Local Anodic Oxidation for Crossbar-Array Architecture

The formation feasibility for a neural network based on crossbar-array architecture on a silicon substrate has been demonstrated. The possibility of neural network implementation in the form of crossbar-array architecture on a silicon substrate has been shown. It is suggested that the crossbar-array...

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Bibliographic Details
Published in:Technical physics 2022-05, Vol.67 (5), p.423-428
Main Authors: Polyakova, V. V., Savenko, A. V.
Format: Article
Language:English
Subjects:
Anodizing
Arrays
Classical and Continuum Physics
Conductors
Integrated circuits
Memory (Computers)
Memristors
Neural networks
Oxidation
Oxidation-reduction reaction
Physics
Physics and Astronomy
Process parameters
Semiconductor chips
Silicon
Silicon substrates
Titanium oxides
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Summary:The formation feasibility for a neural network based on crossbar-array architecture on a silicon substrate has been demonstrated. The possibility of neural network implementation in the form of crossbar-array architecture on a silicon substrate has been shown. It is suggested that the crossbar-array architecture (a set of orthogonal nanometer conductors with a titanium oxide layer in between, the conductivity of which is sensitive to applied voltage) be configured using local anodic oxidation. Test results for process parameters used in local anodic oxidation of silicon and titanium to create elements of a memristor-based neural matrix are presented.
ISSN:1063-7842
1090-6525
DOI:10.1134/S1063784222060068