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ABSTRACT Magnetic skyrmions, as topologically protected spin textures, hold great potential for energy‐efficient neuromorphic systems. While artificial synapses have been demonstrated in magnetic multilayers by electrically controlling skyrmion populations, their probabilistic nucleation severely limits reliability. The recent emergence of 2D van der Waals magnets, with their inherent tunability and novel spintronic phenomena, offers a promising platform to overcome these challenges. Here, we demonstrate an artificial synaptic device in 2D ferromagnet Fe 3 GaTe 2 , operating on the fundamentally different principle of a deterministic and collective spin texture transformation from a skyrmion‐lattice to a stripe‐domain state. This transformation yields a linear, reproducible modulation of the anomalous Hall resistance. The slope of this linear response, defined as the synaptic weight, is effectively tuned by varying the pulse width, thereby enabling multi‐weight functionality and multiply‐accumulate operations. Projected scaling of the device reduces the single‐operation energy consumption to 0.66 pJ, a level comparable to state‐of‐the‐art memristor technologies (e.g., resistive random‐access memory and phase‐change memory). Furthermore, a hardware‐informed quantized neural network based on this synapse achieves a high recognition accuracy (∼96.1%) in handwritten‐digit recognition. Our findings establish a robust pathway for creating large‐scale and energy‐efficient neuromorphic systems based on the collective dynamics of Fe 3 GaTe 2 spin textures at room temperature.
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J Huang
University of Science and Technology of China
Tongji Zhu
University of Science and Technology of China
PeiYu Cai
University of Edinburgh
Advanced Materials
University of Edinburgh
University of Hong Kong
Tsinghua University
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Huang et al. (Wed,) studied this question.
synapsesocial.com/papers/6a1097f3d478ddac0ffd3d07 — DOI: https://doi.org/10.1002/adma.202520288
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