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technical paper
All electrical Manipulation of Multiple Resistant States via Modifying Magnetic Anisotropy for Emulating Synaptic Memory
Current-induced magnetization switching via spin-orbit torque (SOT) has been intensively investigated for conventional memory applications. With the emergence of multi-states devices that can be utilized in both memory and computing operations, research has pivoted to focus on all electrical-induced multiple resistant states to provide complementary hardware for unconventional computing 1. SOT-based multi-state devices can mimic artificial synapses and neurons for unconventional computing due to their non-volatility, high scalability, and low power consumption. Artificial synapses are utilized for memory function, acting as junctions between pre-and post-neurons, these continuously being adjusted to tune the strength between two neurons. Artificial neurons integrate all the input stimuli and fire once the accumulated potential reaches a certain threshold. SOT manipulation of multiple magnetization states can be realized by controlling domain wall propagation and modulating domain wall nucleation to emulate synapses 2. Domain wall propagation requires controllable pinning while domain nucleation can be effectively achieved by modifying the magnetic anisotropy energy. In this work, SOT-induced domain wall nucleation in Pt/Co system is demonstrated by engineering its interface to lower the anisotropy energy. A low magnetic anisotropy energy of 1.35×105 J/m3 has been achieved in Pt (5 nm)/Co (1.2 nm)/HfOx (2 nm)/Ti (2 nm) structure, as obtained from the hysteresis loops shown in Fig. 1(a) and (b). Electrical and Kerr microscopy measurements were carried out to determine the multiple resistance states. Figure 2(a) shows the Hall resistance Rxy change with magnetic field HOOP. Figure 2(b) shows the pulse current-induced multiple resistance; the insets show the domain images after sending a pulse current (I) from 6 to 9 mA. The results clearly indicate the multi-states in Pt/Co/HfOx/Ti system are driven by current, which is promising for synaptic memory-driven neuromorphic applications.
References 1 Zhou, J., et. al., Adv. Mater. 33, 2103672 (2021).
2 Jin, T., et. al., J. Phys. D: Appl. Phys, 52, 445001 (2019).