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Record W2077647201 · doi:10.1080/10420150.2012.738209

Ions and carbon nanostructures

2012· article· en· W2077647201 on OpenAlexfundno aff
J. Gyulai, Levente Tapasztó, Zsolt E. Horváth, Péter Nemes‐Incze, Z. Osváth, László Péter Biró

Bibliographic record

VenueRadiation effects and defects in solids · 2012
Typearticle
Languageen
FieldMaterials Science
TopicGraphene research and applications
Canadian institutionsnot available
FundersUniversity of Lethbridge
KeywordsGrapheneMaterials scienceCarbon nanotubeIonNanotechnologyGraphiteIon beamIrradiationNanolithographyComposite materialChemistryFabricationPhysics

Abstract

fetched live from OpenAlex

First experiments on swift ion irradiation of highly oriented pyrolythic graphite led to formation of carbon nanotubes (CNT) at the cascade eruption points. CNT length was in the micron range, which corresponded to an explosive crystallization of the carbon plume with about sound velocity. Multiplicity of CNT walls depended on cascade density: single wall CNTs were formed for approx. 200 MeV Xe ions, while multiwall CNTs for Kr, Ne ions of similar energy. Ion beam created defects were clearly visible on scanning tunneling microscopy (STM) images with atomic resolution. Second part of the paper deals with results of ion irradiation to sensitize CNT-s to reach, e.g. gas sensing properties using mainly changes in electrical conductivity of the bunch of CNTs. A third part of the paper contains some results on irradiated graphene. A new nanolithography technique of graphene used STM as a tool for nanostructuring graphene with crystallographic orientation control and line width of the order of few nanometers. The process enables to produce few nm wide stripes with precise crystallographic orientation.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.648
Threshold uncertainty score0.262

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 science0.0000.000
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 head0.006
GPT teacher head0.263
Teacher spread0.257 · 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 designObservational
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
Published2012
Admission routes1
Has abstractyes

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