journal article·2025-04-02

Strategic Material Design for Highly Reliable QLC 3D V-NAND Using Bypass Resistive Random Access Memory

Geonhui Han, Jongseon Seo, Junghoon Park, Minji Hong, Juhyung Kim, Kilho Lee, Wanki Kim, Daewon Ha, Hyunsang Hwang

ACS Applied Materials & Interfaces· Volume 17· Issue 13
Publisher page

Abstract

To overcome the limitation of conventional flash memory, electrochemical random-access memory (ECRAM)-based bypass memory (bypass RRAM) has been proposed as a potential candidate for V-NAND memory application. While bypass RRAM demonstrates excellent memory characteristics through ion hopping conduction, the key parameters governing multilevel cell (MLC) operation remain unexplored. In this study, we propose design guidelines for bypass RRAM, targeting highly uniform quadruple-level cell (QLC) operation by using quantized oxygen vacancy (V o ) injections. To achieve the uniform QLC operation, we precisely controlled ion migration using material engineering in the bypass RRAM. By leveraging the unique electrical characteristic of the WO x resistive switching (RS) layer, we minimized V o migration (from WO 2.65 to WO 2.73 ), which enabled low-voltage operation (<5 V) and a significant on/off ratio (>10 6 ) with a minimal stoichiometry (Δ x < 0.08) change. Additionally, key parameters, such as ionic barrier ( E a,ion ) in the electrolyte layer and ion diffusivity ( D ion ) in the RS layer, were identified to achieve both a high on/off ratio and a uniform sensing margin based on MATLAB simulations and experimental results. As a result, optimized parameters led to superior QLC performance, featuring a highly uniform distribution (σ/μ ∼ 0.01) and a uniform sensing margin (Δ G ∼ 4 μS) between each state without read disturbance issues. Finally, we also confirmed that the substantial reduction of the V o migration at the nanometer scale suggests the potential for extending beyond QLC levels with quantized V o injection, ensuring highly uniform switching for V-NAND memory.
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Research context

OpenAlex topics: Advanced Memory and Neural Computing · Transition Metal Oxide Nanomaterials · ZnO doping and properties

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

Affiliations

Center for Single Atom-based Semiconductor Device and the Department of Materials Science and Engineering

Pohang University of Science and Technology

Samsung Electronics, Semiconductor R&D Center, Dongtangiheng-ro, Hwaseong-si, Gyeonggi-do 18479, Korea

Funding

Samsung

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