Controlling the multi-state switching is significantly essential for the extensive utilization of 2D ferromagnet in magnetic racetrack memories, topological devices, and neuromorphic computing devices. The development of all-electric functional nanodevices with multi-state switching and a rapid reset remains challenging. Herein, to imitate the potentiation and depression process of biological synapses, a full-current strategy is unprecedently established by the controllable resistance-state switching originating from the spin configuration rearrangement by domain wall number modulation in Fe3GeTe2. In particular, a strong correlation is uncovered in the reduction of domain wall number with the corresponding resistance decreasing by in-situ Lorentz transmission electron microscopy. Interestingly, the magnetic state is reversed instantly to the multi-domain wall state under a single pulse current with a higher amplitude, attributed to the rapid thermal demagnetization by simulation. Based on the neuromorphic computing system with full-current-driven artificial Fe3GeTe2 synapses with multi-state switching, a high accuracy of ≈91% is achieved in the handwriting image recognition pattern. The results identify 2D ferromagnet as an intriguing candidate for future advanced neuromorphic spintronics.
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