605 research outputs found
Tuning a binary ferromagnet into a multi-state synapse with spin-orbit torque induced plasticity
Inspired by ion-dominated synaptic plasticity in human brain, artificial
synapses for neuromorphic computing adopt charge-related quantities as their
weights. Despite the existing charge derived synaptic emulations, schemes of
controlling electron spins in ferromagnetic devices have also attracted
considerable interest due to their advantages of low energy consumption,
unlimited endurance, and favorable CMOS compatibility. However, a generally
applicable method of tuning a binary ferromagnet into a multi-state memory with
pure spin-dominated synaptic plasticity in the absence of an external magnetic
field is still missing. Here, we show how synaptic plasticity of a
perpendicular ferromagnetic FM1 layer can be obtained when it is
interlayer-exchange-coupled by another in-plane ferromagnetic FM2 layer, where
a magnetic-field-free current-driven multi-state magnetization switching of FM1
in the Pt/FM1/Ta/FM2 structure is induced by spin-orbit torque. We use current
pulses to set the perpendicular magnetization state which acts as the synapse
weight, and demonstrate spintronic implementation of the excitatory/inhibitory
postsynaptic potentials and spike timing-dependent plasticity. This
functionality is made possible by the action of the in-plane interlayer
exchange coupling field which leads to broadened, multi-state magnetic reversal
characteristics. Numerical simulations, combined with investigations of a
reference sample with a single perpendicular magnetized Pt/FM1/Ta structure,
reveal that the broadening is due to the in-plane field component tuning the
efficiency of the spin-orbit-torque to drive domain walls across a landscape of
varying pinning potentials. The conventionally binary FM1 inside our
Pt/FM1/Ta/FM2 structure with inherent in-plane coupling field is therefore
tuned into a multi-state perpendicular ferromagnet and represents a synaptic
emulator for neuromorphic computing.Comment: 37 pages with 11 figures, including 20 pages for manuscript and 17
pages for supplementary informatio
Terahertz electrical writing speed in an antiferromagnetic memory
The speed of writing of state-of-the-art ferromagnetic memories is physically limited by an intrinsic gigahertz threshold. Recently, realization of memory devices based on antiferromagnets, in which spin directions periodically alternate from one atomic lattice site to the next has moved research in an alternative direction. We experimentally demonstrate at room temperature that the speed of reversible electrical writing in a memory device can be scaled up to terahertz using an antiferromagnet. A current-induced spin-torque mechanism is responsible for the switching in our memory devices throughout the 12-order-of-magnitude range of writing speeds from hertz to terahertz. Our work opens the path toward the development of memory-logic technology reaching the elusive terahertz band
Quantum materials for energy-efficient neuromorphic computing
Neuromorphic computing approaches become increasingly important as we address
future needs for efficiently processing massive amounts of data. The unique
attributes of quantum materials can help address these needs by enabling new
energy-efficient device concepts that implement neuromorphic ideas at the
hardware level. In particular, strong correlations give rise to highly
non-linear responses, such as conductive phase transitions that can be
harnessed for short and long-term plasticity. Similarly, magnetization dynamics
are strongly non-linear and can be utilized for data classification. This paper
discusses select examples of these approaches, and provides a perspective for
the current opportunities and challenges for assembling quantum-material-based
devices for neuromorphic functionalities into larger emergent complex network
systems
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