2D Metal-Organic Framework Based Optoelectronic Neuromorphic Transistors for Human Emotion Simulation and Neuromorphic Computing

2D metal-organic frameworks (2D-MOFs) have been extensively studied as promising materials in the fields of electrocatalysis, drug delivery, electronic devices, etc. However, few studies have explored the application potential of 2D-MOFs in novel neuromorphic computing devices. Herein, an optoelectronic neuromorphic transistor based on a 2D-MOF/polymer charge-trapping layer is reported. It is found that the large specific surface area, stable crystal structure, and highly accessible active sites in 2D-MOFs make them excellent charge-trapping materials for the devices, which are beneficial for mimicking the memory and learning functions observed in the organism's nervous systems. Different types of synaptic behaviors have been realized in the 2D-MOF-based neuromorphic devices under stimuli signal, e.g., paired-pulse facilitation, excitatory postsynaptic current, short-term memory, and long-term memory. More interestingly, emotion-adjustable learning behavior is realized by changing the value of the source-drain voltage. This work can shed light on the application of 2D-MOFs in neuromorphic computing and will contribute to the further development of neuromorphic computing devices.

Automated summary

This article reports on an optoelectronic neuromorphic transistor based on a 2D-MOF/polymer charge-trapping layer, and explores the application potential of 2D-MOFs in neuromorphic computing. The results show that 2D-MOFs exhibit excellent charge-trapping properties and achieve various synaptic behaviors and emotion-adjustable learning behavior.