An artificial neural network chip based on two-dimensional semiconductor

Shunli Ma

doi:10.1016/j.scib.2021.10.005

An artificial neural network chip based on two-dimensional semiconductor

2022-02-01

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AI

DOI：10.1016/j.scib.2021.10.005

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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.

Keywords:

MoS2

Two-dimensional (2D) FETs

Artificial neural network (ANN)

Multiply-and-accumulate (MAC)

Circuits

An artificial neural network chip based on two-dimensional semiconductor

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