journal article·2025-08-12

Dual-Mode Functionality in Analog-Weight-Tunable TiOx-Based RRAM: Exploiting Optical and Electrical Stimuli for Synaptic Behaviors

Hyogeun Park, Hyojin So, Minsu Ko, Sungjun Kim, Sungjoon Kim

ACS Applied Electronic Materials· Volume 7· Issue 15
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Abstract

In this study, an RRAM with a crossbar array structure incorporating an oxygen-deficient TiO y layer on top of an oxygen-rich TiO x and Al 2 O 3 tunnel barrier was developed. The Ti top electrode underwent oxidation reactions with the oxygen-rich TiO x ( x = 1.78) layer, resulting in the formation of an oxygen-deficient TiO y layer. The TiO y /TiO x structure performed functions of switching and an oxygen reservoir, enhancing switching stability and inducing analog weight modulation effects, which further reduced the current level. The oxygen ion drift and diffusion effect of the proposed device led to conductance relaxation, which also means short-term memory (STM) properties. It demonstrated stable uniformity and endurance during DC sweep measurements, and the successful implementation of multilevel characteristics was achieved by using the time-dependent weight expression of the proposed device. Reservoir computing functions were executed through pulse measurements, enabling the realization of an MNIST pattern recognition system. Additionally, synaptic functionalities were emulated, successfully demonstrating the potential for neuromorphic computing system implementation. We also demonstrated dual-mode operation by simultaneously utilizing both electrical and optical stimulation, with optical stimulation emulating synaptic function.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced Memory and Neural Computing · Neuroscience and Neural Engineering · Ferroelectric and Negative Capacitance Devices

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Division of Electronics and Electrical Engineering

Dongguk University

Department of AI Semiconductor Engineering

Korea University

Funding

National Research Foundation of Korea · Korea Institute of Energy Technology Evaluation and Planning · Korea University

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