Low-Power Artificial Neural Network Perceptron Based on Monolayer MoS<sub>2</sub>-Reference-Cited by-同舟云学术

Low-Power Artificial Neural Network Perceptron Based on Monolayer MoS₂

Published:2022-02-15 Issue:3 Volume:16 Page:3684-3694
ISSN:1936-0851
Container-title:ACS Nano
language:en
Short-container-title:ACS Nano

Author:

Migliato Marega Guilherme¹²,Wang Zhenyu¹²,Paliy Maksym³,Giusi Gino⁴,Strangio Sebastiano³,Castiglione Francesco⁵,Callegari Christian⁵,Tripathi Mukesh¹²,Radenovic Aleksandra⁶^ORCID,Iannaccone Giuseppe³⁵,Kis Andras¹²^ORCID

Affiliation:

1. Institute of Electrical and Microengineering, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland

2. Institute of Materials Science and Engineering, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland

3. Department of Information Engineering, University of Pisa, I-56122 Pisa, Italy

4. Engineering Department, University of Messina, I-98166 Messina, Italy

5. Quantavis s.r.l., Largo Padre Renzo Spadoni snc, I-56123 Pisa, Italy

6. Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland

Funder

?cole Polytechnique F?d?rale de Lausanne

H2020 Future and Emerging Technologies

Competence Centre for Materials Science and Technology

H2020 European Research Council

Publisher

American Chemical Society (ACS)

Subject

General Physics and Astronomy,General Engineering,General Materials Science

Link

https://pubs.acs.org/doi/pdf/10.1021/acsnano.1c07065

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