Charlotte Cui, Fereshteh Falah Chamasemani, Priya Paulachan, Rahulkumar Sinojiya, Jördis Rosc, Michael Reisinger, Peter Imrich, Walter Hartner, Roland Brunner
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引用次数: 0
Abstract
Reliable connections of electrical components embody a crucial topic in the microelectronics and power semiconductor industry. This study utilises 3D non-destructive X-ray tomography and specifically developed machine learning (ML-) algorithms to statistically investigate crack initiation and propagation in SAC305-Bi solder balls upon thermal cycling on board (TCoB). We quantitatively segment fatigue cracks and flux pores from 3D X-ray tomography data utilising a multi-level ML-workflow incorporating a 3D U-Net model. The data reveals that intergranular fatigue cracking is the predominant failure mechanism during TCoB and that dynamic recrystallisation precedes crack initiation. Moreover, we find that fatigue cracks are initiated at surface notches, flux pores and printed circuit board-metallisation intrusions. The work provides important insights regarding the underlying microstructural and mechanical mechanisms for recrystallisation and cracking, uniting the aspects of big-data analysis with ML-algorithms and in-depth understanding about the underlying materials science.
期刊介绍:
npj Materials Degradation considers basic and applied research that explores all aspects of the degradation of metallic and non-metallic materials. The journal broadly defines ‘materials degradation’ as a reduction in the ability of a material to perform its task in-service as a result of environmental exposure.
The journal covers a broad range of topics including but not limited to:
-Degradation of metals, glasses, minerals, polymers, ceramics, cements and composites in natural and engineered environments, as a result of various stimuli
-Computational and experimental studies of degradation mechanisms and kinetics
-Characterization of degradation by traditional and emerging techniques
-New approaches and technologies for enhancing resistance to degradation
-Inspection and monitoring techniques for materials in-service, such as sensing technologies