Non-Destructive Analysis of Intergranular Fatigue Cracking in SAC305-Bi Solder Balls

In a recent paper published in the journal NPJ Materials Degradation, researchers proposed an innovative approach to analyze the degradation mechanisms of lead (Pb)-free solder balls in microelectronics, utilizing X-ray tomography combined with machine learning (ML) algorithms. Their investigation uncovered intergranular fatigue cracking as the primary failure mode during thermal cycling, with dynamic recrystallization occurring prior to crack initiation.

a Rendered X-ray tomography image of the entire BGA with the chip (blue), the PCB (brown) and the solder balls (yellow). b X-ray tomography slice image of the BGA from the reconstructed three-dimensional raw data, for the x-y- (bird view), x-z- (cross-section 1) and y-z- (cross-section 2) planes. The locations of the cross-sections 1 and 2 are indicated by view A-A (red dashed line) and view B-B (green dashed line), respectively. For the location of the bird view a blue dashed line (0-0) is shown in cross-section (view A-A and view B-B). c Correlated cross-sectional X-ray tomography and FESEM EBSD maps for SAC305 with 0 wt.% Bi, 1.1 wt.% Bi and 1.9 wt.% Bi, respectively, are presented. Grain orientation data from the FESEM EBSD characterization is projected on the X-ray tomography data. The illustrated X-ray tomography cross-sections correspond to the view A-A. Image Credit: https://www.nature.com/articles/s41529-024-00456-8
a Rendered X-ray tomography image of the entire BGA with the chip (blue), the PCB (brown) and the solder balls (yellow). b X-ray tomography slice image of the BGA from the reconstructed three-dimensional raw data, for the x-y- (bird view), x-z- (cross-section 1) and y-z- (cross-section 2) planes. The locations of the cross-sections 1 and 2 are indicated by view A-A (red dashed line) and view B-B (green dashed line), respectively. For the location of the bird view a blue dashed line (0-0) is shown in cross-section (view A-A and view B-B). c Correlated cross-sectional X-ray tomography and FESEM EBSD maps for SAC305 with 0 wt.% Bi, 1.1 wt.% Bi and 1.9 wt.% Bi, respectively, are presented. Grain orientation data from the FESEM EBSD characterization is projected on the X-ray tomography data. The illustrated X-ray tomography cross-sections correspond to the view A-A. Image Credit: https://www.nature.com/articles/s41529-024-00456-8

Background

Solder balls play a crucial role in microelectronics and power semiconductor devices, facilitating both electrical and thermal connections between the chip and the printed circuit board (PCB). However, they are prone to degradation due to thermal and mechanical stresses resulting from coefficient of thermal expansion (CTE) mismatches among different materials in the device. These stresses can lead to microstructural changes such as recrystallization and grain boundary formation, as well as the formation of cracks and pores in the solder material, affecting its functionality and lifespan.

To address environmental and health concerns associated with Pb based solder alloys, tin (Sn) based alternatives like Sn - 3.0 wt.% silver (Ag) - 0.5 wt.% copper (Cu) (SAC305) has been widely adopted. However, SAC305 solder balls may undergo microstructural degradation even after reflowing due to flux pore formation and the low hardness of the beta-Sn (β-Sn) matrix. Hence, the addition of bismuth (Bi) as an alloying element has emerged as a promising strategy to enhance the thermo-mechanical stability of SAC305 solder balls.

About the Research

In the present paper, the authors conducted a comprehensive investigation into the effect of Bi content on the microstructural and mechanical properties of Pb free Sn-Ag-Cu-305 (SAC305) solder balls, correlating them with fatigue behavior during thermal cycling on board (TCoB). They employed three SAC305-Bi solder alloys with varying Bi contents (0, 1.1, and 1.9 wt.%) and subjected them to extended thermal cycling on board (TCoB) in ambient atmosphere conditions.

The solder balls were placed between the chip and the PCB, forming a ball grid array (BGA) package. Utilizing X-ray tomography, the study non-destructively imaged the entire BGA package in 3D to visualize degradation features such as flux pores and fatigue cracks within the solder balls.

To analyze the large amount of X-ray tomography data, the researchers devised an ML-based image processing workflow comprising localization and segmentation steps. The localization step employed a binary convolutional neural network (CNN) to detect solder ball positions in the X-ray tomography data.

Subsequently, the segmentation step utilized both two dimensional (2D) and three dimensional (3D) u-shaped CNN (U-Net) models to segment morphological features including metallization, cracks, and pores within each solder ball. The 3D U-Net model was trained using manually refined labels derived from the 2D U-Net model. This ML-based image processing workflow enabled fully automated, non-destructive 3D failure analysis of the entire BGA package, facilitating statistical analysis of solder ball properties.

