Decoding the metallic bridging dynamics in nanogap atomic switches
Atomic switch is a promising candidate as the basic building block for large-scale neuromorphic network due to tunable switching behaviors. Several neuromorphic components based on the atomic switch have been demonstrated, including artificial synapse, artificial neuron and short-term to long-term memory, making it possible to construct neuromorphic systems using a unified device. Although the mechanism of atomic switch has been actively studied, most of the discussions in previous works are qualitative and fail to provide a comprehensive view of the dynamics that can precisely describe the metallic bridging under electric field. In this paper, we designed a gap-type atomic switch and realized various switching behaviors including both volatile and non-volatile resistive switching. Employing advanced microanalysis technology, we experimentally studied the switching mechanism and captured the nanoscale metallic filament in gap-type atomic switch. Further, based on the experimental findings as well as the electrochemistry fundamental and electron tunneling effect, we proposed a physical model that precisely reproduced the sophisticated switching behaviors. Our model mathematically described the growth/shrinkage dynamics of nanoscale metallic filament, providing a direction for studying the switching behaviors from a quantitative view. The simulation results are in good agreement with the experimental findings in both DC sweep and pulse operation modes. In addition, we have demonstrated neuronal tonic spiking and short-term to long-term memory in experiment and simulation, indicating that our model can be applied to circuit level simulation of large-scale atomic switch array for neuromorphic applications.