Time series modeling of the cycle-to-cycle variability in h-BN based memristors

J. B. Roldán; D. Maldonado; F. J. Alonso; A. M. Roldán; F. Hui; Y. Shi; F. Jiménez-Molinos; A.M. Aguilera; Mario Lanza

doi:10.1109/IRPS46558.2021.9405100

Time series modeling of the cycle-to-cycle variability in h-BN based memristors

J. B. Roldán, D. Maldonado, F. J. Alonso, A. M. Roldán, F. Hui, Y. Shi, F. Jiménez-Molinos, A.M. Aguilera, Mario Lanza

Physical Sciences and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Scopus citations

Abstract

We have characterized and modeled memristor devices based on the Au/Ti/multilayer h-BN/Au/Ti stack. Resistive switching (RS) operation has been analysed by extracting the reset and set voltages and currents. The evolution of the set and reset parameters along a RS series was mathematically modeled in a cycle-to-cycle (CTC) basis by means of the Time Series Analysis (TSA). To do so, the Autocorrelation Functions (ACF) and the Partial Autocorrelation Functions (PACF) have been calculated. These tools help to perform a comprehensive variability study and to obtain the corresponding analytical models within the TSA context. Finally, we have included this modeling procedure in a complete compact model such as the Stanford to be able to account for this variability at the circuit level. Experimental current versus voltage (I- V) curves have been correctly fitted with the model.

Original language	English (US)
Title of host publication	2021 IEEE International Reliability Physics Symposium (IRPS)
Publisher	IEEE
ISBN (Print)	978-1-7281-6894-4
DOIs	https://doi.org/10.1109/IRPS46558.2021.9405100
State	Published - 2021

Bibliographical note

KAUST Repository Item: Exported on 2021-04-28
Acknowledgements: We thank the Spanish Ministry of Science for project TEC2017-84321-C4-3-R, MTM2017-88708-P, PGC2018-098860-B-I00 and Junta de Andalucía for projects A-TIC-117-UGR18 and A-FQM345-UGR18 all with the support of the European Regional Development Fund. We also thank NSFC (61874075), MOST (BRICS2018-211-2DNEURO) and the Ministry of Finance of China (SX21400213).

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@inproceedings{dc0eb76b673542738795013a078e4f22,

title = "Time series modeling of the cycle-to-cycle variability in h-BN based memristors",

abstract = "We have characterized and modeled memristor devices based on the Au/Ti/multilayer h-BN/Au/Ti stack. Resistive switching (RS) operation has been analysed by extracting the reset and set voltages and currents. The evolution of the set and reset parameters along a RS series was mathematically modeled in a cycle-to-cycle (CTC) basis by means of the Time Series Analysis (TSA). To do so, the Autocorrelation Functions (ACF) and the Partial Autocorrelation Functions (PACF) have been calculated. These tools help to perform a comprehensive variability study and to obtain the corresponding analytical models within the TSA context. Finally, we have included this modeling procedure in a complete compact model such as the Stanford to be able to account for this variability at the circuit level. Experimental current versus voltage (I- V) curves have been correctly fitted with the model.",

author = "Rold{\'a}n, {J. B.} and D. Maldonado and Alonso, {F. J.} and Rold{\'a}n, {A. M.} and F. Hui and Y. Shi and F. Jim{\'e}nez-Molinos and A.M. Aguilera and Mario Lanza",

note = "KAUST Repository Item: Exported on 2021-04-28 Acknowledgements: We thank the Spanish Ministry of Science for project TEC2017-84321-C4-3-R, MTM2017-88708-P, PGC2018-098860-B-I00 and Junta de Andaluc{\'i}a for projects A-TIC-117-UGR18 and A-FQM345-UGR18 all with the support of the European Regional Development Fund. We also thank NSFC (61874075), MOST (BRICS2018-211-2DNEURO) and the Ministry of Finance of China (SX21400213).",

year = "2021",

doi = "10.1109/IRPS46558.2021.9405100",

language = "English (US)",

isbn = "978-1-7281-6894-4",

booktitle = "2021 IEEE International Reliability Physics Symposium (IRPS)",

publisher = "IEEE",

}

TY - GEN

T1 - Time series modeling of the cycle-to-cycle variability in h-BN based memristors

AU - Roldán, J. B.

AU - Maldonado, D.

AU - Alonso, F. J.

AU - Roldán, A. M.

AU - Hui, F.

AU - Shi, Y.

AU - Jiménez-Molinos, F.

AU - Aguilera, A.M.

AU - Lanza, Mario

N1 - KAUST Repository Item: Exported on 2021-04-28 Acknowledgements: We thank the Spanish Ministry of Science for project TEC2017-84321-C4-3-R, MTM2017-88708-P, PGC2018-098860-B-I00 and Junta de Andalucía for projects A-TIC-117-UGR18 and A-FQM345-UGR18 all with the support of the European Regional Development Fund. We also thank NSFC (61874075), MOST (BRICS2018-211-2DNEURO) and the Ministry of Finance of China (SX21400213).

PY - 2021

Y1 - 2021

N2 - We have characterized and modeled memristor devices based on the Au/Ti/multilayer h-BN/Au/Ti stack. Resistive switching (RS) operation has been analysed by extracting the reset and set voltages and currents. The evolution of the set and reset parameters along a RS series was mathematically modeled in a cycle-to-cycle (CTC) basis by means of the Time Series Analysis (TSA). To do so, the Autocorrelation Functions (ACF) and the Partial Autocorrelation Functions (PACF) have been calculated. These tools help to perform a comprehensive variability study and to obtain the corresponding analytical models within the TSA context. Finally, we have included this modeling procedure in a complete compact model such as the Stanford to be able to account for this variability at the circuit level. Experimental current versus voltage (I- V) curves have been correctly fitted with the model.

AB - We have characterized and modeled memristor devices based on the Au/Ti/multilayer h-BN/Au/Ti stack. Resistive switching (RS) operation has been analysed by extracting the reset and set voltages and currents. The evolution of the set and reset parameters along a RS series was mathematically modeled in a cycle-to-cycle (CTC) basis by means of the Time Series Analysis (TSA). To do so, the Autocorrelation Functions (ACF) and the Partial Autocorrelation Functions (PACF) have been calculated. These tools help to perform a comprehensive variability study and to obtain the corresponding analytical models within the TSA context. Finally, we have included this modeling procedure in a complete compact model such as the Stanford to be able to account for this variability at the circuit level. Experimental current versus voltage (I- V) curves have been correctly fitted with the model.

UR - http://hdl.handle.net/10754/668984

UR - https://ieeexplore.ieee.org/document/9405100/

U2 - 10.1109/IRPS46558.2021.9405100

DO - 10.1109/IRPS46558.2021.9405100

M3 - Conference contribution

SN - 978-1-7281-6894-4

BT - 2021 IEEE International Reliability Physics Symposium (IRPS)

PB - IEEE

ER -

Time series modeling of the cycle-to-cycle variability in h-BN based memristors

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