Selecting Device, In-Memory Search, and Monolithic 3D Integration of RRAMs and 2D Devices Towards High Reliability and High Efficiency: (Invited Paper)

Resistive random-access memories (RRAMs) are highly promising for high-density memory and energy-efficient inmemory computing. Towards the integration of RRAM arrays, the sneak path leakage and IR drop problem need to be alleviated and the memory density should be further enhanced. Here we develop the consistent RRAM model, demonstrate two-dimensional (2D) selectors and one-selector-one-selector (1S1R) memory cells, perform monolithic 3D integration of 2D transistors and vertical RRAMs (VRRAMs), and show the promise for in-memory search applications.

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Publication Details

Published
2025-03-09
DOI
https://doi.org/10.1109/edtm61175.2025.11041062
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00

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article

Selecting Device, In-Memory Search, and Monolithic 3D Integration of RRAMs and 2D Devices Towards High Reliability and High Efficiency: (Invited Paper)

Yueyang Jia, Yiyan Liu, Maosong Xie, Rui Yang et al.
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Advanced Memory and Neural Computing
article

Selecting Device, In-Memory Search, and Monolithic 3D Integration of RRAMs and 2D Devices Towards High Reliability and High Efficiency: (Invited Paper)

Yueyang Jia, Yiyan Liu, Maosong Xie, Rui Yang, Yijian Zhang, Minliang Shen
article en

Abstract

Resistive random-access memories (RRAMs) are highly promising for high-density memory and energy-efficient inmemory computing. Towards the integration of RRAM arrays, the sneak path leakage and IR drop problem need to be alleviated and the memory density should be further enhanced. Here we develop the consistent RRAM model, demonstrate two-dimensional (2D) selectors and one-selector-one-selector (1S1R) memory cells, perform monolithic 3D integration of 2D transistors and vertical RRAMs (VRRAMs), and show the promise for in-memory search applications.

Shanghai Jiao Tong University (CN)
National Natural Science Foundation of China, Science and Technology Commission of Shanghai Municipality, Natural Science Foundation of Chongqing
Openalex Percentile: Top 87%
Advanced Memory and Neural Computing
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