Experimental measurement of ungated channel region conductance in a multi-terminal, metal oxide-based ECRAM. (13th October 2021)

• Record Type: Journal Article
• Authors: Kwak, Hyunjeong; Lee, Chuljun; Lee, Chaeun; Noh, Kyungmi; Kim, Seyoung
• Is Part Of: Semiconductor science and technology. Volume 36:Number 11(2021)
• Publication Date: 2021-10-13
• Subjects: neuromorphic device -- memristor -- resistive switching -- ECRAM; Semiconductors -- Periodicals; 621.38152
• DOI: 10.1088/1361-6641/ac25c8
• Languages: English
• ISSNs: 0268-1242

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 WO3 -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.