MétaCan
Menu
Back to cohort
Record W4391099936 · doi:10.3390/ma17020521

Differential Etching of Rays at Wood Surfaces Exposed to an Oxygen Glow Discharge Plasma

2024· article· en· W4391099936 on OpenAlexafffund
Kenneth J. Cheng, Weicong Ma, Philip D. Evans

Bibliographic record

VenueMaterials · 2024
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaBritish Columbia Knowledge Development FundFPInnovationsAustralian National University
KeywordsEtching (microfabrication)Plasma etchingMaterials sciencePlasmaComposite materialIsotropic etchingMicrostructureDry etchingScanning electron microscopeReactive-ion etchingEngravingAnalytical Chemistry (journal)ChemistryLayer (electronics)PhysicsChromatography

Abstract

fetched live from OpenAlex

Basswood samples were exposed to oxygen glow-discharge plasmas for 30 min, and etching of radial and tangential longitudinal surfaces was measured. It was hypothesized that there would be a positive correlation between etching and plasma energy, and differential etching of wood surfaces because of variation in the microstructure and chemical composition of different woody tissues. Etching at the surface of basswood samples was examined using profilometry. Light and scanning electron microscopy were used to examine the microstructure of samples exposed to plasma. There was a large effect of plasma energy on etching of basswood surfaces, and radial surfaces were etched to a greater extent than tangential surfaces. However, rays at radial surfaces were more resistant to etching than fibers, resulting in greater variation in the etching of radial versus tangential surfaces. The same phenomenon occurred at radial surfaces of balsa wood, jelutong and New Zealand white pine subjected to plasma etching. The possible reasons for the greater resistance of rays to plasma etching are explored, and it is suggested that such differential etching of wood surfaces may impose a limitation on the use of plasma to precisely etch functional patterns at wood surfaces (raised pillars, grooves), as has been done with other materials.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.011
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0130.001

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 head0.029
GPT teacher head0.266
Teacher spread0.237 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueMaterialsSame topicSurface Modification and SuperhydrophobicityFrench-language works237,207