(Invited) Impact of Polarization Variation on Ferroelectric Field-Effect Transistor and Compute-in-Memory

Abstract

The discovery of Hafnia-based ferroelectric materials made ferroelectric field-effect transistor (FeFET) a promising nonvolatile memory device and enables aggressive scaling down. However, the ferroelectric layer possesses polarization variation (PV) induced by its crystallinity, whereby FeFET suffers from performance variation. Hence, it is critical to assess its influence quantitatively to utilize the FeFET for storage or compute-in-memory applications. In this review, recent trends and progress of the performance variation on the FeFETs are surveyed. We present the impact of PV on three-dimensional (3D) FeFETs. In addition, to show its capability for compute-in-memory application, the inference accuracy is discussed under the structures. Next, the Voronoi diagram is introduced to model the different sizes and shapes of ferroelectric grains. A comparative study of the device variability with other sources is investigated under different technology nodes. Finally, a machine learning-aided methodology to analyze the variability of FeFET based on the metrology data is proposed.