Towards Artificial Intelligence Hardware With 3D Integrated Ferroelectric Transistors

cycles, and stable multilevel conductance states suitable for synaptic computing. Mapping device characteristics to a convolutional neural network (CNN) for Canadian Institute for Advanced Research (CIFAR-10) inference yields 95.0% (tier-2) and 95.5% (tier-4) accuracy, approaching the 96.1% software baseline. Analog-domain convolution was further demonstrated by encoding kernel weights into FeFET conductance states for edge-aware image processing. These results establish M3D-integrated FeFETs as a scalable and reliable platform for next-generation compute-in-memory and neuromorphic vision applications.