journal article·2008-01

Novel Techniques for Characterization of Fast-Cure Anisotropic Conductive and Non-conductive Adhesives

Mary Teo

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Abstract

Anisotropic conductive adhesives (ACAs) and non-conductive adhesives (NCAs) are widely used in adhesive flip chip technology. Typically, ACAs and NCAs are formulated to achieve a complete cure in less than 60 s when curing between 180 and 250°C. The fast-cure characteristic of these adhesives poses great difficulties for conventional cure characterization techniques. In this study, novel cure monitoring techniques including Modulated Differential Scanning Calorimetry (MDSC), Dielectric Analysis (DEA) and Fibre Bragg Grating (FBG) techniques were evaluated. Cure-related properties in terms of adhesion strength and cure shrinkage were characterized. Findings showed that MDSC is an improved method for analyzing partial-cured samples compared to conventional Differential Scanning Calorimetry (DSC). It was also demonstrated that cure monitoring of these fast-cure materials was feasible using both DEA and FBG techniques. Adhesion study showed good correlation of adhesion strength and failure modes with degree of cure. Failure mode changes from mixed to cohesive mode at 50% degree of cure. Above 90% degree of cure, adhesion strength was found to surpass the shear strength of silicon substrate. These results clearly emphasize the importance of cure optimization to attain sufficient adhesion strength of these adhesives. For cure shrinkage measurement, feasibility of both FBG and Thermomechanical Analysis (TMA) techniques was demonstrated. In summary, this study has demonstrated the applicability of several techniques for cure behaviour characterization of fast-cure ACA and NCA materials. Key findings from this work represent a significant step towards cure process optimization for the development of reliable adhesives for flip chip interconnects.
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Research context

OpenAlex topics: Electronic Packaging and Soldering Technologies · 3D IC and TSV technologies · Epoxy Resin Curing Processes

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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