Leveraging Automation of TEM Sample Preparation for Increased Throughput and Reproducible Results from Advanced Multimodal STEM Analysis of 3-nm FinFET Transistors
Leveraging Automation of TEM Sample Preparation for Increased Throughput and Reproducible Results from Advanced Multimodal STEM Analysis of 3-nm FinFET Transistors
Monday, November 17, 2025: 10:20 AM
1 (Pasadena Convention Center)
Summary:
Semiconductor manufacturers aim to enhance production yields and develop next-generation technologies, requiring advanced failure analysis of nanometer-sized structures. Transmission Electron Microscopy (TEM) is critical for this, necessitating precise preparation of ultra-thin, artifact-free samples. The increasing complexity of devices has driven demand for automated, high-quality TEM sample preparation. Addressing this, the AI-powered TEM AutoPrep™ Pro software, integrated with the SOLARIS 2 Ga FIB-SEM platform, automates all preparation steps—from trench milling to final low keV polishing—ensuring accurate region targeting via AI fiducial recognition. In a case study on Apple’s 3-nm A17 Pro SoC, four consistent TEM samples were prepared, showcasing the system’s ability to isolate and reveal FinFET architecture and materials. Analytical STEM and EDS confirmed the elemental structure, including titanium-filled gates and a novel ruthenium layer. Further testing on silicon samples showed a 96% success rate and ±10 nm thickness variation across 30 samples. Automation reduced operator time by 40%, improving throughput and overnight usage efficiency of FIB-SEM instruments.
Semiconductor manufacturers aim to enhance production yields and develop next-generation technologies, requiring advanced failure analysis of nanometer-sized structures. Transmission Electron Microscopy (TEM) is critical for this, necessitating precise preparation of ultra-thin, artifact-free samples. The increasing complexity of devices has driven demand for automated, high-quality TEM sample preparation. Addressing this, the AI-powered TEM AutoPrep™ Pro software, integrated with the SOLARIS 2 Ga FIB-SEM platform, automates all preparation steps—from trench milling to final low keV polishing—ensuring accurate region targeting via AI fiducial recognition. In a case study on Apple’s 3-nm A17 Pro SoC, four consistent TEM samples were prepared, showcasing the system’s ability to isolate and reveal FinFET architecture and materials. Analytical STEM and EDS confirmed the elemental structure, including titanium-filled gates and a novel ruthenium layer. Further testing on silicon samples showed a 96% success rate and ±10 nm thickness variation across 30 samples. Automation reduced operator time by 40%, improving throughput and overnight usage efficiency of FIB-SEM instruments.