2017
DOI: 10.48550/arxiv.1712.00550
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

Using Programmable Graphene Channels as Weights in Spin-Diffusive Neuromorphic Computing

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2018
2018
2018
2018

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 0 publications
0
1
0
Order By: Relevance
“…In recent years, graphene has emerged as one of the most efficient spin channel materials [2], exhibiting gate tunable spin transport, long spin lifetimes and long spin diffusion lengths at room temperature [3][4][5][6][7][8][9][10][11][12]. These make graphene a promising material for spintronics applications [13][14][15][16][17][18][19]. What makes graphene even more special is the high tunability of its properties.…”
Section: Introductionmentioning
confidence: 99%
“…In recent years, graphene has emerged as one of the most efficient spin channel materials [2], exhibiting gate tunable spin transport, long spin lifetimes and long spin diffusion lengths at room temperature [3][4][5][6][7][8][9][10][11][12]. These make graphene a promising material for spintronics applications [13][14][15][16][17][18][19]. What makes graphene even more special is the high tunability of its properties.…”
Section: Introductionmentioning
confidence: 99%