Design and modeling of niobium oxide-tantalum oxide based self-selective memristor for large-scale crossbar memory

Parit, Aditya Kuber; Yadav, Mani Shankar; Gupta, Alok K.; Mikhaylov, A. N.; Rawat, Brajesh

doi:10.1016/j.chaos.2021.110818

Cited by 18 publications

(16 citation statements)

References 30 publications

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“…With advantages that include compatibility with CMOS and resistive instead of capacitive reading, memristors are frontrunners in the new generation of resistive random-access memory (RRAM) technology. High memory density, endurance, retention and low power consumption are some of the characteristics which can justify the possibility of memristors being used as an ultimate element for neuromorphic computing [ 2 ], in logic circuit applications [ 3 ], Recently, valve metals in their oxidized forms [ 4 , 5 ] have drawn scientific attention as memristive materials. The switching mechanism of memristive devices depends on the formation of conductive filaments (CFs) inside the insulating layer, which is the oxide sandwiched between two metallic electrodes [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

Impact of Electrolyte Incorporation in Anodized Niobium on Its Resistive Switching

et al. 2022

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The aim of this study was to develop memristors based on Nb2O5 grown by a simple and inexpensive electrochemical anodization process. It was confirmed that the electrolyte selection plays a crucial role in resistive switching due to electrolyte species incorporation in oxide, thus influencing the formation of conductive filaments. Anodic memristors grown in phosphate buffer showed improved electrical characteristics, while those formed in citrated buffer exhibited excellent memory capabilities. The chemical composition of oxides was successfully determined using HAXPES, while their phase composition and crystal structure with conductive filaments was assessed by TEM at the nanoscale. Overall, understanding the switching mechanism leads towards a wide range of possible applications for Nb memristors either as selector devices or nonvolatile memories.

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Section: Introductionmentioning

confidence: 99%

Impact of Electrolyte Incorporation in Anodized Niobium on Its Resistive Switching

et al. 2022

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“…The maximum switching currents for SET and RESET transitions are around 477 µA and 284 µA, respectively. The memristor has a sneak current of around 72 µA, a selectivity (S) of around 4.02 (S = (I on ) V read /(I o f f ) V read/2 ), and an on-off current ratio of around 1.55 for the V/2 biasing scheme [17]. Thus, the CFbased memristor has a lower selectivity or nonlinearity, and integration of the switching layer is much needed for a realistic crossbar array realization.…”

Section: Resultsmentioning

confidence: 99%

“…1(b) summarizes the developed multi-scale modeling approach. Firstly, the material attributes of NbO 2 and Nb 2 O 5−x are acquired from reported experimental data [15], [17]- [19]. Subsequently, these material attributes are used to develop a fully coupled multi-physics simulator for understanding the switching properties of niobium-oxide devices.…”

Section: Memristor Geometry and Modeling Approachmentioning

confidence: 99%

“…In general, the threshold switching effect in NbO 2 is attributed to the IMT that occurs at around 1081 K temperature [17], [20]. However, the thermal conductance-based model (σ as a function of T) exhibits major conflicts in comparison to the experimental findings as the internal device temperature is found to be well below the IMT transition temperature during switching [15].…”

Section: A Modeling Of Switching Properties Of Nbo 2 Layermentioning

confidence: 99%

“…Interestingly, NbO 2 /Nb 2 O 5−x -based self-selective memristors have demonstrated excellent performance with high current density and high on/off current ratio [15], [16]. Even though several recent efforts have been devoted to the understanding of the underlying switching mechanism in NbO 2 /Nb 2 O 5−x based self-selective memristor [15], [17], crossbar-level performance analysis remains unexplored. Therefore, more efforts on crossbar-level performance analysis are required to expand their usage in memory and neuromorphic system design.…”

Section: Introductionmentioning

confidence: 99%

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Device-Circuit Co-design of Memristor-based on Niobium Oxide for Large-Scale Crossbar Memory

Kumar¹,

Yadav²,

Rawat³

2022

Preprint

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Memristor-based crossbar architecture emerges as a promising candidate for 3-D memory and neuromorphic computing; however, the sneak current through the unselected cells becomes a fundamental roadblock for their development as it results in misreading and high power consumption. In this regard, we investigate Pt/Ti/NbO2/Nb2O5−x/Pt-based self-selective memristor, which combines inherent nonlinearity of NbO2 switching layer and non-volatile operation of Nb2O5−x memory layer in a single device. The results show that Pt/Ti/NbO2/Nb2O5−x/Pt memristor offers the sneak current of 310 nA, selectivity of around 174, and on/off current ratio of 4.79 compared to the sneak current of around 70 µA, selectivity of about 4.02, and on/off current ratio of around 1.55 for Pt/Ti/Nb2O5−x/Pt-based memristor. Our self-selective memristor minimizes the sneak current, but a small on/off current ratio limits their readout margin and power efficiency for crossbar array size greater than 212. Further, we demonstrate that breaking down a large-scale crossbar array into smaller subarrays and separating them by transistor switches is a more efficient way of eliminating the sneak current. The memristor-transistor split crossbar architecture essentially provides the readout margin and power efficiency of subarray for large size crossbar array and allows high-density array integration over 1Transistor-1Memristor architecture.

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Forming‐Free Resistive Switching of Electrochemical Titanium Oxide Localized Nanostructures: Anodization, Chemical Composition, Nanoscale Size Effects, and Memristive Storage

Tominov

Avilov

Вакулов

et al. 2022

Adv Elect Materials

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Electrochemical anodization is a powerful method for the preparation of oxide thin films with controlled thickness, structure, and composition and proves as a promising approach to be applied to memristive devices. Here, experimental studies on titanium oxide nanoscale structures produced by local anodic oxidation and the influence of the thickness on the memristive properties are presented. Controllable preparation of forming‐free memristive cells with switching voltages less than 3 V are demonstrated. The chemical composition and oxidation state of the elements in the TiOx nanostructures are analyzed by means of X‐ray photoelectron spectroscopy, which reveals the formation of TiO2 (458.4 eV), Ti2O3 (456.6 eV), and TiO (454.8 eV). The increasing thickness of the devices from 4.5 ± 0.7 to 7.9 ± 0.3 nm leads to a decrease in the OFF to ON resistance ratio from 250 to 10.7, respectively. The mechanism of formation and resistive switching in the anodic devices is also discussed. The results can be applied to the design and development of technological processes for memristive structure manufacturing based on electrochemical oxidation.

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Design and modeling of niobium oxide-tantalum oxide based self-selective memristor for large-scale crossbar memory

Cited by 18 publications

References 30 publications

Impact of Electrolyte Incorporation in Anodized Niobium on Its Resistive Switching

Impact of Electrolyte Incorporation in Anodized Niobium on Its Resistive Switching

Device-Circuit Co-design of Memristor-based on Niobium Oxide for Large-Scale Crossbar Memory

Forming‐Free Resistive Switching of Electrochemical Titanium Oxide Localized Nanostructures: Anodization, Chemical Composition, Nanoscale Size Effects, and Memristive Storage

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