Issue 3, 2024

Magnetic-ferroelectric synergic control of multilevel conducting states in van der Waals multiferroic tunnel junctions towards in-memory computing

Abstract

van der Waals (vdW) multiferroic tunnel junctions (MFTJs) based on two-dimensional materials have gained significant interest due to their potential applications in next-generation data storage and in-memory computing devices. In this study, we construct vdW MFTJs by employing monolayer Mn2Se3 as the spin-filter tunnel barrier, TiTe2 as the electrodes and In2S3 as the tunnel barrier to investigate the spin transport properties based on first-principles quantum transport calculations. It is highlighted that apparent tunneling magnetoresistance (TMR) and tunneling electroresistance (TER) effects with a maximum TMR ratio of 6237% and TER ratio of 1771% can be realized by using bilayer In2S3 as the tunnel barrier under finite bias. Furthermore, the physical origin of the distinguished TMR and TER effects is unraveled from the k||-resolved transmission spectra and spin-dependent projected local density of states analysis. Interestingly, four distinguishable conductance states reveal the implementation of four-state nonvolatile data storage using one MFTJ unit. More importantly, in-memory logic computing and multilevel data storage can be achieved at the same time by magnetic switching and electrical control, respectively. These results shed light on vdW MFTJs in the applications of in-memory computing as well as multilevel data storage devices.

Graphical abstract: Magnetic-ferroelectric synergic control of multilevel conducting states in van der Waals multiferroic tunnel junctions towards in-memory computing

Supplementary files

Article information

Article type
Paper
Submitted
19 ستمبر 2023
Accepted
02 دسمبر 2023
First published
05 دسمبر 2023

Nanoscale, 2024,16, 1331-1344

Magnetic-ferroelectric synergic control of multilevel conducting states in van der Waals multiferroic tunnel junctions towards in-memory computing

Z. Cui, B. Sa, K. Xue, Y. Zhang, R. Xiong, C. Wen, X. Miao and Z. Sun, Nanoscale, 2024, 16, 1331 DOI: 10.1039/D3NR04712A

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