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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Petrov, R. H. | Madrid |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Zhang, Guoqi
Delft University of Technology
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (20/20 displayed)
- 2024Training Convolutional Neural Networks with Confocal Scanning Acoustic Microscopy Imaging for Power QFN Package Delamination Classification
- 2023Heterogeneous Integration of Diamond Heat Spreaders for Power Electronics Applicationcitations
- 2022Patterning of fine-features in nanoporous films synthesized by spark ablationcitations
- 2021Facile synthesis of ag nanowire/tio2 and ag nanowire/tio2/go nanocomposites for photocatalytic degradation of rhodamine bcitations
- 2020Vertically-Aligned Multi-Walled Carbon Nano Tube Pillars with Various Diameters under Compressioncitations
- 2020Toward a Self-Sensing Piezoresistive Pressure Sensor for all-SiC Monolithic Integrationcitations
- 2018Effects of Conformal Nanoscale Coatings on Thermal Performance of Vertically Aligned Carbon Nanotubescitations
- 2018Wafer Level Through Polymer Optical Vias (TPOV) Enabling High Throughput of Optical Windows Manufacturing
- 20163D interconnect technology based on low temperature copper nanoparticle sinteringcitations
- 2015An overview of scanning acoustic microscope, a reliable method for non-destructive failure analysis of microelectronic componentscitations
- 2010Theory of aluminum metallization corrosion in microelectronics
- 2009Reliability of Wafer Level Thin Film MEMS Packages during Wafer Backgrinding
- 2008Effect of aging of packaging materials on die surface cracking of a SiP carrier
- 2008Die Fracture Probability Prediction and Design Guidelines for Laminate-Based Over-Molded Packages
- 2007Modeling of the mechanical stiffness of the GaP/GaAs nanowires with point defects/stacking faults
- 2007Correlation between chemistry of polymer building blocks and microelectronics reliability
- 2007Effect of filler concentration of rubbery shear and bulk modulus of molding compounds
- 2007Micro-mechanical testing of SiLK by nanoindentation and substrate curvature techniques
- 2007Characterization of moisture properties of polymers for IC packaging
- 2005State-of-the-Art of Thermo-Mechanical Characterization of Thin Polymer Films
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document
Training Convolutional Neural Networks with Confocal Scanning Acoustic Microscopy Imaging for Power QFN Package Delamination Classification
Abstract
This study introduces a training protocol utilizing Convolutional Neural Networks (CNNs) and Confocal Scanning Acoustic Microscopy (CSAM) imaging techniques to classify Power Quad Flat No-leads (PQFN) package delamination. The investigation involves empty PQFN packages with varied substrate metallizations subjected to thermal cycling. Four delamination classes were labeled: Die-pad delamination (Class-A), Bond-pad delamination (Class-B), both Die-pad and Bond-pad delamination (Class-C), and No delamination (Class-D). Due to data imbalance, additional randomness was introduced for distribution balancing. Residual Networks (ResNet-18) based CNN model was selected for classification. Five-fold cross-validation assessed overfitting performance concerning input data size, image resolution, and batch size. The ResNet-18 prediction performance was evaluated using precision and recall metrics, with the model achieving average precision and recall scores of 0.86/1 and 0.83/1, respectively. Additionally, a comparison of delamination among different substrate metallizations was presented with Ag and NiPdAu indicating significant delamination compared to bare Cu substrate. This study pioneers the integration of CNNs with CSAM imaging for package defect detection and classification, laying the groundwork for future research to address the complex interplay of multiple failure mechanisms in functional packages.