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Technical Brief

Prediction of Interfacial Surface Energy and Effective Fracture Energy From Contaminant Concentration in Polymer-Based Interfaces

[+] Author and Article Information
Denizhan Yavas

Department of Aerospace Engineering,
Iowa State University,
Ames, IA 50011-2271
e-mail: dyavas@iastate.edu

Ashraf F. Bastawros

Mem. ASME
Department of Aerospace Engineering,
Iowa State University,
Ames, IA 50011-2271
e-mail: bastaw@iastate.edu

1Corresponding author.

Contributed by the Applied Mechanics Division of ASME for publication in the JOURNAL OF APPLIED MECHANICS. Manuscript received January 5, 2017; final manuscript received February 3, 2017; published online February 22, 2017. Assoc. Editor: Junlan Wang.

J. Appl. Mech 84(4), 044501 (Feb 22, 2017) (5 pages) Paper No: JAM-17-1011; doi: 10.1115/1.4035931 History: Received January 05, 2017; Revised February 03, 2017

The principals of interfacial fracture mechanics and modified Gibbs adsorption equation are utilized to provide a predictive correlation for the macroscopic (effective) fracture toughness of polymer-based adhesive interfaces, exposed to varying level of contaminant concentration. The macroscopic fracture toughness measurement by double cantilever beam test exhibits a progressive deterioration with the increase of the contaminant surface concentration. The associated variation of fracture surface morphology exhibits ductile-to-brittle failure transition, caused by the contamination-induced suppression of plastic deformation within the adhesive layer. The corresponding intrinsic interfacial surface energy is extracted by finite-element simulation, employing surface-based cohesive elements. The modified Gibbs adsorption equation is utilized to correlate the contamination-induced degradation of the interfacial surface energy as a function of contaminant surface concentration. Interfacial fracture mechanics principals are applied to extend the correlation to the macroscopic fracture toughness of the interface. With additional examination of other systems, the proposed correlation may provide the basis for nondestructive evaluation of bond line integrity, exposed to different levels of contaminant.

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References

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Figures

Grahic Jump Location
Fig. 1

(a) A representative set of force–displacement curves and (b) the corresponding fracture energy release rate G-curves, obtained from DCB experiments, along with the numerical results (dashed lines), for the examined cases

Grahic Jump Location
Fig. 2

Optical images of the fracture surfaces of (a) the control, (b) 3 μg/cm2, and (c) 55 μg/cm2 contaminated cases, showing the marked difference in roughness

Grahic Jump Location
Fig. 3

Topologies of the fracture surface, measured by 3D noncontact surface profilometer with 1.45 × 1.05 mm2 field of view. (a) and (b) Three-dimensional rendering of the fracture surface topologies. (c) and (d) Height profiles along the marked lines, showing the roughening and extent of plasticity in the control case, and the smooth profile in the 55 μg/cm2 contaminated case.

Grahic Jump Location
Fig. 4

Summary of the experimentally measured macroscopic fracture energy (solid squares) and the numerically calibrated interfacial surface energy (open squares) as a function of contamination concentration. The error bars depict standard deviation of the data. The dashed and dotted lines stand for the corresponding predictive correlations of Eqs. (3) and (6).

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