Spin–Orbit-Torque-Driven Two-Terminal Giant Magnetoresistance Memristive Devices for In-Memory Computing
Source abstract
Abstract
The rising complexity of artificial intelligence and data-intensive applications drives the demand for memristive devices to support high-performance and scalable processing-in-memory (PIM) architectures. While three- and four-terminal spintronic PIM solutions show promise, they face scalability challenges due to large footprints. This study demonstrates a two-terminal spin-orbit torque (SOT)-driven giant magnetoresistance (GMR) memristive device utilizing a Pt/Co/Cu/CoTb stack, integrating data storage and logic functions within a single unit. Ten nonvolatile resistance states are achieved by modulating the SOT current amplitude, and additional states with opposite polarities are created by tuning the CoTb alloy composition. Synaptic plasticity, including long-term potentiation and depression, is demonstrated through current pulse modulation. Simulations of a deep neural network constructed with this GMR device achieve 92% accuracy in handwritten digit recognition and image visualization tasks. Moreover, basic Boolean logic functions further showcase the processing capabilities. This two-terminal GMR device offers a scalable solution for advanced memristive memory and in-memory computing.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Memory and Neural Computing · Neural Networks and Reservoir Computing · Ferroelectric and Negative Capacitance Devices
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Physical and Mathematical Sciences, Nanyang Technological University, 21 Nanyang Link, Singapore 637371, Singapore
School of Integrated Circuits
Huazhong University of Science and Technology
School of Physical Science and Technology
Lanzhou University
School of Physics
Funding
Ministry of Education of the People's Republic of China · China Scholarship Council · National Natural Science Foundation of China
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