Towards engineering in memristors for emerging memory and neuromorphic computing: A review

Abstract Resistive random-access memory (RRAM), also known as memristors, having a very simple device structure with two terminals, fulfill almost all of the fundamental requirements of volatile memory, nonvolatile memory, and neuromorphic characteristics. Its memory and neuromorphic behaviors are c...

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Bibliographic Details
Published in:Journal of semiconductors 2021-01, Vol.42 (1), p.13101-55
Main Authors: Sokolov, Andrey S., Abbas, Haider, Abbas, Yawar, Choi, Changhwan
Format: Article
Language:English
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Summary:Abstract Resistive random-access memory (RRAM), also known as memristors, having a very simple device structure with two terminals, fulfill almost all of the fundamental requirements of volatile memory, nonvolatile memory, and neuromorphic characteristics. Its memory and neuromorphic behaviors are currently being explored in relation to a range of materials, such as biological materials, perovskites, 2D materials, and transition metal oxides. In this review, we discuss the different electrical behaviors exhibited by RRAM devices based on these materials by briefly explaining their corresponding switching mechanisms. We then discuss emergent memory technologies using memristors, together with its potential neuromorphic applications, by elucidating the different material engineering techniques used during device fabrication to improve the memory and neuromorphic performance of devices, in areas such as I ON / I OFF ratio, endurance, spike time-dependent plasticity (STDP), and paired-pulse facilitation (PPF), among others. The emulation of essential biological synaptic functions realized in various switching materials, including inorganic metal oxides and new organic materials, as well as diverse device structures such as single-layer and multilayer hetero-structured devices, and crossbar arrays, is analyzed in detail. Finally, we discuss current challenges and future prospects for the development of inorganic and new materials-based memristors.
ISSN:1674-4926
2058-6140
DOI:10.1088/1674-4926/42/1/013101