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Record W1979671908 · doi:10.1002/ppap.201200125

Different Polymerizing Characteristics of Ar/He Atmospheric Pressure Plasma Jets at Room Temperature

2013· article· en· W1979671908 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

VenuePlasma Processes and Polymers · 2013
Typearticle
Languageen
FieldMedicine
TopicPlasma Applications and Diagnostics
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsX-ray photoelectron spectroscopyAtmospheric pressureAtmospheric-pressure plasmaPlasmaRadicalFibroinAnalytical Chemistry (journal)Acrylic acidPolymerizationMaterials sciencePolymerDeposition (geology)Plasma polymerizationChemistryPolymer chemistryChemical engineeringComposite materialOrganic chemistryMonomer

Abstract

fetched live from OpenAlex

Abstract In this paper, the different discharge and polymerizing characteristics of Ar and He atmospheric pressure plasma jets (APPJs) were studied. The as‐deposited polymer of acrylic acid (PAA) on silk fibroin film (SFF) by APPJs with Ar/O 2 and He/O 2 gases is investigated with AFM, FESEM and XPS. Optical emission spectroscopy (OES) measurements indicated that various reactive radicals, such as OH and O as well as some acrylic acid (AA) particles existed in the plasma jets. AFM images showed that the He/O 2 plasma‐deposited films had the most homogeneous characteristics and good water resistance properties. The cross‐sections of silicon substrates obtained by FESEM showed that the deposition rates of PAA were 50 nm · min −1 and 15 nm · min −1 for Ar/O 2 and He/O 2 plasmas, respectively. Also, according to XPS analysis, He/O 2 plasma created a higher concentration of carboxyl groups on the deposited film than when Ar/O 2 plasma was used. magnified image

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 categoriesMeta-epidemiology (narrow)
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 score0.189
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.007
GPT teacher head0.217
Teacher spread0.210 · 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