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Record W4376272235 · doi:10.1111/ijac.14431

High aspect ratio sapphire micromachining by ultraviolet laser‐induced plasma‐assisted ablation (LIPAA)

2023· article· en· W4376272235 on OpenAlexafffund
D. Cole, Ricardo J. Zednik, Lucas A. Hof

Bibliographic record

VenueInternational Journal of Applied Ceramic Technology · 2023
Typearticle
Languageen
FieldEngineering
TopicLaser Material Processing Techniques
Canadian institutionsÉcole de Technologie Supérieure
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsMaterials scienceSapphireAblationLaser ablationLaserUltravioletOptoelectronicsSurface micromachiningEtching (microfabrication)PlasmaX-ray laserOpticsSurface roughnessSurface finishFabricationLaser power scalingNanotechnologyComposite material

Abstract

fetched live from OpenAlex

Abstract The ultraviolet laser‐induced plasma‐assisted ablation performed in this article can attain deep and high‐quality engravings in sapphire without necessitating volatile solutions or expensive equipment such as high‐power ultrashort‐pulsed lasers. The dominant mechanism of ablation is discovered to be from the direct ablation of excited sapphire surfaces and not from the plasma generated from the target material. Only an initial deposition from the target is needed to initiate the direct ablation. Note that 20‐µm wide, 30‐µm deep channel and hole features with a surface roughness (Sa) of .65 µm are achieved at an etching rate of .3 µm per pulse without the need for extensive cleaning. Engravings can reach up to 150‐µm depths at a maximum tapering angle of 5° until the shrinking absorbent surface vanishes, and 500‐µm wide 430‐µm deep topside through‐cutting is achieved. This study characterizes the morphology of direct laser ablation of transient absorbent sapphire surfaces. This method demonstrates the potential for the low‐cost rapid engraving of high aspect ratio features in transparent sapphire substrates.

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 score0.001
Threshold uncertainty score0.003

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)0.0010.000

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 head0.008
GPT teacher head0.235
Teacher spread0.227 · 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

Citations4
Published2023
Admission routes2
Has abstractyes

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Same venueInternational Journal of Applied Ceramic TechnologySame topicLaser Material Processing TechniquesFrench-language works237,207