Spin–Orbit Torque-Driven Memristor in L1₀ FePt Systems with Nanoscale-Thick Layers for Neuromorphic Computing

In this study, a memristor driven by spin–orbit torque (SOT) is realized in the nanoscale thickness L1 0 FePt systems with high perpendicular magnetization anisotropy (PMA). Due to the domain nucleation and expansion driven by current pulses, multilevel Hall resistance states can be continuously tuned by current density, where the memristive states are retained by the domain wall pinning effects. The properties of multilevel resistance states for samples with different structures are associated with the magnitude of field-like torque, and the larger efficiency of field-like torque enhances multiple resistance characteristics. Furthermore, the stable memristive behavior is obtained in the FePt/MgO/NiFe heterostructure. Finally, a three-layer multilayer perceptron (MLP) neural network is built to perform the MNIST handwritten digit recognition task based on the device’s memristive behaviors, and the accuracy of weight update can reach up to 88.55%. These results pave the way for the application of L1 0 FePt nanomaterials in neuromorphic computing.