Ferroelectric Aluminum Scandium Nitride Transistors with Intrinsic Switching Characteristics and Artificial Synaptic Functions for Neuromorphic Computing.

Aluminum Scandium Nitride (Al1-xScxN) has received attention for its exceptional ferroelectric properties, whereas the fundamental mechanism determining its dynamic response and reliability remains elusive. In this work, an unreported nucleation-based polarization switching mechanism in Al0.7Sc0.3N (AlScN) is unveiled, driven by its intrinsic ferroelectricity rooted in the ionic displacement. Fast polarization switching, characterized by a remarkably low characteristic time of 0.00183 ps, is captured, and effectively simulated using a nucleation-limited switching (NLS) model, where the profound effect of defects on the nucleation and domain propagation is systematically studied. These findings are further integrated into Monte Carlo simulations to unravel the influence of the activation energy for ferroelectric switching on the distributions of switching thresholds. The long-term reliability of devices is also confirmed by time-dependent dielectric breakdown (TDDB) measurements, and the effect of thickness scaling is discussed. Ferroelectric field-effect transistors (FeFETs) are demonstrated through the integration of AlScN and 2D MoS2 channel, where biological synaptic functions can be emulated with optimized operation voltage. The artificial neural network built from AlScN-based FeFETs achieves 93.8% recognition accuracy of handwritten digits, demonstrating the potential of ferroelectric AlScN in future neuromorphic computing applications.

Demonstration of 10 nm Ferroelectric Al0.7Sc0.3N-Based Capacitors for Enabling Selector-Free Memory Array.

In this work, 10 nm scandium-doped aluminum nitride (AlScN) capacitors are demonstrated for the construction of the selector-free memory array application. The 10 nm Al0.7Sc0.3N film deposited on an 8-inch silicon wafer with sputtering technology exhibits a large remnant polarization exceeding 100 µC/cm2 and a tight distribution of the coercive field, which is characterized by the positive-up-negative-down (PUND) method. As a result, the devices with lateral dimension of only 1.5 µm show a large memory window of over 250% and a low power consumption of ~40 pJ while maintaining a low disturbance rate of <2%. Additionally, the devices demonstrate stable multistate memory characteristics with a dedicated operation scheme. The back-end-of-line (BEOL)-compatible fabrication process, along with all these device performances, shows the potential of AlScN-based capacitors for the implementation of the high-density selector-free memory array.