Research Findings

The outcomes revealed intergranular fatigue cracking as the primary degradation mechanism in solder balls during TCoB, preceded by dynamic recrystallization. The initiation of fatigue cracks occurred at three types of notches: surface notches, flux pores, and PCB-metallization intrusions.

Correlation between X-ray tomography data and microstructural features in the solder balls was achieved using field emission scanning electron microscopy (FESEM) and electron backscatter diffraction (EBSD). EBSD maps illustrated grain refinement in initially single- or few-grained solder balls near highly strained interfaces, where shear strain predominated, with the resulting new grain boundaries serving as favored crack propagation sites.

Recrystallized areas were predominantly concentrated near surface notches and PCB-metallization intrusions, coinciding with stress concentrations simulated by finite element method (FEM) modeling. Energy dispersive X-ray spectroscopy (EDX) analysis on grain boundaries revealed copper enrichment, potentially promoting intergranular fatigue cracking.

Furthermore, the study investigated the influence of Bi content on microstructural and fatigue properties of solder balls. Bi addition to the SAC305 alloy enhanced fatigue resistance by delaying recrystallization and reinforcing grain boundaries. Bi was confirmed to be soluble in the β-Sn matrix, acting as a solid solution strengthener and increasing yield stress. Bi-containing solder balls exhibited less pronounced recrystallization fronts and smaller, less gaping intergranular cracks compared to Bi-free solder balls.

Additionally, a statistical analysis of crack volume and its correlation with various solder ball properties, including flux pore volume, distance from the BGA center, and PCB-geometry factor, was performed. The researchers revealed a decrease in crack volume with increasing Bi content, with flux pores and PCB-metallization intrusions significantly influencing crack initiation and propagation.

Applications

The research has several applications, including the development of more sustainable and reliable lead-free solder alloys with improved fatigue resistance and reduced microstructural degradation. It also involves the optimization of solder ball geometry and BGA layout to minimize stress concentrations and notch effects in solder balls during TCoB. Additionally, the implementation of the ML-based image processing workflow serves as a quality and reliability control method for fast identification of poorly fatigued solder balls in microelectronics devices.

Conclusion

In conclusion, the study introduced a novel method for analyzing the degradation of Pb-free solder balls in microelectronics. This method enabled non-destructive, 3D, and statistical characterization of the entire BGA package and correlated the microstructural and mechanical properties of the solder balls with their fatigue behavior during TCoB. The findings revealed that intergranular fatigue cracking is the predominant failure mechanism in SAC305 solder balls, and that dynamic recrystallization precedes crack initiation. Moreover, the study demonstrated that the addition of bismuth to the SAC305 alloy improves its fatigue resistance by delaying recrystallization and strengthening the grain boundaries.

Journal reference:
Muhammad Osama

Written by

Muhammad Osama

Muhammad Osama is a full-time data analytics consultant and freelance technical writer based in Delhi, India. He specializes in transforming complex technical concepts into accessible content. He has a Bachelor of Technology in Mechanical Engineering with specialization in AI & Robotics from Galgotias University, India, and he has extensive experience in technical content writing, data science and analytics, and artificial intelligence.

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Osama, Muhammad. (2024, April 30). Non-Destructive Analysis of Intergranular Fatigue Cracking in SAC305-Bi Solder Balls. AZoAi. Retrieved on May 21, 2024 from https://www.azoai.com/news/20240430/Non-Destructive-Analysis-of-Intergranular-Fatigue-Cracking-in-SAC305-Bi-Solder-Balls.aspx.

  • MLA

    Osama, Muhammad. "Non-Destructive Analysis of Intergranular Fatigue Cracking in SAC305-Bi Solder Balls". AZoAi. 21 May 2024. <https://www.azoai.com/news/20240430/Non-Destructive-Analysis-of-Intergranular-Fatigue-Cracking-in-SAC305-Bi-Solder-Balls.aspx>.

  • Chicago

    Osama, Muhammad. "Non-Destructive Analysis of Intergranular Fatigue Cracking in SAC305-Bi Solder Balls". AZoAi. https://www.azoai.com/news/20240430/Non-Destructive-Analysis-of-Intergranular-Fatigue-Cracking-in-SAC305-Bi-Solder-Balls.aspx. (accessed May 21, 2024).

  • Harvard

    Osama, Muhammad. 2024. Non-Destructive Analysis of Intergranular Fatigue Cracking in SAC305-Bi Solder Balls. AZoAi, viewed 21 May 2024, https://www.azoai.com/news/20240430/Non-Destructive-Analysis-of-Intergranular-Fatigue-Cracking-in-SAC305-Bi-Solder-Balls.aspx.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of AZoAi.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
Machine Learning Tames Chaos on Edge Devices