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Record W2329394242 · doi:10.1515/aot-2014-0047

Interferometric femtosecond laser processing for nanostructuring inside thin film

2014· article· en· W2329394242 on OpenAlexaff
Stephen Ho, Kitty Kumar, Kenneth K. C. Lee, Jianzhao Li, Peter R. Herman

Bibliographic record

VenueAdvanced Optical Technologies · 2014
Typearticle
Languageen
FieldEngineering
TopicLaser Material Processing Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFemtosecondMaterials scienceLaserThin filmOpticsWavelengthInterferometryDielectricRefractive indexNanoscopic scaleFabricationOptoelectronicsInterference (communication)NanotechnologyPhysics

Abstract

fetched live from OpenAlex

Abstract Femtosecond laser interactions inside transparent dielectric films of refractive index, n film, with tight focusing presents strong nonlinear interactions that can be preferentially confined at the fringe maxima as formed by Fabry-Perot interference, to generate thin nanoscale plasma disks separated on half-wavelength, λ/2n film. The nano-thin disk explosions can be controlled inside the film to cleave open subwavelength internal cavities at single or multiple periodic depths at low laser exposure, while higher exposure will eject a quantised number of film segments with segment thickness defined by the laser wavelength. This new method enables high-resolution film patterning for ejecting nanodisks at quantised film depth for colouring and three-dimensional (3D) surface structuring, as well as for fabrication of free-standing nanofilms.

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 score0.002
Threshold uncertainty score0.006

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.232
Teacher spread0.223 · 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

Citations7
Published2014
Admission routes1
Has abstractyes

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