Experimental measurement of ungated channel region conductance in a multi-terminal, metal oxide-based ECRAM

Abstract

Abstract Due to the rapid progress of artificial intelligence technology based on neural networks, the amount of required computation has been increasing dramatically. To keep up with the ever-increasing demand, novel analog neuromorphic computing architectures have been intensively studied, where cross-point arrays of resistive memory devices are utilized for high-speed and power-efficient computation. Among various synaptic memory device candidates, a metal oxide-based electrochemical random-access memory (MO-ECRAM) has been attractive due to its complementary metal-oxide-semiconductor-compatibility and superior programmability. In this work, we fabricate a WO 3 -based MO-ECRAM with multiple terminals and characterize the conductance modulation in the channel regions with and without the gate stack. While the gated region conductance shows a high on/off ratio, the ungated region conductance displays weak modulation with a near-unity on/off ratio. Based on our experimental observation, we propose a lithographical technique to intentionally uncover the channel area and utilize the ungated area’s resistance to limit the maximum conductance of each cross-point element at the individual device level. We conduct a neural network training simulation for MNIST dataset and show that this technique can guarantee robust large array operations for high-performance neural network computation.