Ultrafine Nickel Sulfide-Based Bipolar Resistive Switching Device as Artificial Synapses for Neuromorphic Application

Biologically inspired systems, particularly those that mimic the nervous system of living beings, are becoming more demanded due to their ability to solve ill-posed problems such as pattern recognition or communication with the external environment. Memristors are essential components to replicate high-density networks of biological synapses that control the effectiveness of communication among neurons and implement learning capability because of their tunable conductance. In this study, an organic-inorganic hybrid system of hexamethylenediamine-stabilized ultrafine nickel sulfide particles was synthesized by employing a complexation-mediated route. Here, we propose a nickel sulfide-based memristor as an artificial synapse for neuromorphic application. The current-voltage behavior of the device exhibited bipolar resistive switching with a stable ON and OFF state with an ON/OFF ratio value of 2.5 x 101. The high-conductance state of the device showed the Ohmic conduction mechanism, and the low-conductance state of the device exhibited the Fowler-Nordheim tunneling mechanism. Using identical and nonidentical pulses, the synaptic plasticity behavior of the device was investigated, which revealed the inverse-symmetric and mirror-symmetric patterns, respectively. The device mimicked the spike-time-dependent plasticity properties for Hebbian learning with a conductance value change from -86 to 91%. We also designed the spiking neural network, consisting of 18 synapses and 11 integrated firing neurons, based on the winner-take-all strategy for unsupervised feature learning.