Wafer-level chip-scale package lead-free solder fatigue: A critical review

Arriola, Emmanuel; Ubando, Aristotle T.; Gonzaga, Jeremias A.; Lee, Chang‐Chun

doi:10.1016/j.engfailanal.2022.106986

Cited by 13 publications

(6 citation statements)

References 70 publications

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“…After the thermomechanical process, the microstructures of the samples were characterized through nanoindentation mapping equipped with a nano-positioning module. It should be noted that the solder bump at the corner site of the assembly, as the most vulnerable part, 33 was considered for this experiment. Nanoindentation testing (NanoTest Vantage) was conducted on a surface at the center of solder bumps with windows of 100 μm × 100 μm by a diamond Berkovich tip.…”

Section: Methodsmentioning

confidence: 99%

A Micromechanical Data-Driven Machine-Learning Approach for Microstructural Characterization of Solder Balls in Electronic Packages Subjected to Thermomechanical Fatigue

Kurniawan

Sayed

Luna

et al. 2023

J. Electron. Mater.

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A combination of nanoindentation mapping and machine-earning (ML) modeling has been used to characterize the micro-structural changes in SnPb solder balls exposed to thermal cycling. The model facilitated the microstructural evaluation of solder bumps through the prediction of microscale variations of Young's modulus in the joint zone. The outcomes revealed that the micromechanical data-driven ML model precisely classified the microstructural constituents, i.e., β-Sn and α-Pb, along with the grain boundary (GB) regions. However, some deviations were observed in GB recognition, when the elastic modulus gradient was not sharp enough. The predictive results also revealed that the increase in number of thermal cycles led to stiffening and grain coarsening of α-Pb, while the β-Sn matrix mainly remained stable. Moreover, it was found that the thermal cycling intensified structural heterogeneity in the solder and sharpened the elastic modulus variations at the GB regions. In summary, the outcomes of this study demonstrate the prediction possibility of microstructural features in SnPb solder balls with a predefined thermal cycle numbers, and unfolded the relationship between morphological characteristics and microscale mechanical properties.

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Section: Methodsmentioning

confidence: 99%

A Micromechanical Data-Driven Machine-Learning Approach for Microstructural Characterization of Solder Balls in Electronic Packages Subjected to Thermomechanical Fatigue

Kurniawan

Sayed

Luna

et al. 2023

J. Electron. Mater.

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“…With the rapid development of microelectronics packaging technology, to improve the integration and reduce the size of devices, the surface mount technology (SMT) assembly, new chip scale packaging (CSP), ball grid array (BGA), and multi-chip module (MCM) packaging technologies are widely used to directly realize the electrical and mechanical connection between different materials through solder joint interconnection, which will inevitably produce stress concentration and dramatically increase its strain level [5]. The coefficient of thermal expansion (CTE) of different materials between layers is different, which will inevitably lead to thermal failure, as shown in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

“…Materials 2024, 17, x FOR PEER REVIEW 2 of 15 (MCM) packaging technologies are widely used to directly realize the electrical and mechanical connection between different materials through solder joint interconnection, which will inevitably produce stress concentration and dramatically increase its strain level [5]. The coefficient of thermal expansion (CTE) of different materials between layers is different, which will inevitably lead to thermal failure, as shown in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

Thermal Fatigue Failure of Micro-Solder Joints in Electronic Packaging Devices: A Review

