Key points are not available for this paper at this time.
Abstract Low‐current multilevel programmability with inherent non‐volatility and high stability of resistance states is required for both multi‐bit memory storage and deep learning accelerators but is difficult to achieve. Here, in a resistive switching system, this work realizes >512 (>9 bits) distinct non‐volatile conductance levels with stable retention for each state with current levels down to the nanoampere range, highly promising for potential integration with small processing nodes with ultra‐low power consumption requirements. This is achieved by demonstrating a new thin film design concept that encompasses three key features: an ultra‐thin epitaxial oxygen ionic switching layer that provides a tunable energy barrier at the bottom electrode, an overcoat amorphous layer that acts as an ion migration barrier for stable state retention, and a partial conductive filament as a localized electronic transport channel to the epitaxial switching layer. A large dynamic resistance range of up to seven orders of magnitude is achieved with reset‐free transitions among intermediate states, and programmability is demonstrated with ultra‐fast (20 ns) pulses. Artificial neural network (ANN) simulations, based on the experimental performance and its non‐idealities, demonstrate close‐to‐ideal inference accuracies for various Modified National Institute of Standards and Technology (MNIST) data sets.
Xiao et al. (Tue,) studied this question.