Fine-tuning of chemical and physical polymer surface modifications by atmospheric pressure post-discharge plasma and its correlation with adhesion improvement - Archive ouverte HAL Access content directly
Journal Articles Surface and Coatings Technology Year : 2019

Fine-tuning of chemical and physical polymer surface modifications by atmospheric pressure post-discharge plasma and its correlation with adhesion improvement

Abstract

Our study focuses on the use of a remote atmospheric pressure plasma process for the improvement of polymer surface reactivity. Indeed, surface activation of carbon-fiber-reinforced polymers that use a polyetheretherketone matrix is required to achieve strong and long-term adhesion of paint on the composite. Emphasis will be placed on the contribution of gas plasma used on surface modification. We use two techniques to characterize adherence improvement: a qualitative and industrial approach with a cross-cut test and a quantitative approach with a three-point bending test. However, to provide a better understanding of the plasma-induced modifications using air or nitrogen gas, diagnostics of the surface are also necessary. The wettability improvement, chemical surface modifications, and topography are analyzed by using contact angle measurement, X-ray photoelectron spectroscopy, and atomic force microscopy, respectively. The combination of these diagnostics highlights the capability of plasma treatment to tune the plasma/surface interactions depending on gas plasma, which results in improved adhesion.
Fichier principal
Vignette du fichier
Bres_23772.pdf (1.9 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-02108788 , version 1 (24-04-2019)

Identifiers

Cite

Lucie Bres, Audrey Sanchot, Bertrand Rives, Nicolas Ghérardi, Nicolas Naudé, et al.. Fine-tuning of chemical and physical polymer surface modifications by atmospheric pressure post-discharge plasma and its correlation with adhesion improvement. Surface and Coatings Technology, 2019, 362, pp.388-396. ⟨10.1016/j.surfcoat.2019.01.102⟩. ⟨hal-02108788⟩
50 View
71 Download

Altmetric

Share

Gmail Facebook X LinkedIn More