Javascript must be enabled to continue!
Controllable Conductance Quantization in Electrochemical Metallization Based Tantalum Oxide Crossbar RRAM Devices
View through CrossRef
<p>In the past decade resistance-based memory devices, or the resistive random access memory Devices (RRAM) have emerged as a potential candidate for multi-state memory storage and non-conventional computing applications. Reports on conduction quantization (QC) have added an interesting layer to the utility of these RRAM devices for ultra-dense memory and neuromorphic computing applications due to the occurrence of integral and half-integral conduction (resistive) states. Since the first reports of QC phenomena in RRAM devices, there have been detailed studies on the nature of the conducting filaments, switching mechanisms, and tunability of the QC states, but there exists a scarcity of studies exploring controllability of QC phenomena in scalable device geometries. In this work, we report compliance current controlled tunable QC phenomena in crossbar RRAM cells based on electrochemical metallization switching mechanism. The devices exhibited robust bipolar resistive switching, with well separated high and low resistance states. The magnitude and number of the QC states were found to increase from ~2.5 to 3.5 and from 4 to 6, respectively as the <em>IC</em> increased from 50 to 200μA. The Cu/Ta2O5/Pt device structure was chosen to strategically govern the metallic nature of the conduction filament (CF) formation, which helped postulating factors contributing to the tunability of the states via compliance current. We report the lateral dimension variability as the main factor governing the magnitude and number of quantized steps observed in RRAM devices, where we also discuss a numerical method to approximate the diameter of the CFs. The increase in number and magnitude of QC steps with IC was explained considering the fact that thicker CF obtained at higher <em>ICC</em>, when undergoes a gradual rupture during reset process, results in larger number of QC steps compared to a thinner CF.</p>
Institute of Electrical and Electronics Engineers (IEEE)
Title: Controllable Conductance Quantization in Electrochemical Metallization Based Tantalum Oxide Crossbar RRAM Devices
Description:
<p>In the past decade resistance-based memory devices, or the resistive random access memory Devices (RRAM) have emerged as a potential candidate for multi-state memory storage and non-conventional computing applications.
Reports on conduction quantization (QC) have added an interesting layer to the utility of these RRAM devices for ultra-dense memory and neuromorphic computing applications due to the occurrence of integral and half-integral conduction (resistive) states.
Since the first reports of QC phenomena in RRAM devices, there have been detailed studies on the nature of the conducting filaments, switching mechanisms, and tunability of the QC states, but there exists a scarcity of studies exploring controllability of QC phenomena in scalable device geometries.
In this work, we report compliance current controlled tunable QC phenomena in crossbar RRAM cells based on electrochemical metallization switching mechanism.
The devices exhibited robust bipolar resistive switching, with well separated high and low resistance states.
The magnitude and number of the QC states were found to increase from ~2.
5 to 3.
5 and from 4 to 6, respectively as the <em>IC</em> increased from 50 to 200μA.
The Cu/Ta2O5/Pt device structure was chosen to strategically govern the metallic nature of the conduction filament (CF) formation, which helped postulating factors contributing to the tunability of the states via compliance current.
We report the lateral dimension variability as the main factor governing the magnitude and number of quantized steps observed in RRAM devices, where we also discuss a numerical method to approximate the diameter of the CFs.
The increase in number and magnitude of QC steps with IC was explained considering the fact that thicker CF obtained at higher <em>ICC</em>, when undergoes a gradual rupture during reset process, results in larger number of QC steps compared to a thinner CF.
</p>.
Related Results
Controllable Conductance Quantization in Electrochemical Metallization Based Tantalum Oxide Crossbar RRAM Devices
Controllable Conductance Quantization in Electrochemical Metallization Based Tantalum Oxide Crossbar RRAM Devices
<p>In the past decade resistance-based memory devices, or the resistive random access memory Devices (RRAM) have emerged as a potential candidate for multi-state memory stora...
Investigation of HfO2 based Resistive Random Access Memory (RRAM) : characterization and modeling of cell reliability and novel access device
Investigation of HfO2 based Resistive Random Access Memory (RRAM) : characterization and modeling of cell reliability and novel access device
Étude des mémoires résistives (RRAM) à base d’HfO2 : caractérisation et modélisation de la fiabilité des cellules mémoire et des nouveaux dispositifs d'accès (Sélecteurs)
...
Observation of Resistive Switching Behavior in Crossbar Core–Shell Ni/NiO Nanowires Memristor
Observation of Resistive Switching Behavior in Crossbar Core–Shell Ni/NiO Nanowires Memristor
AbstractThe crossbar structure of resistive random access memory (RRAM) is the most promising technology for the development of ultrahigh‐density devices for future nonvolatile mem...
Recycling of Composite Metallic Coatings
Recycling of Composite Metallic Coatings
Recycling of bimetallic composite coatings presents challenging opportunities as both the alloy substrates and coatings contain valuable resources for recovery and reuse. Several c...
Exploring the Impact of Variability in Resistance Distributions of RRAM on the Prediction Accuracy of Deep Learning Neural Networks
Exploring the Impact of Variability in Resistance Distributions of RRAM on the Prediction Accuracy of Deep Learning Neural Networks
In this work, we explore the use of the resistive random access memory (RRAM) device as a synapse for mimicking the trained weights linking neurons in a deep learning neural networ...
Interfacial thermal conductance of gallium nitride/graphene/diamond heterostructure based on molecular dynamics simulation
Interfacial thermal conductance of gallium nitride/graphene/diamond heterostructure based on molecular dynamics simulation
<sec>Gallium nitride chips are widely used in high-frequency and high-power devices. However, thermal management is a serious challenge for gallium nitride devices. To improv...
Total hip arthroplasty with tantalum rod extraction via direct anterior approach based on preoperative DCE-MRI and AI: a case report
Total hip arthroplasty with tantalum rod extraction via direct anterior approach based on preoperative DCE-MRI and AI: a case report
Introduction and importance:
Osteonecrosis of the femoral head (ONFH) is a debilitating condition characterized by compromised blood supply to the femoral head, leading...
Resistive Switching Devices for Neuromorphic Computing: From Foundations to Chip Level Innovations
Resistive Switching Devices for Neuromorphic Computing: From Foundations to Chip Level Innovations
Neuromorphic computing has emerged as an alternative computing paradigm to address the increasing computing needs for data-intensive applications. In this context, resistive random...

