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Marco Rossi
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Proceedings Papers
ISTFA2024, ISTFA 2024: Tutorial Presentations from the 50th International Symposium for Testing and Failure Analysis, w1-w82, October 28–November 1, 2024,
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Presentation slides for the ISTFA 2024 Tutorial session “AI-Driven Advancements in Image Processing, Analysis and 3D Modeling for Fault Isolation and Failure Analysis.”
Proceedings Papers
ISTFA2024, ISTFA 2024: Conference Proceedings from the 50th International Symposium for Testing and Failure Analysis, 273-281, October 28–November 1, 2024,
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In semiconductor manufacturing, the process of laser dicing can result in a loss of yield due to defects associated to the laser interaction with the sample. These defects can be difficult to identify, especially before a proper tuning of the process. Traditional investigation methods, like infrared (IR) inspection and focused-ion beam scanning electron microscopy (FIB-SEM) analysis, are labor-intensive and lack comprehensive insights. Here, we propose a robust correlative microscopy (CM) workflow integrating IR, X-ray Microscopy (XRM), and FIB-SEM tomography analyses, leveraging artificial intelligence (AI) driven algorithm for time- and quality-improved dataset reconstruction, automatic segmentation and defect site identification. Our approach streamlines defect identification, preparation, and characterization. Through AI-enhanced methodologies, as well as femtosecond (fs) laser, we optimize investigation efficiency and extract crucial information about defects properties and evolution. Our research aims to advance semiconductor failure analysis by integrating AI for enhanced defect localization and high-quality 3D dataset acquisition in the realm of laser dicing processes.
Proceedings Papers
ISTFA2023, ISTFA 2023: Conference Proceedings from the 49th International Symposium for Testing and Failure Analysis, 92-100, November 12–16, 2023,
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Power MOSFETs are electronic devices that are commonly used as switches or amplifiers in power electronics applications such as motor control, audio amplifiers, power supplies and illumination systems. During the fabrication process, impurities such as copper can become incorporated into the device structure, giving rise to defects in crystal lattice and creating localized areas of high resistance or conductivity. In this work we present a multiscale and multimodal correlative microscopy workflow for the characterization of copper inclusions found in the epitaxial layer in power MOSFETs combining Light Microscopy (LM), non-destructive 3D X-ray Microscopy (XRM), Focused-Ion Beam Scanning Electron Microscopy (FIB-SEM) tomography coupled with Energy Dispersive X-ray Spectroscopy (EDX), and Transmission Electron Microscopy (TEM) coupled with Electron Energy Loss Spectroscopy (EELS). Thanks to this approach of correlating 2D and 3D morphological insights with chemical information, a comprehensive and multiscale understanding of copper segregations distribution and effects at the structural level of the power MOSFETs can be achieved.
Proceedings Papers
ISTFA2022, ISTFA 2022: Conference Proceedings from the 48th International Symposium for Testing and Failure Analysis, 201-205, October 30–November 3, 2022,
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In this work we present a new approach in physical failure analysis. Fault isolation can be done using volume diagnosis techniques. But when studying the identified defect sites by Focused Ion Beam (FIB) cross-sectioning, correct interpretation of the cross-sectional views strongly relies on choosing an appropriate cutting strategy. However, volume diagnosis techniques do not provide any information on which cutting directions and settings to choose to avoid misinterpretation of the spatial evolution of the defects. The proposed approach is to acquire FIB-SEM tomographic datasets at the defect sites to unequivocally characterize the defects in three-dimensional visualizations, independent of particular cross-sectioning strategies. In this specific case we have applied the methodology at a microcontroller for automotive applications on which a couple of floating VIAS were found. Thanks to the complete information obtained with the tomography, the defect could be assigned to a specific class of etching tools, and the root cause thus be solved.