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Record W1495792579

Surface energy modification by radiofrequency inductive and capacitive plasmas at low pressures on sugar maple: an exploratory study.

2009· article· en· W1495792579 on OpenAlexaboutno aff
Vincent Blanchard, Pierre Blanchet, Bernard Riedl

Bibliographic record

VenueWood and Fiber Science (Society of Wood Science and Technology) · 2009
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsnot available
Fundersnot available
KeywordsCoatingMaterials scienceContact angleSurface energyWettingMapleAdhesionPenetration (warfare)SugarMoistureChemical engineeringYellow birchSubstrate (aquarium)Composite materialPlasmaPulp and paper industryChemistryOrganic chemistry
DOInot available

Abstract

fetched live from OpenAlex

The wood products industry is going through hard times in both Canada and the US.It is faced with competition from emerging economies and substitution products.The North American economy is slowing down with decreasing demand for wood products.Under these conditions, the industry should be innovative and develop the next generation of wood products.Plasma technology could be used to improve wood surface properties and compensate for the variations to be expected from an organic living material, which is sensitive to its environment (moisture, water, temperature, ultraviolet light).In recent years, the plastic and textile industries have begun experimenting with plasma technology to activate surfaces, mainly to improve coating/substrate adhesion.The literature on potential applications of plasma treatment to wood surfaces is very limited.This report describes the results of an exploratory study on the effect of plasma treatments on sugar maple wood using different gases and mixtures (N 2 , H 2 , O 2 , and Ar) at different pressures .Water wettability and adhesion between surface and waterborne polyurethane acrylate coatings were also studied.The results show that it was possible, under certain conditions, to significantly increase wood/coating adhesion by 30 -100%.This improvement is correlated with improvements in wood surface energy and coating penetration depth.In addition, chemical analyses showed that, with some plasma types, the treatment led to new atoms being grafted.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
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 score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.007
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.018
GPT teacher head0.247
Teacher spread0.229 · 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

Citations22
Published2009
Admission routes1
Has abstractyes

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