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Record W2990016752 · doi:10.1515/nanoph-2019-0385

Helium focused ion beam direct milling of plasmonic heptamer‐arranged nanohole arrays

2019· article· en· W2990016752 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNanophotonics · 2019
Typearticle
Languageen
FieldEngineering
TopicPlasma Diagnostics and Applications
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMaterials scienceFocused ion beamPlasmonBeam (structure)FabricationIon milling machineOpticsOptoelectronicsIon beamIonNanotechnologyChemistryLayer (electronics)

Abstract

fetched live from OpenAlex

Abstract We fabricate plasmonic heptamer‐arranged nanohole (HNH) arrays by helium (He) focused ion beam (HeFIB) milling, which is a resist‐free, maskless, direct‐write method. The small He + beam spot size and high milling resolution achieved by the gas field‐ionization source used in our HeFIB allows the milling of high aspect ratio (4:1) nanoscale features in metal, such as HNHs incorporating 15 nm walls of high verticality between holes in a 55‐nm‐thick gold film. Drifts encountered during the HeFIB milling of large arrays, due to sample stage vibrations or He beam instability, were compensated by a drift correction technique based on in situ He ion imaging of alignment features. Our drift correction technique yielded 20 nm maximum dislocation of HNHs, with 6.9 and 4.6 nm average dislocations along the horizontal and vertical directions, respectively. The measured optical resonance spectra of the fabricated plasmonic HNH arrays are presented to support the fabrication technique. Defects associated with HeFIB milling are also discussed.

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.

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 score0.035
Threshold uncertainty score0.812

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 head0.182
Teacher spread0.177 · 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