Nanograin network memory with reconfigurable percolation paths for synaptic interactions

Abstract

Abstract The development of memory devices with functions that simultaneously process and store data is required for efficient computation. To achieve this, artificial synaptic devices have been proposed because they can construct hybrid networks with biological neurons and perform neuromorphic computation. However, irreversible aging of these electrical devices causes unavoidable performance degradation. Although several photonic approaches to controlling currents have been suggested, suppression of current levels and switching of analog conductance in a simple photonic manner remain challenging. Here, we demonstrated a nanograin network memory using reconfigurable percolation paths in a single Si nanowire with solid core/porous shell and pure solid core segments. The electrical and photonic control of current percolation paths enabled the analog and reversible adjustment of the persistent current level, exhibiting memory behavior and current suppression in this single nanowire device. In addition, the synaptic behaviors of memory and erasure were demonstrated through potentiation and habituation processes. Photonic habituation was achieved using laser illumination on the porous nanowire shell, with a linear decrease in the postsynaptic current. Furthermore, synaptic elimination was emulated using two adjacent devices interconnected on a single nanowire. Therefore, electrical and photonic reconfiguration of the conductive paths in Si nanograin networks will pave the way for next-generation nanodevice technologies.