Dual-gate manipulation of a HfZrOx-based MoS<sub>2</sub> field-effect transistor towards enhanced neural network applications-Reference-Cited by-同舟云学术

Dual-gate manipulation of a HfZrOx-based MoS₂ field-effect transistor towards enhanced neural network applications

Published:2023 Issue:1 Volume:15 Page:313-320
ISSN:2040-3364
Container-title:Nanoscale
language:en
Short-container-title:Nanoscale

Author:

Liu Yilun¹,Li Qingxuan¹,Zhu Hao¹^ORCID,Ji Li¹,Sun Qingqing¹,Zhang David Wei¹,Chen Lin¹^ORCID

Affiliation:

1. State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, P. R. China

Abstract

Artificial neural networks (ANNs) have learning and computing capabilities, and alleviate the problem of high power consumption of traditional von Neumann architectures, providing a basis for advanced image recognition and low-power detection.

Funder

Shanghai Rising-Star Program

Publisher

Royal Society of Chemistry (RSC)

Subject

General Materials Science

Link

http://pubs.rsc.org/en/content/articlepdf/2023/NR/D2NR05720D

Reference39 articles.

1. Deep learning for computational biology

2. Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups

3. Birkhoff and von Neumann's Interpretation of Quantum Mechanics

4. Perovskite neural trees

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