Photoresponsive Two-Dimensional Magnetic Junctions for Reconfigurable In-Memory Sensing

Magnetic tunneling junctions (MTJs) lie in the core of magnetic random access memory, holding promise in integrating memory and computing to reduce hardware complexity, transition latency, and power consumption. However, traditional MTJs are insensitive to light, limiting their functionality in in-memory sensing─a crucial component for machine vision systems in artificial intelligence applications. Herein, the convergence of magnetic memory with optical sensing capabilities is achieved in the all-two-dimensional (2D) magnetic junction Fe<sub>3</sub>GaTe<sub>2</sub>/WSe<sub>2</sub>/Fe<sub>3</sub>GaTe<sub>2</sub>, which combines 2D magnetism and optoelectronic properties. The clean intrinsic band gap and prominent photoresponse of interlayer WSe<sub>2</sub> endow the tunneling barrier with optical tunability. The on-off states of junctions and the magnetoresistance can be flexibly controlled by the intensity of the optical signal at room temperature. Based on the optical-tunable magnetoresistance in all-2D magnetic junctions, a machine vision system with the architecture of in-memory sensing and computing is constructed, which possesses high performance in image recognition. Our work exhibits the advantages of 2D magneto-electronic devices and extends the application scenarios of magnetic memory devices in artificial intelligence.

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Publication Details

Journal
ACS Nano
Published
2024-09-17
DOI
https://doi.org/10.1021/acsnano.4c09735
Citations
8
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
1.67

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article

Photoresponsive Two-Dimensional Magnetic Junctions for Reconfigurable In-Memory Sensing

Feng Pan, Cheng Song, Hua Bai, Yuyan Wang et al.
8 citations
ACS Nano
Advanced Memory and Neural Computing
1.67
article

Photoresponsive Two-Dimensional Magnetic Junctions for Reconfigurable In-Memory Sensing

Feng Pan, Cheng Song, Hua Bai, Yuyan Wang, Lei Han, Wenxuan Zhu, Jiacheng Sun, Yuan Cheng
article en
8 citations

Abstract

Magnetic tunneling junctions (MTJs) lie in the core of magnetic random access memory, holding promise in integrating memory and computing to reduce hardware complexity, transition latency, and power consumption. However, traditional MTJs are insensitive to light, limiting their functionality in in-memory sensing─a crucial component for machine vision systems in artificial intelligence applications. Herein, the convergence of magnetic memory with optical sensing capabilities is achieved in the all-two-dimensional (2D) magnetic junction Fe<sub>3</sub>GaTe<sub>2</sub>/WSe<sub>2</sub>/Fe<sub>3</sub>GaTe<sub>2</sub>, which combines 2D magnetism and optoelectronic properties. The clean intrinsic band gap and prominent photoresponse of interlayer WSe<sub>2</sub> endow the tunneling barrier with optical tunability. The on-off states of junctions and the magnetoresistance can be flexibly controlled by the intensity of the optical signal at room temperature. Based on the optical-tunable magnetoresistance in all-2D magnetic junctions, a machine vision system with the architecture of in-memory sensing and computing is constructed, which possesses high performance in image recognition. Our work exhibits the advantages of 2D magneto-electronic devices and extends the application scenarios of magnetic memory devices in artificial intelligence.

ACS NanoVol. 18(39)
Tsinghua University (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 16%
Advanced Memory and Neural Computing
1.67
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