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DIGITAL.CSIC
Article . 2024 . Peer-reviewed
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Effects of the voltage ramp rate on the conduction characteristics of HfO2-based resistive switching devices

Authors: H García; G Vinuesa; E García-Ochoa; F L Aguirre; M B González; F Jiménez-Molinos; F Campabadal; +4 Authors

Effects of the voltage ramp rate on the conduction characteristics of HfO2-based resistive switching devices

Abstract

Abstract Memristive devices have shown a great potential for non-volatile memory circuits and neuromorphic computing. For both applications it is essential to know the physical mechanisms behind resistive switching; in particular, the time response to external voltage signals. To shed light in these issues we have studied the role played by the applied voltage ramp rate in the electrical properties of TiN/Ti/HfO2/W metal–insulator–metal resistive switching devices. Using an ad hoc experimental set-up, the current–voltage characteristics were measured for ramp rates ranging from 100 mV s−1–1 MV s−1. These measurements were used to investigate in detail the set and reset transitions. It is shown that the highest ramp rates allow controlling the resistance values corresponding to the intermediate states at the very beginning of the reset process, which is not possible by means of standard quasistatic techniques. Both the set and reset voltages increase with the ramp rate because the oxygen vacancies movement is frequency dependent so that, when the ramp rate is high enough, the conductive filaments neither fully form nor dissolve. In agreement with Chua’s theory of memristive devices, this effect causes the device resistance window to decrease as the ramp rate increases, and even to vanish for very high ramp rates. Remarkably, we demonstrate that the voltage ramp rate can be straightforwardly used to control the conductance change of the switching devices, which opens up a new way to program the synaptic weights when using these devices to mimic synapses for neuromorphic engineering applications. Moreover, the data obtained have been compared with the predictions of the dynamic memdiode model.

Country
Spain
Keywords

Memdiode model, 2203 Electrónica, Resistive switching, 3307.90 Microelectrónica, Memristor, Electrical characterization

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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11
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31
15
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