High efficiency giant magnetoresistive device based on two-dimensional MXene (Mn₂NO₂)

Abstract

Due to the unique electronic structure of half-metals, characterized by the conductivity of majority-spin and the band gap of minority-spin, these materials have emerged as suitable alternatives for the design of efficient giant magnetoresistive (GMR) devices. Based on the first-principles calculations, an excellent GMR device has been designed by using two-dimensional (2D) half-metal Mn₂NO₂. The results show that Mn₂NO₂ has sandwiched between the Au/nMn₂NO₂ (n = 1, 2, 3)/Au heterojunction and maintains its half-metallic properties. Due to the half-metallic characteristics of Mn₂NO₂, the total current of the monolayer device can reach up to 1500 nA in the ferromagnetic state. At low voltage, the maximum GMR is observed to be 1.15 × 10³¹ %. Further, by increasing the number of layers, the ultra-high GMR at low voltage is still maintained. The developed device is a spintronic device exhibiting the highest magnetoresistive ratio reported theoretically so far. Simultaneously, a significant negative differential resistance (NDR) effect is also observed in the heterojunction. Owing to its excellent half-metallic properties and 2D structure, Mn₂NO₂ is an ideal energy-saving GMR material.

Graphical abstract

Keywords

half-metals / Mn₂NO₂ / giant magnetoresistive

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Electronic supplementary materials

are available in the online version of this article at https://doi.org/10.1007/s11467-022-1184-z and https://journal.hep.com.cn/fop/EN/10.1007/s11467-022-1184-z and are accessible for authorized users.

Acknowledgements

The authors would like to thank the National Natural Science Foundation of China (Grant Nos. 11704291 and 51875417), Hubei Province Key Laboratory of Systems Science in Metallurgical Process (Wuhan University of Science and Technology) (No. Y202101), and Key Laboratory of Nanodevices and Applications, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences (No. 21YZ03). The work was supported by High-Performance Computing Center of Wuhan University of Science and Technology. We thank ShiXiao Wen from HZWTECH for help and discussions regarding this study.

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