither damaged nor contaminated by the electron beam for doses of the order of 10 7 electrons per nm 2 . The transparency of graphene is measured to be 74%, equivalent to electron transmission through a sheet twice as thick as the covalent radius of sp 2 -bonded carbon. Also observed is rippling in the structure of the suspended graphene, with a wavelength of approximately 26 nm. The interference of the electron beam due to diffraction off the edge of a graphene knife edge is observed and is used to calculate a virtual source size of 4.7±0.6 Å for the electron emitter. It is demonstrated that graphene can serve as both the anode and the substrate in PPM, thereby avoiding distortions due to strong field gradients around nanoscale objects. Graphene can be used to image objects suspended on the sheet using PPM and, in the future, electron holography.

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 score0.004
Threshold uncertainty score0.012

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.010
GPT teacher head0.294
Teacher spread0.283 · 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

Citations50
Published2011
Admission routes2
Has abstractyes

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