Oxygen-modulated quantum conductance for ultrathin 
<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi mathvariant="normal">HfO</mml:mi><mml:mn>2</mml:mn></mml:msub></mml:math>
-based memristive switching devices

Zhong, Xiaoliang; Rungger, Ivan; Zapol, Peter; Heinonen, Olle

doi:10.1103/physrevb.94.165160

Cited by 15 publications

(14 citation statements)

References 24 publications

(28 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The existence of half‐integer multiples of G 0 , more frequently observed in VCMs has been suggested to be either due a difference in chemical potential of the electrodes sometimes related to the symmetry (β) of voltage drop or due to the absence of spin degeneracy arising from a weak magnetism in oxygen vacancies . Recent theoretical study also suggests fractional quantum conductance levels in HfO 2 like 0.35 G 0 arising from definitive position of the first and second oxidized vacancy in the filament, which might explain the few conductance steps in between 0.1 G 0 and 0.5 G 0 . Further, the analysis of multiple reset steps during the cf8 reset in t ‐HfO 1.5 , as shown for a few cycles in Figure c also showed the presence of quantized conductance steps up to 10 G 0 .…”

Section: Resultsmentioning

confidence: 97%

Control of Switching Modes and Conductance Quantization in Oxygen Engineered HfO_x based Memristive Devices

Sharath

Vogel

Molina‐Luna

et al. 2017

Adv Funct Materials

107

110

View full text Add to dashboard Cite

Hafnium oxide (HfO x )-based memristive devices have tremendous potential as nonvolatile resistive random access memory (RRAM) and in neuromorphic electronics. Despite its seemingly simple two-terminal structure, a myriad of RRAM devices reported in the rapidly growing literature exhibit rather complex resistive switching behaviors. Using Pt/HfO x /TiN-based metal-insulator-metal structures as model systems, it is shown that a well-controlled oxygen stoichiometry governs the filament formation and the occurrence of multiple switching modes. The oxygen vacancy concentration is found to be the key factor in manipulating the balance between electric field and Joule heating during formation, rupture (reset), and reformation (set) of the conductive filaments in the dielectric. In addition, the engineering of oxygen vacancies stabilizes atomic size filament constrictions exhibiting integer and half-integer conductance quantization at room temperature during set and reset. Identifying the materials conditions of different switching modes and conductance quantization contributes to a unified switching model correlating structural and functional properties of RRAM materials. The possibility to engineer the oxygen stoichiometry in HfO x will allow creating quantum point contacts with multiple conductance quanta as a first step toward multilevel memristive quantum devices.

show abstract

Section: Resultsmentioning

confidence: 97%

Control of Switching Modes and Conductance Quantization in Oxygen Engineered HfO_x based Memristive Devices

Sharath

Vogel

Molina‐Luna

et al. 2017

Adv Funct Materials

107

110

View full text Add to dashboard Cite

show abstract

“…Nonlinear effects in HfO 2 were also reported by Degraeve et al [ 152 ] and in CeO x /SiO 2 -based structures by Miranda et al [ 153 ]. From the point of view of theory, it is worth mentioning that the CF formation in monoclinic- and amorphous-HfO 2 was investigated from first principles by Cartoixa et al [ 154 ] and by Zhong et al [ 155 ]. The filamentary paths are built from oxygen vacancies and using a Green’s function formalism coupled to a density functional theory code, the conductance of filaments of different lengths was calculated.…”

Section: Rram Quantum Point Contact Modeling Thermal Effectsmentioning

confidence: 99%

On the Thermal Models for Resistive Random Access Memory Circuit Simulation

et al. 2021

View full text Add to dashboard Cite

Resistive Random Access Memories (RRAMs) are based on resistive switching (RS) operation and exhibit a set of technological features that make them ideal candidates for applications related to non-volatile memories, neuromorphic computing and hardware cryptography. For the full industrial development of these devices different simulation tools and compact models are needed in order to allow computer-aided design, both at the device and circuit levels. Most of the different RRAM models presented so far in the literature deal with temperature effects since the physical mechanisms behind RS are thermally activated; therefore, an exhaustive description of these effects is essential. As far as we know, no revision papers on thermal models have been published yet; and that is why we deal with this issue here. Using the heat equation as the starting point, we describe the details of its numerical solution for a conventional RRAM structure and, later on, present models of different complexity to integrate thermal effects in complete compact models that account for the kinetics of the chemical reactions behind resistive switching and the current calculation. In particular, we have accounted for different conductive filament geometries, operation regimes, filament lateral heat losses, the use of several temperatures to characterize each conductive filament, among other issues. A 3D numerical solution of the heat equation within a complete RRAM simulator was also taken into account. A general memristor model is also formulated accounting for temperature as one of the state variables to describe electron device operation. In addition, to widen the view from different perspectives, we deal with a thermal model contextualized within the quantum point contact formalism. In this manner, the temperature can be accounted for the description of quantum effects in the RRAM charge transport mechanisms. Finally, the thermometry of conducting filaments and the corresponding models considering different dielectric materials are tackled in depth.

show abstract

“…As schematically illustrated in Fig. 2.b, the opening (RESET) or closing (SET) of the atom chain raises or lowers the top of the confinement barrier for the electron flow [21,22]. According to this picture, ballistic transport would not be required along the whole filament structure but just at the narrowest section of the constriction.…”

Section: I) Current-voltage Characteristicmentioning

confidence: 99%

Fundamentals and SPICE Implementation of the Dynamic Memdiode Model for Bipolar Resistive Switching Devices

Miranda¹,

Suñé²

2020

Preprint

View full text Add to dashboard Cite

show abstract

Oxygen-modulated quantum conductance for ultrathin HfO2 -based memristive switching devices

Cited by 15 publications

References 24 publications

Control of Switching Modes and Conductance Quantization in Oxygen Engineered HfO_x based Memristive Devices

Control of Switching Modes and Conductance Quantization in Oxygen Engineered HfO_x based Memristive Devices

On the Thermal Models for Resistive Random Access Memory Circuit Simulation

Fundamentals and SPICE Implementation of the Dynamic Memdiode Model for Bipolar Resistive Switching Devices

Contact Info

Product

Resources

About

Oxygen-modulated quantum conductance for ultrathin HfO2 -based memristive switching devices

Cited by 15 publications

References 24 publications

Control of Switching Modes and Conductance Quantization in Oxygen Engineered HfOx based Memristive Devices

Control of Switching Modes and Conductance Quantization in Oxygen Engineered HfOx based Memristive Devices

On the Thermal Models for Resistive Random Access Memory Circuit Simulation

Fundamentals and SPICE Implementation of the Dynamic Memdiode Model for Bipolar Resistive Switching Devices

Contact Info

Product

Resources

About

Control of Switching Modes and Conductance Quantization in Oxygen Engineered HfO_x based Memristive Devices

Control of Switching Modes and Conductance Quantization in Oxygen Engineered HfO_x based Memristive Devices