journal article·2018-09-05Open access

Reliable Multivalued Conductance States in TaOxMemristors through Oxygen Plasma-Assisted Electrode Deposition with in Situ-Biased Conductance State Transmission Electron Microscopy Analysis

Myoung-Jae Lee, Gyeong-Su Park, David H. Seo, Sung Min Kwon, Hyeon-Jun Lee, June-Seo Kim, MinKyung Jung, Chun-Yeol You, Hyangsook Lee, Hee-Goo Kim, Su-Been Pang, Sunae Seo, Hyunsang Hwang, Sung Kyu Park

ACS Applied Materials & Interfaces· Volume 10· Issue 35

Abstract

Transition metal oxide-based memristors have widely been proposed for applications toward artificial synapses. In general, memristors have two or more electrically switchable stable resistance states that device researchers see as an analogue to the ion channels found in biological synapses. The mechanism behind resistive switching in metal oxides has been divided into electrochemical metallization models and valence change models. The stability of the resistance states in the memristor vary widely depending on: oxide material, electrode material, deposition conditions, film thickness, and programming conditions. So far, it has been extremely challenging to obtain reliable memristors with more than two stable multivalued states along with endurances greater than ∼1000 cycles for each of those states. Using an oxygen plasma-assisted sputter deposition method of noble metal electrodes, we found that the metal-oxide interface could be deposited with substantially lower interface roughness observable at the nanometer scale. This markedly improved device reliability and function, allowing for a demonstration of memristors with four completely distinct levels from ∼6 × 10–6 to ∼4 × 10–8 S that were tested up to 104 cycles per level. Furthermore through a unique in situ transmission electron microscopy study, we were able to verify a redox reaction-type model to be dominant in our samples, leading to the higher degree of electrical state controllability. For solid-state synapse applications, the improvements to electrical properties will lead to simple device structures, with an overall power and area reduction of at least 1000 times when compared to SRAM.
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

Department of Materials Science and Engineering, Seoul National University, Seoul 08826, Korea

School of Electrical and Electronic Engineering, Chung-Ang University, Seoul 06974, Korea

Samsung Advanced Institute of Technology, Samsung Electronics Co., Suwon 443-803, Korea

Department of Physics, Sejong University, Seoul 143-747, Korea

Department of Materials Science and Engineering, Pohang University of Science and Technology, Pohang 790-784, Korea

Funding

National Research Foundation of Korea · Ministry of Science, ICT and Future Planning

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