Assessing Electronics with Advanced 3D X-ray Microscopy Techniques

This webinar discusses new methods and techniques that use 3D X-ray microscopy (XRM), nanoscale imaging, and deep learning (DL) to visualize the internal structures and assemblies of electronic devices, e.g., ball grid array components (BGAs), column grid arrays, solder connections, underfill/staking, etc. 
 
Key discussions include: 
•    Deep Learning Algorithms: These improve the quality of scans by enhancing contrast and reducing noise. 
•    DeepScout Tool: This tool uses 3D XRM scans from specific areas to train a neural network, allowing for high-resolution images to be created from lower-resolution data over a larger area. 
 
These methods can be used independently or complementary to other multiscale correlative microscopy evaluations, e.g., electron microscopy. They provide valuable insights into electronic packages and integrated circuits, revealing details from large features (hundreds of mm) to microscopic details in electronic components (tens of nm). By using X-ray imaging and machine learning, along with other imaging methods, we can speed up development time, reduce costs, and simplify failure analysis (FA) and quality inspection of printed circuit boards (PCBs) and electronic devices assembled with new emerging technologies.