Reconfigurable memristor based on SrTiO_(3) thin-film for neuromorphic computing

Neuromorphic computing aims to achieve artificial intelligence by mimicking the mechanisms of biological neurons and synapses that make up the human brain.However,the possibility of using one reconfigurable memristor as both artificial neuron and synapse still requires intensive research in detail.In this work,Ag/SrTiO_(3)(STO)/Pt memristor with low operating voltage is manufactured and reconfigurable as both neuron and synapse for neuromorphic computing chip.By modulating the compliance current,two types of resistance switching,volatile and nonvolatile,can be obtained in amorphous STO thin film.This is attributed to the manipulation of the Ag conductive filament.Furthermore,through regulating electrical pulses and designing bionic circuits,the neuronal functions of leaky integrate and fire,as well as synaptic biomimicry with spike-timing-dependent plasticity and paired-pulse facilitation neural regulation,are successfully realized.This study shows that the reconfigurable devices based on STO thin film are promising for the application of neuromorphic computing systems.

A multimode-fused sensory memory system based on a robust self-assembly nanoscaffolded BaTiO_(3):Eu_(2)O_(3) memristor

Biologically inspired neuromorphic sensory memory systems based on memristor have received a lot of attention in the booming artificial intelligence industry due to significant potential to effectively process multi-sensory signals from complex external environments.However,many memristors have significant switching parameters disperse,which is a great challenge for using memristors in bionic neuromorphic sensory memory systems.Herein,a stable ferroelectric memristor based on the Pd/BaTiO_(3):Eu2O_(3)/La0.67Sr0.33MnO_(3)grown on Silicon structure with SrTiO_(3)as buffer layer is presented.The device possesses low coercive field voltage(-1.3-2.1 V)and robust endurance characteristic(~10^(10)cycles)through optimizing the growth temperature.More importantly,an ultra-stable artificial multimodal sensory memory system with visual and tactile functions was reported for the first time by combining a pressure sensor,a photosensitive sensor,and a robotic arm.Utilizing the above system,the sensitivity value of the system is expressed by the conductance of the memristor to realize the gradual change of external stimulus,and multi signals inputs at the same time to this system have faithfully achieved sensory adaptation to multimodal sensors.This work paves the way for future development of memristor-based perception systems in efficient multisensory neural robots.