In semiconductor manufacturing, preparing ultra-thin, electron-transparent TEM lamellae is a critical step for failure analysis and process monitoring. Root-cause investigations increasingly require detailed characterization of nanometer-scale structures, defects, and complex thin-layer stacks. As device architecture grows more complex and dimensions shrink at advanced nodes, conventional operator-dependent workflows struggle to deliver the throughput and reproducibility required for nanoscale characterization. Discover how AI-driven automation on a Ga⁺ FIB-SEM platform enables unattended, reliable, high-throughput TEM sample preparation for multimodal STEM analysis of a 3-nm FinFET device.
