AI datacenters are ultimately giant computing factories. CPUs coordinate workloads, GPUs perform the massive parallel calculations required for AI model training and inference, and DRAM continuously feeds data to these processors. As AI models become larger and more complex, faster, more energy-efficient computing architectures and 3D memory structures are needed.
To enhance device performance, semiconductor manufacturers are increasingly incorporating germanium-based materials into next-generation transistor architectures and advanced 3D memory devices. Germanium's high carrier mobility enables faster switching while reducing power consumption. In addition, sacrificial germanium layers are a key enabler for the fabrication of future transistor nodes and emerging 3D DRAM architectures.
