Issue 41, 2017

Revisiting the generalized scaling law for adhesion: role of compliance and extension to progressive failure

Abstract

A generalized scaling law, based on the classical fracture mechanics approach, is developed to predict the bond strength of adhesive systems. The proposed scaling relationship depends on the rate of change of debond area with compliance, rather than the ratio of area to compliance. This distinction can have a profound impact on the expected bond strength of systems, particularly when the failure mechanism changes or the compliance of the load train increases. Based on the classical fracture mechanics approach for rate-independent materials, the load train compliance should not affect the force capacity of the adhesive system, whereas when the area to compliance ratio is used as the scaling parameter, it directly influences the bond strength, making it necessary to distinguish compliance contributions. To verify the scaling relationship, single lap shear tests were performed for a given pressure sensitive adhesive (PSA) tape specimens with different bond areas, number of backing layers, and load train compliance. The shear lag model was used to derive closed-form relationships for the system compliance and its derivative with respect to the debond area. Digital image correlation (DIC) is implemented to verify the non-uniform shear stress distribution obtained from the shear lag model in a lap shear geometry. The results obtained from this approach could lead to a better understanding of the relationship between bond strength and the geometry and mechanical properties of adhesive systems.

Graphical abstract: Revisiting the generalized scaling law for adhesion: role of compliance and extension to progressive failure

Supplementary files

Article information

Article type
Paper
Submitted
02 Jun 2017
Accepted
01 Sep 2017
First published
04 Sep 2017

Soft Matter, 2017,13, 7529-7536

Revisiting the generalized scaling law for adhesion: role of compliance and extension to progressive failure

A. R. Mojdehi, D. P. Holmes and D. A. Dillard, Soft Matter, 2017, 13, 7529 DOI: 10.1039/C7SM01098B

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