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@ARTICLE{Wiefels:889691,
author = {Wiefels, Stefan and Bengel, Christopher and Kopperberg,
Nils and Zhang, Kaihua and Waser, Rainer and Menzel,
Stephan},
title = {{HRS} {I}nstability in {O}xide-{B}ased {B}ipolar
{R}esistive {S}witching {C}ells},
journal = {IEEE transactions on electron devices},
volume = {67},
number = {10},
issn = {1557-9646},
address = {New York, NY},
publisher = {IEEE},
reportid = {FZJ-2021-00315},
pages = {4208 - 4215},
year = {2020},
note = {Kein post-print verfügbar},
abstract = {One of the key challenges in the reliability of valence
change [valence change-based memory (VCM)] resistive
switching random access memories (ReRAMs) is the short-term
instability of the programed state. Due to read noise,
program verify or shaping algorithms are ineffective and
read current (or resistance) distributions always revert to
their intrinsic statistics. In this work, we analyze the
instability of the high resistive state (HRS) measured on
ZrO 2 -based devices via Factorial Hidden Markov Models. The
extracted current jumps are explained by distinct ionic
jumps via physics-based kinetic Monte Carlo (KMC) models.
The simulation results reveal jumps of oxygen vacancies from
the densely packed filament (plug) region to a sparsely
packed gap (disc) region as origin of the most critical,
large current jumps. These findings are used to extend our
compact model (JART v1b) by a read noise module. We
demonstrate simulated HRS instability in excellent agreement
with our experimental data. Whereas the KMC approach
provides a physical understanding of the processes
underlying the HRS instability, the compact model enables
the simulation of read noise up to industrially relevant
array scales.},
cin = {PGI-7 / PGI-10 / JARA-FIT / JARA-HPC},
ddc = {620},
cid = {I:(DE-Juel1)PGI-7-20110106 / I:(DE-Juel1)PGI-10-20170113 /
$I:(DE-82)080009_20140620$ / $I:(DE-82)080012_20140620$},
pnm = {521 - Controlling Electron Charge-Based Phenomena
(POF3-521) / Modelling the Valency Change Memory Effect in
Resistive Switching Random Access Memory (RRAM).
$(jpgi70_20200501)$ / BMBF-16ES1134 - Verbundprojekt:
Neuro-inspirierte Technologien der künstlichen Intelligenz
für die Elektronik der Zukunft - NEUROTEC - (BMBF-16ES1134)
/ Verbundprojekt: Neuro-inspirierte Technologien der
künstlichen Intelligenz für die Elektronik der Zukunft -
NEUROTEC -, Teilvorhaben: Forschungszentrum Jülich
(16ES1133K) / Advanced Computing Architectures
$(aca_20190115)$},
pid = {G:(DE-HGF)POF3-521 / $G:(DE-Juel1)jpgi70_20200501$ /
G:(DE-82)BMBF-16ES1134 / G:(BMBF)16ES1133K /
$G:(DE-Juel1)aca_20190115$},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000572635400044},
doi = {10.1109/TED.2020.3018096},
url = {https://juser.fz-juelich.de/record/889691},
}