Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/141472
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dc.contributor.authorBerco, Danen_US
dc.contributor.authorAng, Diing Shenpen_US
dc.date.accessioned2020-06-08T10:08:01Z-
dc.date.available2020-06-08T10:08:01Z-
dc.date.issued2019-
dc.identifier.citationBerco, D., & Ang, D. A. (2019). Inducing alternating nanoscale rectification in a dielectric material for bidirectional-trigger artificial synapses. Journal of Vacuum Science and Technology B: Nanotechnology and Microelectronics, 37(6), 061806-. doi:10.1116/1.5123665en_US
dc.identifier.issn2166-2746en_US
dc.identifier.urihttps://hdl.handle.net/10356/141472-
dc.description.abstractNanoionic device-based artificial neural networks that consume little power and hold a potential for enormous densities still fall behind the capabilities of software algorithms running on traditional von Neumann machines. In addition, despite many publications showing multilevel parametric capabilities associated with these devices, a real-world nonvolatile memory application that maximizes their potential density is yet to be realized. One reason may be due to their limited functional mode as an analog passive element that is crippled by large interdevice variations. This work demonstrates that the nanoscale stoichiometry in transition metal oxides can be triggered to form asymmetric cationlike vacancy distributions that yield dynamically toggled current rectifying properties. In this manner, a rectifying device operated as an artificial synapse is capable of switching between excitatory and inhibitory modes, dissipating ∼20 fJ/switching event. This complementary functionality (in a similar manner to CMOS transistors) adds a whole new degree of freedom to the design of neuromorphic computing platforms. Moreover, the entire spectrum of nonvolatile states derived from different cation distributions (positive-rectifying, negative-rectifying, conductive, and insulating) may be considered as a mutually exclusive and interchangeable basis set for robust multilevel memory implementation that overcomes the issues associated with large process and device related parametric distributions.en_US
dc.description.sponsorshipMOE (Min. of Education, S’pore)en_US
dc.language.isoenen_US
dc.relation.ispartofJournal of Vacuum Science and Technology B: Nanotechnology and Microelectronicsen_US
dc.rights© 2019 The Author(s). All rights reserved. This paper was published by the AVS in Journal of Vacuum Science and Technology B: Nanotechnology and Microelectronics and is made available with permission of The Author(s).en_US
dc.subjectEngineering::Electrical and electronic engineeringen_US
dc.titleInducing alternating nanoscale rectification in a dielectric material for bidirectional-trigger artificial synapsesen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.identifier.doi10.1116/1.5123665-
dc.description.versionPublished versionen_US
dc.identifier.scopus2-s2.0-85073369134-
dc.identifier.issue6en_US
dc.identifier.volume37en_US
dc.identifier.spage061806-1en_US
dc.identifier.epage061806-10en_US
dc.subject.keywordsNanoionicsen_US
dc.subject.keywordsIons and Propertiesen_US
item.fulltextWith Fulltext-
item.grantfulltextopen-
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