Characterization of delamination failure of two-dimensional horseshoe stretchable interconnects using digital image correlation. (February 2021)

• Record Type: Journal Article
• Authors: Chen, Cheng; Chen, Shaoxuan; Gu, Wanghang; Zhang, Hongru; Liu, Bing
• Is Part Of: Polymer testing. Volume 94(2021)
• Publication Date: 2021-02
• Subjects: Stretchable interconnect -- Delamination failure -- Digital image correlation (DIC) -- von mises strain; Polymers -- Testing -- Periodicals; Polymères -- Tests -- Périodiques; 620.1920287
• DOI: 10.1016/j.polymertesting.2020.107041
• Languages: English
• ISSNs: 0142-9418

Abstract

Abstract: The purpose of this paper is to achieve efficient detection and prediction of delamination failure of stretchable interconnects by using digital image correlation (DIC) methods. In order to achieve this goal, a visual experiment system and a delamination failure detection and prediction method are designed, and the mechanical characteristics of two-dimensional horseshoe-shaped interconnect are experimentally studied. Firstly, the evolution law of von Mises strain on the surface of the sample was analyzed, and then the time and location of the failure were determined by measuring and calculating the strain at the failure site, and the site that was about to fail was predicted based on this criterion. The experimental results show that von Mises strain field has a distribution feature closely related to the two-dimensional horseshoe geometry, and the boundaries of each strain region are obvious. When a 2 μm layer thickness sample was stretched 3.2 mm at 50 °C, the sample delaminates at 60 pixels on the horizontal reference line, based on the 0.0187 strain difference at the failure point, the location where the failure is about to occur is successfully predicted. Highlights: The delamination failure of flexible electronic composite film is detected by DIC. The evolution law of interconnect strain field is measured accurately. Temperature and layer thickness affect the strain field. The location of the failure point is successfully predicted.