Temperature Regulated Artificial Neuron Based on Memristor

Recently, artificial neurons have attracted much attention due to their excellent energy efficiency and scalability. However, there are still few reports on the regulation of the performance of artificial neuron based on single device. In the letter, we present an artificial neuron device based on Ag/TaOx/Si that not only has excellent turn-on and turn-off performance, but also exhibits sustained stability under multiple cycle tests. Moreover, the Integrate -and-Fire (IF) neuron model is successfully simulated at room temperature. More importantly, we find that an increase of temperature could reduce the threshold voltage and reset voltage of neurons, improve the probability of neuronal firing, and promote the transformation of neurons from nonvolatile to volatile. This work provides an effective method for regulating artificial neurons and has important implications for studying information transfer in biology and adapting complex computations in a memory computing framework.

Automated summary

This study introduces an artificial neuron device based on Ag/TaOx/Si, which demonstrates stable performance and successfully simulates neuron models. Moreover, increasing temperature can enhance neuron performance and promote neuron transformation.