电磁兼容配方与工作电流的相互作用模型及Cu-Al线键在恶劣环境下工作的可靠性

P. Lall, Shantanu Deshpande, YiHua Luo, L. Nguyen
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引用次数: 2

摘要

需要在恶劣环境中持续运行的高可靠性应用程序的迁移需要更好地了解运行压力下的加速因素。铜线长时间暴露在高温下会导致过量金属间化合物的生长和界面的退化。铜线键在高温电流条件下的行为尚不完全清楚。暴露在大电流下可能会引起焦耳加热和电迁移,因此与低电流操作条件相比,降解率显着增加。此外,无偏条件下的加速试验结果不能用于此类大功率部件的寿命预测。用于封装芯片和互连的EMCs在配方上可能有很大差异,包括pH值、孔隙度、扩散速率、水平和污染物的组成。不同材料的选择,如成型过程中使用的电磁兼容,在确定线键系统的使用寿命方面起着关键作用。为了能够真实地代表期望的可靠性,需要能够考虑到环境条件、操作条件和电磁兼容公式的预测模型。在本文中,采用不同的EMCs对一组零件进行高温电流环境(温度范围为150°C-200°C, 0.2A-1A)。为了计算Cu-Al WB在高压高温下的加速系数,建立了一种人工神经网络驱动的预测模型,用于估计输入变量的β灵敏度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Model for Interaction of EMC Formulation with Operating Current and Reliability of Cu-Al Wirebonds Operating in Harsh Environments
The migration of high-reliability applications requiring sustained operation in harsh environments needs a better understanding of the acceleration factors under the stresses of operation. Prolonged exposure of the copper wire to elevated temperatures results in growth of excessive intermetallics and degradation of the interface. Behavior of Copper wirebond under high current-temperature conditions is not yet fully understood. Exposure to high current may induce Joule heating and electromigration, and thus significantly increase the degradation rate in comparison with low current operating conditions. Further, the accelerated test results of unbiased conditions cannot be used for life prediction of such high powered parts. EMCs used for encapsulation of the chip and the interconnects may vary widely in their formulation including pH, porosity, diffusion rates, levels and composition of the contaminants. Selection of different materials, such as EMC used in the molding process plays key role in defining lifetime for wirebond system. There is need for predictive models which can account for the exposure to environmental conditions, operating conditions and the EMC formulation in order to be realistically representative of the expected reliability. In this paper, a set of parts, molded with different EMCs were subjected to high temperature-current environment (temperature range of 150°C-200°C, 0.2A-1A). An artificial neural network (ANN) driven predictive model for estimation of the beta-sensitivities of the input variables has been developed for computation of the acceleration factor for the Cu-Al WB under high voltage and high temperature.
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