An artificial neural network chip based on two-dimensional semiconductor

• 作者: Shunli Ma Tianxiang Wu Xinyu Chen Yin Wang Hongwei Tang Yuting Yao Yan Wang Ziyang Zhu Jianan Deng Jing Wan Ye Lu Zhengzong Sun Zihan Xu Antoine Riaud Chenjian Wu David Wei Zhang Yang Chai Peng Zhou Junyan Ren Wenzhong Bao
• 来源期刊: 科学通报（英文版）
• 年，卷（期）: 2022,（3）
• 所属期刊栏目: Physical Sciences
• 页码范围: 270-277
• 页数: 8页
• 语种: 英文

摘要

Recently,research on two-dimensional (2D) semiconductors has begun to translate from the fundamen-tal 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 inte-grated circuits,but also paves the way for its future application in AI computation.