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Bidirectional volatile signatures of metal-oxide memristors-Part II: modeling

Bidirectional volatile signatures of metal-oxide memristors-Part II: modeling
Bidirectional volatile signatures of metal-oxide memristors-Part II: modeling
Volatility in metal-oxide resistive random access memory (RRAM) families has mostly been treated as an unwanted side-effect, although recently there are trends to interpret such behavior as an additional technological feature. To date, the field has seen early demonstrations of possible applications that harness volatility. Moreover, some work has been conducted to understand both the mechanisms responsible for this behavior. In the context of modeling RRAM volatility, we still lack a comprehensive model that could allow simulations in a larger scale. In an attempt to fill this gap, this work presents a modeling framework that can account for RRAM relaxation characteristics. Specifically, we show how volatility can be simulated to significant accuracy when the resistive state (RS) of a device as well as the stimulus protocol in use are well-defined. Importantly, our approach is solely data-driven and decoupled from previous physical modeling studies on volatility. Our results work for both stimulation polarities and are consistent for a number of TiOx devices in use. Moreover, the mathematical relations that unfold via modeling volatility provide further intuition on the effect that invasive protocols can have on this technology. This modeling solution enables more advanced studying of memristive technologies in one hand, as well as more intricate designs of larger systems that can account for transient RRAM changes over time.
Memristors, modelling, resistive random access memory (RRAM), volatility
1557-9646
5166-5173
Giotis, Christos
2b14de78-3ff1-425d-ac4b-10fbf228377c
Serb, Alexantrou
30f5ec26-f51d-42b3-85fd-0325a27a792c
Stathopoulos, Spyros
98d12f06-ad01-4708-be19-a97282968ee6
Prodromakis, Themistoklis
d58c9c10-9d25-4d22-b155-06c8437acfbf
Giotis, Christos
2b14de78-3ff1-425d-ac4b-10fbf228377c
Serb, Alexantrou
30f5ec26-f51d-42b3-85fd-0325a27a792c
Stathopoulos, Spyros
98d12f06-ad01-4708-be19-a97282968ee6
Prodromakis, Themistoklis
d58c9c10-9d25-4d22-b155-06c8437acfbf

Giotis, Christos, Serb, Alexantrou, Stathopoulos, Spyros and Prodromakis, Themistoklis (2020) Bidirectional volatile signatures of metal-oxide memristors-Part II: modeling. IEEE Transactions on Electron Devices, 67 (11), 5166-5173, [9210791]. (doi:10.1109/TED.2020.3022343).

Record type: Article

Abstract

Volatility in metal-oxide resistive random access memory (RRAM) families has mostly been treated as an unwanted side-effect, although recently there are trends to interpret such behavior as an additional technological feature. To date, the field has seen early demonstrations of possible applications that harness volatility. Moreover, some work has been conducted to understand both the mechanisms responsible for this behavior. In the context of modeling RRAM volatility, we still lack a comprehensive model that could allow simulations in a larger scale. In an attempt to fill this gap, this work presents a modeling framework that can account for RRAM relaxation characteristics. Specifically, we show how volatility can be simulated to significant accuracy when the resistive state (RS) of a device as well as the stimulus protocol in use are well-defined. Importantly, our approach is solely data-driven and decoupled from previous physical modeling studies on volatility. Our results work for both stimulation polarities and are consistent for a number of TiOx devices in use. Moreover, the mathematical relations that unfold via modeling volatility provide further intuition on the effect that invasive protocols can have on this technology. This modeling solution enables more advanced studying of memristive technologies in one hand, as well as more intricate designs of larger systems that can account for transient RRAM changes over time.

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Bidirectional Volatile Signatures of Metal-Oxide Memristors - Part II Modelling - Version of Record
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Accepted/In Press date: 1 September 2020
e-pub ahead of print date: 1 October 2020
Published date: November 2020
Keywords: Memristors, modelling, resistive random access memory (RRAM), volatility

Identifiers

Local EPrints ID: 446399
URI: http://eprints.soton.ac.uk/id/eprint/446399
ISSN: 1557-9646
PURE UUID: 078064be-de99-4e3e-8d55-7e3b8abb42f7
ORCID for Spyros Stathopoulos: ORCID iD orcid.org/0000-0002-0833-6209
ORCID for Themistoklis Prodromakis: ORCID iD orcid.org/0000-0002-6267-6909

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Date deposited: 05 Feb 2021 17:33
Last modified: 15 Sep 2021 02:06

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Contributors

Author: Christos Giotis
Author: Alexantrou Serb
Author: Spyros Stathopoulos ORCID iD
Author: Themistoklis Prodromakis ORCID iD

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