Low-Voltage Oscillatory Neurons for Memristor-Based Neuromorphic Systems.

Neuromorphic systems consisting of artificial neurons and synapses can process complex information with high efficiency to overcome the bottleneck of von Neumann architecture. Artificial neurons are essentially required to possess functions such as leaky integrate-and-fire and output spike. However, previous reported artificial neurons typically have high operation voltage and large leakage current, leading to significant power consumption, which is contrary to the energy-efficient biological model.

A Threshold Switching Selector Based on Highly Ordered Ag Nanodots for X-Point Memory Applications.

Leakage interference between memory cells is the primary obstacle for enlarging X-point memory arrays. Metal-filament threshold switches, possessing excellent selectivity and low leakage current, are developed in series with memory cells to reduce sneak path current and lower power consumption. However, these selectors typically have limited on-state currents (≤10 µA), which are insufficient for memory RESET operations.