Memristive Anodic Oxides: Production, Properties and Applications in Neuromorphic Computing

Andrea Brenna, Fernando Corinto, Seyedreza Noori, Marco Ormellese, MariaPia Pedeferri and Maria Vittoria Diamanti

A chapter in Advances in Memristor Neural Networks - Modeling and Applications from IntechOpen

Abstract: Memristive devices generally consist of metal oxide elements with specific structure and chemical composition, which are crucial to obtain the required variability in resistance. This makes the control of oxide properties vital. While CMOS compatible production technologies for metal oxides deposition generally involve physical or chemical deposition pathways, we here describe the possibility of using an electrochemical technique, anodic oxidation, as an alternative route to produce memristive oxides. In fact, anodization allows to form a very large range of oxides on the surface of valve metals, such as titanium, hafnium, niobium and tantalum, whose thickness, structure and functional properties depend on process parameters imposed. These oxides may be of interest to build neural networks based on memristive elements produced by anodic oxidation.

Keywords: titanium dioxide; tantalum oxide; hafnium oxide; niobium oxide; memristor; resistive switching; anodizing (search for similar items in EconPapers)
JEL-codes: C60 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:ito:pchaps:154402

DOI: 10.5772/intechopen.79292

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