An artificial neural network chip based on two-dimensional semiconductor

Recently, research on two-dimensional (2D) semiconductors has begun to translate from the fundamental investigation into rudimentary functional circuits. In this work, we unveil the first functional MoS2 artificial neural network (ANN) chip, including multiply-and-accumulate (MAC), memory and activation function circuits. Such MoS2 ANN chip is realized through fabricating 818 field-effect transistors (FETs) on a wafer-scale and high-homogeneity MoS2 film, with a gate-last process to realize top gate structured FETs. A 62-level simulation program with integrated circuit emphasis (SPICE) model is utilized to design and optimize our analog ANN circuits. To demonstrate a practical application, a tactile digit sensing recognition was demonstrated based on our ANN circuits. After training, the digit recognition rate exceeds 97%. Our work not only demonstrates the protentional of 2D semiconductors in wafer-scale integrated circuits, but also paves the way for its future application in AI computation. (C) 2021 Science China Press. Published by Elsevier B.V. and Science China Press. All rights reserved.

Automated summary

Research has shown that a MoS2 artificial neural network (ANN) chip with multiply-and-accumulate (MAC), memory, and activation function circuits has been successfully developed. Based on the design and optimization of analog ANN circuits, a tactile digit recognition application was demonstrated. This work not only showcases the potential of 2D semiconductors in wafer-scale integrated circuits, but also opens up possibilities for their future application in AI computation.