Microneural Network System Based on MoS2/h-BN/Graphene van der Waals Heterojunction Transistor

The integration of data storage and computing capabilities into a single physical component has led to the development of a microneuronal network system with high precision and speed rates. To achieve this system architecture, bold innovations in the underlying hardware structure and neural network architecture are required. This article introduces an optoelectronic storage device based on the MoS2/h-BN/graphene van der Waals heterojunction transistor. At room temperature, the transistor exhibits an electron mobility of up to 340 cm(2)/(V center dot s) and a large storage window due to its unique van der Waals heterojunction. The transistor's reconfigurable nonvolatile optoelectronic properties enable the construction of logic gates, including AND, OR, NAND, and NOR. Leveraging these logic gates, a microneural network system is created that simulates future machine vision applications. The system achieves a remarkable recognition rate of 96.3% for images in a multidimensional color space, demonstrating the significant development potential of the microneural network system based on the MoS2/h-BN/graphene vdW heterojunction transistor in future machine vision.

Automated summary

The integration of data storage and computing capabilities has led to the development of a microneuronal network system with high precision and speed rates. This article introduces an optoelectronic storage device based on a transistor, which enables the construction of logic gates and the simulation of future machine vision applications. The microneural network system achieves a recognition rate of 96.3% in a multidimensional color space.