Flexible three-dimensional artificial synapse networks with correlated learning and trainable memory capability

Chaoxing Wu; Tae Whan Kim; Hwan Young Choi; Dmitri B. Strukov; J. Joshua Yang

doi:10.1038/s41467-017-00803-1

Nature Communications (Sep 2017)

Flexible three-dimensional artificial synapse networks with correlated learning and trainable memory capability

Chaoxing Wu,
Tae Whan Kim,
Hwan Young Choi,
Dmitri B. Strukov,
J. Joshua Yang

Affiliations

Chaoxing Wu: Department of Electronic and Computer Engineering, Hanyang University
Tae Whan Kim: Department of Electronic and Computer Engineering, Hanyang University
Hwan Young Choi: Department of Electronic and Computer Engineering, Hanyang University
Dmitri B. Strukov: Department of Electrical and Computer Engineering, University of California at Santa Barbara
J. Joshua Yang: Department of Electrical and Computer Engineering, University of Massachusetts

DOI: https://doi.org/10.1038/s41467-017-00803-1
Journal volume & issue: Vol. 8, no. 1
pp. 1 – 9

Abstract

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High-density information storage calls for the development of modern electronics with multiple stacking architectures that increase the complexity of three-dimensional interconnectivity. Here, Wu et al. build a stacked yet flexible artificial synapse network using layer-by-layer solution processing.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

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