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Record W4403335632 · doi:10.1021/acsapm.4c02152

Alternative Surface Treatment for the Enhanced Adhesion of Polytetrafluoroethylene Films via Atmospheric Pressure Nitrogen Plasma

2024· article· en· W4403335632 on OpenAlexafffund
Williams Marcel Caceres-Ferreira, Alex Destrieux, Jacopo Profili, Andrée‐Anne Guay‐Bégin, Sethumadhavan Ravichandran, Morgane Laurent, M. G. Nolan, Andrew T. Smith, Hua Wang, Gaétan Laroche

Bibliographic record

VenueACS Applied Polymer Materials · 2024
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsUniversité LavalHôpital Saint-François d'Assise
FundersCentre Hospitalier Universitaire de QuébecCentre québécois sur les matériaux fonctionnelsNatural Sciences and Engineering Research Council of CanadaSaint-Gobain Northboro Research and Development Center
KeywordsPolytetrafluoroethyleneAtmospheric-pressure plasmaAdhesionMaterials scienceNitrogenAtmospheric pressurePlasmaComposite materialSurface modificationChemical engineeringNanotechnologyChemistryOrganic chemistryMeteorologyEngineering

Abstract

fetched live from OpenAlex

Polytetrafluoroethylene (PTFE) presents a notably challenging surface for enhancing its adhesion properties. Here, a surface modification of PTFE via atmospheric pressure nitrogen plasma is presented. This treatment produces peel strength values comparable to conventional wet chemical treatments. Indeed, plasma-treated surfaces were compared with those obtained with heat-treated PTFE and conventional chemically etched PTFE. All plasma treatments resulted in altered wettability, increased surface roughness, partial defluorination of the substrates, and the incorporation of oxygen and nitrogen functional groups on the polymer surface. Similar surface topologies were observed between the thermally treated and plasma-treated PTFEs, suggesting that the plasma approach induced a heating process on the substrate. The effect of these outcomes on the adhesive response of plasma-treated substrates was investigated by 180° and T-peel tests with different adhesives (acrylic adhesive, acrylic adhesive tape, and rubber adhesive tape). Peel test results showed a drastic increase in the adhesion of plasma-treated PTFE compared to the untreated PTFE films, reaching similar or higher values to those obtained with the chemically etched PTFE. Additionally, the evolution of the bonding properties of plasma-treated surfaces was studied over time. The peel strength increased from ≈0 N/cm (untreated) to 1.7 ± 1.2 N/cm when measured by a 180° peel test with an acrylic adhesive. There was also an increase from 0.3 ± 0.1 and 2.5 ± 0.2 N/cm to 5.3 ± 0.1 and 9.2 ± 0.6 N/cm when measured by the T-peel test with acrylic and rubber adhesive tapes, respectively. The results revealed that the measured peel strength stabilized after 15 days, remaining constant over 365 days. The remarkable results highlight the possibility of replacing conventional solvent-based chemical processes with a dry atmospheric pressure treatment and also emphasize the potential, lower environmental impact, and cost effectiveness of a nitrogen-based plasma process compared to the wet chemical etching approaches commonly used in the industry today for the surface treatment of fluoropolymers.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.006
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

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 head0.018
GPT teacher head0.258
Teacher spread0.240 · 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 teacher head, not a consensus.

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

Citations11
Published2024
Admission routes2
Has abstractyes

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