Li,

Du,

Chen

et al. 2024

Materials

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In electronic packaging products in the service process, the solder joints experience thermal fatigue due to temperature cycles, which have a significant influence on the performance of electronic products and the reliability of solder joints. In this paper, the thermal fatigue failure mechanism of solder joints in microelectronic packages, the microstructure changes of the thermal fatigue process, the influence factors on the joint fatigue life, and the simulation analysis and forecasting of thermal fatigue life are reviewed. The results show that the solder joints are heterogeneously coarsened, and this leads to fatigue cracks occurring under the elevated high-temperature phase of alternating temperature cycles. However, the thickness of the solder and the hold time in the high-temperature phase do not significantly influence the thermal fatigue. The coarsened region and the IMC layer thicken with the number of cycles, and the cracks initiate and propagate along the interface between the intermetallic compound (IMC) layer and coarsened region, eventually leading to solder joint failure. For lead-containing and lead-free solders, the lead-containing solder shows a faster fatigue crack growth rate and propagates by transgranular mode. Temperature and frequency affect the thermal fatigue life of solder joints to different degrees, and the fatigue lifetime of solder joints can be predicted through a variety of methods and simulated crack trajectories, but also through the use of a unified constitutive model and finite element analysis for prediction.

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“…Over the past decades, the electronics industry has witnessed a rapid evolution toward smaller and more complex devices, leading to increased demands on the reliability and durability of solder joints (Bani Hani et al, 2023a;Arriola et al, 2022;Samavatian et al, 2020aSamavatian et al, , 2022aXiong et al, 2023). One of the significant challenges faced by electronic instruments is lowcycle fatigue (LCF) in solder joints, which has emerged as a critical failure mechanism (Wei et al, 2023b).…”

Section: Introductionmentioning

confidence: 99%

Low-cycle fatigue life assessment of SAC solder alloy through a FEM-data driven machine learning approach

Ruiz-Jacinto,

Gutiérrez-Valverde,

Aslla-Quispe

et al. 2023

SSMT

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Purpose This paper aims to present the novel stacked machine learning approach (SMLA) to estimate low-cycle fatigue (LCF) life of SAC305 solder across structural parts. Using the finite element simulation (FEM) and continuous damage mechanics (CDM) model, a fatigue life database is built. The stacked machine learning (ML) model's iterative optimization during training enables precise fatigue predictions (2.41% root mean square error [RMSE], R2 = 0.975) for diverse structural components. Outliers are found in regression analysis, indicating potential overestimation for thickness transition specimens with extended lifetimes and underestimation for open-hole specimens. Correlations between fatigue life, stress factors, nominal stress and temperature are unveiled, enriching comprehension of LCF, thus enhancing solder behavior predictions. Design/methodology/approach This paper introduces stacked ML as a novel approach for estimating LCF life of SAC305 solder in various structural parts. It builds a fatigue life database using FEM and CDM model. The stacked ML model iteratively optimizes its structure, yielding accurate fatigue predictions (2.41% RMSE, R2 = 0.975). Outliers are observed: overestimation for thickness transition specimens and underestimation for open-hole ones. Correlations between fatigue life, stress factors, nominal stress and temperature enhance predictions, deepening understanding of solder behavior. Findings The findings of this paper highlight the successful application of the SMLA in accurately estimating the LCF life of SAC305 solder across diverse structural components. The stacked ML model, trained iteratively, demonstrates its effectiveness by producing precise fatigue lifetime predictions with a RMSE of 2.41% and an “R2” value of 0.975. The study also identifies distinct outlier behaviors associated with different structural parts: overestimations for thickness transition specimens with extended fatigue lifetimes and underestimations for open-hole specimens. The research further establishes correlations between fatigue life, stress concentration factors, nominal stress and temperature, enriching the understanding of solder behavior prediction. Originality/value The authors confirm the originality of this paper.

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Wafer-level chip-scale package lead-free solder fatigue: A critical review

Cited by 13 publications

References 70 publications

A Micromechanical Data-Driven Machine-Learning Approach for Microstructural Characterization of Solder Balls in Electronic Packages Subjected to Thermomechanical Fatigue

A Micromechanical Data-Driven Machine-Learning Approach for Microstructural Characterization of Solder Balls in Electronic Packages Subjected to Thermomechanical Fatigue

Thermal Fatigue Failure of Micro-Solder Joints in Electronic Packaging Devices: A Review

Low-cycle fatigue life assessment of SAC solder alloy through a FEM-data driven machine learning approach

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