2024

Vol.31 No.2

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  • Journal of the Microelectronics and Packaging Society
  • Volume 31(2); 2024
  • Article

Review

Journal of the Microelectronics and Packaging Society 2024;31(2):28-35. Published online: Jul, 25, 2024

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DOI : doi.org/10.6117/kmeps.2024.31.2.028

Nondestructive Quantification of Corrosion in Cu Interconnects Using Smith Charts

  • Minkyu Kang* , Namgyeong Kim* , Hyunwoo Nam, and Tae Yeob Kang†
    Department of Mechanical Engineering, The University of Suwon, Hwaseong 18323, Korea
Corresponding author E-mail: tykang@suwon.ac.kr
Abstract

Corrosion inside electronic packages significantly impacts the system performance and reliability, necessitating non-destructive diagnostic techniques for system health management. This study aims to present a non-destructive method for assessing corrosion in copper interconnects using the Smith chart, a tool that integrates the magnitude and phase of complex impedance for visualization. For the experiment, specimens simulating copper transmission lines were subjected to temperature and humidity cycles according to the MIL-STD-810G standard to induce corrosion. The corrosion level of the specimen was quantitatively assessed and labeled based on color changes in the R channel. S-parameters and Smith charts with progressing corrosion stages showed unique patterns corresponding to five levels of corrosion, confirming the effectiveness of the Smith chart as a tool for corrosion assessment. Furthermore, by employing data augmentation, 4,444 Smith charts representing various corrosion levels were obtained, and artificial intelligence models were trained to output the corrosion stages of copper interconnects based on the input Smith charts. Among image classification-specialized CNN and Transformer models, the ConvNeXt model achieved the highest diagnostic performance with an accuracy of 89.4%. When diagnosing the corrosion using the Smith chart, it is possible to perform a non-destructive evaluation using electronic signals. Additionally, by integrating and visualizing signal magnitude and phase information, it is expected to perform an intuitive and noise-robust diagnosis.

Keywords Artificial intelligence, Cu interconnects, Corrosion, Non-destructive evaluation, Smith chart

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