Skyrmion-mediated nonvolatile ternary memory.

Autor: Rajib MM; Department of Mechanical and Nuclear Engineering, Virginia Commonwealth University, Richmond, VA, 23284, USA., Bindal N; Department of Electronics and Communication Engineering, Indian Institute of Technology Roorkee, Roorkee, 247667, Uttarakhand, India.; Department of Electronics and Communication Engineering, MVJ College of Engineering, Bangalore, 560067, India., Raj RK; Department of Electronics and Communication Engineering, Indian Institute of Technology Roorkee, Roorkee, 247667, Uttarakhand, India., Kaushik BK; Department of Electronics and Communication Engineering, Indian Institute of Technology Roorkee, Roorkee, 247667, Uttarakhand, India., Atulasimha J; Department of Mechanical and Nuclear Engineering, Virginia Commonwealth University, Richmond, VA, 23284, USA. jatulasimha@vcu.edu.; Department of Electrical and Computer Engineering, Virginia Commonwealth University, Richmond, VA, 23284, USA. jatulasimha@vcu.edu.
Jazyk: angličtina
Zdroj: Scientific reports [Sci Rep] 2024 Jul 26; Vol. 14 (1), pp. 17199. Date of Electronic Publication: 2024 Jul 26.
DOI: 10.1038/s41598-024-66853-w
Abstrakt: Multistate memory systems have the ability to store and process more data in the same physical space as binary memory systems, making them a potential alternative to existing binary memory systems. In the past, it has been demonstrated that voltage-controlled magnetic anisotropy (VCMA) based writing is highly energy-efficient compared to other writing methods used in non-volatile nano-magnetic binary memory systems. In this study, we introduce a new, VCMA-based and skyrmion-mediated non-volatile ternary memory system using a perpendicular magnetic tunnel junction (p-MTJ) in the presence of room temperature thermal perturbation. We have also shown that ternary states {- 1, 0, + 1} can be implemented with three magnetoresistance values obtained from a p-MTJ corresponding to ferromagnetic up, down, and skyrmion state, with 99% switching probability in the presence of room temperature thermal noise in an energy-efficient way, requiring ~ 2 fJ energy on an average for each switching operation. Additionally, we show that our proposed ternary memory demonstrates an improvement in area and energy by at least 2X and ~ 10 4 X respectively, compared to state-of-the-art spin-transfer torque (STT)-based non-volatile magnetic multistate memories. Furthermore, these three states can be potentially utilized for energy-efficient, high-density in-memory quantized deep neural network implementation.
(© 2024. The Author(s).)
Databáze: MEDLINE
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