Kinetic Monte Carlo Analysis of the Operation and Reliability of Oxide Based RRAMs

Toufik Sadi; Oves Badami; Vihar Georgiev; Asen Asenov

doi:10.1007/978-3-030-41032-2_49

Kinetic Monte Carlo Analysis of the Operation and Reliability of Oxide Based RRAMs

Toufik Sadi^*, Oves Badami, Vihar Georgiev, Asen Asenov

^*Corresponding author for this work

Department of Neuroscience and Biomedical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

Abstract

By using a stochastic simulation model based on the kinetic Monte Carlo approach, we study the physics, operation and reliability of resistive random-access memory (RRAM) devices based on oxides, including silicon-rich silica (SiO) and hafnium oxide – HfO – a widely used transition metal oxide. The interest in RRAM technology has been increasing steadily in the last ten years, as it is widely viewed as the next generation of non-volatile memory devices. The simulation procedure describes self-consistently electronic charge and thermal transport effects in the three-dimensional (3D) space, allowing the study of the dynamics of conductive filaments responsible for switching. We focus on the study of the reliability of these devices, by specifically looking into how oxygen deficiency in the system affects the switching efficiency.

Original language	English
Title of host publication	Large-Scale Scientific Computing - 12th International Conference, LSSC 2019, Revised Selected Papers
Editors	Ivan Lirkov, Svetozar Margenov
Pages	429-437
Number of pages	9
DOIs	https://doi.org/10.1007/978-3-030-41032-2_49
Publication status	Published - 1 Jan 2020
MoE publication type	A4 Article in a conference publication
Event	International Conference on Large-Scale Scientific Computing - Sozopol, Bulgaria Duration: 10 Jun 2019 → 14 Jun 2019 Conference number: 12

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11958 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference on Large-Scale Scientific Computing
Abbreviated title	LSSC
Country/Territory	Bulgaria
City	Sozopol
Period	10/06/2019 → 14/06/2019

Keywords

Kinetic Monte Carlo
Nano-devices
RRAM reliability
Transport phenomena

Access to Document

10.1007/978-3-030-41032-2_49

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Sadi, T., Badami, O., Georgiev, V., & Asenov, A. (2020). Kinetic Monte Carlo Analysis of the Operation and Reliability of Oxide Based RRAMs. In I. Lirkov, & S. Margenov (Eds.), Large-Scale Scientific Computing - 12th International Conference, LSSC 2019, Revised Selected Papers (pp. 429-437). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11958 LNCS). https://doi.org/10.1007/978-3-030-41032-2_49

Sadi, Toufik ; Badami, Oves ; Georgiev, Vihar ; Asenov, Asen. / Kinetic Monte Carlo Analysis of the Operation and Reliability of Oxide Based RRAMs. Large-Scale Scientific Computing - 12th International Conference, LSSC 2019, Revised Selected Papers. editor / Ivan Lirkov ; Svetozar Margenov. 2020. pp. 429-437 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Kinetic Monte Carlo Analysis of the Operation and Reliability of Oxide Based RRAMs",

abstract = "By using a stochastic simulation model based on the kinetic Monte Carlo approach, we study the physics, operation and reliability of resistive random-access memory (RRAM) devices based on oxides, including silicon-rich silica (SiO) and hafnium oxide – HfO – a widely used transition metal oxide. The interest in RRAM technology has been increasing steadily in the last ten years, as it is widely viewed as the next generation of non-volatile memory devices. The simulation procedure describes self-consistently electronic charge and thermal transport effects in the three-dimensional (3D) space, allowing the study of the dynamics of conductive filaments responsible for switching. We focus on the study of the reliability of these devices, by specifically looking into how oxygen deficiency in the system affects the switching efficiency.",

keywords = "Kinetic Monte Carlo, Nano-devices, RRAM reliability, Transport phenomena",

author = "Toufik Sadi and Oves Badami and Vihar Georgiev and Asen Asenov",

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editor = "Ivan Lirkov and Svetozar Margenov",

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Sadi, T, Badami, O, Georgiev, V & Asenov, A 2020, Kinetic Monte Carlo Analysis of the Operation and Reliability of Oxide Based RRAMs. in I Lirkov & S Margenov (eds), Large-Scale Scientific Computing - 12th International Conference, LSSC 2019, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11958 LNCS, pp. 429-437, International Conference on Large-Scale Scientific Computing, Sozopol, Bulgaria, 10/06/2019. https://doi.org/10.1007/978-3-030-41032-2_49

Kinetic Monte Carlo Analysis of the Operation and Reliability of Oxide Based RRAMs. / Sadi, Toufik; Badami, Oves; Georgiev, Vihar; Asenov, Asen.

Large-Scale Scientific Computing - 12th International Conference, LSSC 2019, Revised Selected Papers. ed. / Ivan Lirkov; Svetozar Margenov. 2020. p. 429-437 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11958 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

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T1 - Kinetic Monte Carlo Analysis of the Operation and Reliability of Oxide Based RRAMs

AU - Sadi, Toufik

AU - Badami, Oves

AU - Georgiev, Vihar

AU - Asenov, Asen

N1 - Conference code: 12

PY - 2020/1/1

Y1 - 2020/1/1

N2 - By using a stochastic simulation model based on the kinetic Monte Carlo approach, we study the physics, operation and reliability of resistive random-access memory (RRAM) devices based on oxides, including silicon-rich silica (SiO) and hafnium oxide – HfO – a widely used transition metal oxide. The interest in RRAM technology has been increasing steadily in the last ten years, as it is widely viewed as the next generation of non-volatile memory devices. The simulation procedure describes self-consistently electronic charge and thermal transport effects in the three-dimensional (3D) space, allowing the study of the dynamics of conductive filaments responsible for switching. We focus on the study of the reliability of these devices, by specifically looking into how oxygen deficiency in the system affects the switching efficiency.

AB - By using a stochastic simulation model based on the kinetic Monte Carlo approach, we study the physics, operation and reliability of resistive random-access memory (RRAM) devices based on oxides, including silicon-rich silica (SiO) and hafnium oxide – HfO – a widely used transition metal oxide. The interest in RRAM technology has been increasing steadily in the last ten years, as it is widely viewed as the next generation of non-volatile memory devices. The simulation procedure describes self-consistently electronic charge and thermal transport effects in the three-dimensional (3D) space, allowing the study of the dynamics of conductive filaments responsible for switching. We focus on the study of the reliability of these devices, by specifically looking into how oxygen deficiency in the system affects the switching efficiency.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Large-Scale Scientific Computing - 12th International Conference, LSSC 2019, Revised Selected Papers

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Sadi T, Badami O, Georgiev V, Asenov A. Kinetic Monte Carlo Analysis of the Operation and Reliability of Oxide Based RRAMs. In Lirkov I, Margenov S, editors, Large-Scale Scientific Computing - 12th International Conference, LSSC 2019, Revised Selected Papers. 2020. p. 429-437. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-41032-2_49

Kinetic Monte Carlo Analysis of the Operation and Reliability of Oxide Based RRAMs

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