Low-Power Artificial Neural Network Perceptron Based on Monolayer MoS

MoS2 beyond-Moore in-memory computing nanoelectronics two-dimensional materials two-dimensional semiconductors

Journal

ACS nano
ISSN: 1936-086X
Titre abrégé: ACS Nano
Pays: United States
ID NLM: 101313589

Informations de publication

Date de publication:
22 Mar 2022
Historique:
pubmed: 16 2 2022
medline: 16 2 2022
entrez: 15 2 2022
Statut: ppublish

Résumé

Machine learning and signal processing on the edge are poised to influence our everyday lives with devices that will learn and infer from data generated by smart sensors and other devices for the Internet of Things. The next leap toward ubiquitous electronics requires increased energy efficiency of processors for specialized data-driven applications. Here, we show how an in-memory processor fabricated using a two-dimensional materials platform can potentially outperform its silicon counterparts in both standard and nontraditional Von Neumann architectures for artificial neural networks. We have fabricated a flash memory array with a two-dimensional channel using wafer-scale MoS

Identifiants

pubmed: 35167265
doi: 10.1021/acsnano.1c07065
pmc: PMC8945700
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

3684-3694

Références

ACS Nano. 2021 Jan 26;15(1):1764-1774
pubmed: 33443417
Nanotechnology. 2016 Sep 9;27(36):365202
pubmed: 27479054
Nat Nanotechnol. 2013 Jul;8(7):497-501
pubmed: 23748194
Nature. 2020 Nov;587(7832):72-77
pubmed: 33149289
Nat Nanotechnol. 2018 Mar;13(3):183-191
pubmed: 29511331
Adv Mater. 2020 Sep;32(36):e2002431
pubmed: 32700395
Science. 2016 Oct 7;354(6308):99-102
pubmed: 27846499
Nat Nanotechnol. 2011 Mar;6(3):147-50
pubmed: 21278752
Nat Nanotechnol. 2020 Jul;15(7):529-544
pubmed: 32231270
Sci Adv. 2020 Jan 31;6(5):eaay2378
pubmed: 32064342
Nat Nanotechnol. 2015 May;10(5):403-6
pubmed: 25849785
Artif Intell Med. 2001 Aug;23(1):89-109
pubmed: 11470218
Sci Rep. 2017 Jul 10;7(1):5016
pubmed: 28694459
Small. 2020 Nov;16(47):e2004907
pubmed: 33140573
Nature. 2020 Jan;577(7792):641-646
pubmed: 31996818
Nature. 2020 Mar;579(7797):62-66
pubmed: 32132692
Small. 2015 Jan 14;11(2):208-13
pubmed: 25115804
Nat Commun. 2020 Nov 23;11(1):5934
pubmed: 33230113
ACS Nano. 2013 Apr 23;7(4):3246-52
pubmed: 23510133
Proc Natl Acad Sci U S A. 2019 Mar 5;116(10):4123-4128
pubmed: 30782810
Nano Lett. 2017 Aug 9;17(8):5056-5063
pubmed: 28700239
Sci Rep. 2017 May 18;7(1):2118
pubmed: 28522849

Auteurs

Guilherme Migliato Marega (G)

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

Zhenyu Wang (Z)

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

Maksym Paliy (M)

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

Gino Giusi (G)

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

Sebastiano Strangio (S)

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

Francesco Castiglione (F)

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

Christian Callegari (C)

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

Mukesh Tripathi (M)

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

Aleksandra Radenovic (A)

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

Giuseppe Iannaccone (G)

Department of Information Engineering, University of Pisa, I-56122 Pisa, Italy.
Quantavis s.r.l., Largo Padre Renzo Spadoni snc, I-56123 Pisa, Italy.

Andras Kis (A)

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

Classifications MeSH