Parametric Modeling Analysis and Lifetime Prediction of Large-Size Conductive Adhesive Bonding Layers

Wenjian Li, Aowen Luo, Lin Yang, Yanpei Wu, Xiao Liu, Xiaoli Wang, Yutai Su, Tiancun Hu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

During the use of electronic devices, the thermal cycling experienced can impose enormous alternating stress cycles on the chip adhesive layers, which can accumulate over time to cause fatigue cracks, leading to the failure of the adhesive layers. To accurately and rapidly simulate the effects of thermal cycling on the chip adhesive layers, this paper adopts a parametric simulation-based approach, establishing a set of physical modeling methods for thermal cycle fatigue failure of chip adhesive structures. Through the secondary development function of Abaqus-Python, this study parametrically processes various physical variables that affect the reliability and lifetime of chip adhesive structures, allowing the model to account for changes in different working environments, stress states, and material parameters. This method, which combines numerical simulation technology and parametric modeling, can accurately predict the thermal cycling fatigue failure of chip adhesive layers under various working conditions and stress conditions. By establishing a simulation model that approximates actual working conditions, this method is expected to guide engineering practice, improving the reliability and stability of chip adhesive structures.

Original languageEnglish
Title of host publicationComputational and Experimental Simulations in Engineering - Proceedings of ICCES 2024 — International Conference on Computational and Experimental Engineering and Sciences ICCES
EditorsKun Zhou
PublisherSpringer Science and Business Media B.V.
Pages665-678
Number of pages14
ISBN (Print)9783031816727
DOIs
StatePublished - 2025
Event30th International Conference on Computational and Experimental Engineering and Sciences, ICCES 2024 - Singapore, Singapore
Duration: 3 Aug 20246 Aug 2024

Publication series

NameMechanisms and Machine Science
Volume175 MMS
ISSN (Print)2211-0984
ISSN (Electronic)2211-0992

Conference

Conference30th International Conference on Computational and Experimental Engineering and Sciences, ICCES 2024
Country/TerritorySingapore
CitySingapore
Period3/08/246/08/24

Keywords

  • Fatigue failure
  • Life prediction
  • Parametric modeling
  • Thermal cycling

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