Search results for "memristors"
showing 8 items of 8 documents
Electrochemical polymerization of ambipolar carbonyl-functionalized indenofluorene with memristive properties
2019
Abstract Carbonyl-functionalized indenofluorene was electropolymerized with a high faradaic efficiency of 85% and the solid state properties of the resulting polymeric thin films were investigated. They displayed modular optical properties depending on their oxidation state. The approach used for inorganic semiconductors was applied to polyindeonofluorene derivative. Mott-Schottky analysis evidenced a switching from p-type to n-type electrical conduction, suggesting an ambipolar behaviour of the polymer. As an application, flexible organic memristors were fabricated and resistive switching properties were observed.
Theory of Heterogeneous Circuits With Stochastic Memristive Devices
2022
We introduce an approach based on the Chapman-Kolmogorov equation to model heterogeneous stochastic circuits, namely, the circuits combining binary or multi-state stochastic memristive devices and continuum reactive components (capacitors and/or inductors). Such circuits are described in terms of occupation probabilities of memristive states that are functions of reactive variables. As an illustrative example, the series circuit of a binary memristor and capacitor is considered in detail. Some analytical solutions are found. Our work offers a novel analytical/numerical tool for modeling complex stochastic networks, which may find a broad range of applications.
Modeling Networks of Probabilistic Memristors in SPICE
2021
Efficient simulation of stochastic memristors and their networks requires novel modeling approaches. Utilizing a master equation to find occupation probabilities of network states is a recent major departure from typical memristor modeling [Chaos, solitons fractals 142, 110385 (2021)]. In the present article we show how to implement such master equations in SPICE – a general purpose circuit simulation program. In the case studies we simulate the dynamics of acdriven probabilistic binary and multi-state memristors, and dc-driven networks of probabilistic binary and multi-state memristors. Our SPICE results are in perfect agreement with known analytical solutions. Examples of LTspice code are…
Probabilistic Memristive Networks: Application of a Master Equation to Networks of Binary ReRAM cells
2020
Abstract The possibility of using non-deterministic circuit components has been gaining significant attention in recent years. The modeling and simulation of their circuits require novel approaches, as now the state of a circuit at an arbitrary moment in time cannot be predicted deterministically. Generally, these circuits should be described in terms of probabilities, the circuit variables should be calculated on average, and correlation functions should be used to explore interrelations among the variables. In this paper, we use, for the first time, a master equation to analyze the networks composed of probabilistic binary memristors. Analytical solutions of the master equation for the ca…
Resistive switching behaviour in ZnO and VO 2 memristors grown by pulsed laser deposition
2014
The resistive switching behaviour observed in microscale memristors based on laser ablated ZnO and VO 2 is reported. A comparison between the two materials is reported against an active device size. The results show that devices up to 300 × 300 μm 2 exhibit a memristive behaviour regardless of the device size, and 100 × 100 μm 2 ZnO-based memristors have the best resistance off/on ratio.
Modeling Networks of Probabilistic Memristors in SPICE
2021
Efficient simulation of stochastic memristors and their networks requires novel modeling approaches. Utilizing a master equation to find occupation probabilities of network states is a recent major departure from typical memristor modeling [Chaos, solitons fractals 142, 110385 (2021)]. In the present article we show how to implement such master equations in SPICE – a general purpose circuit simulation program. In the case studies we simulate the dynamics of acdriven probabilistic binary and multi-state memristors, and dc-driven networks of probabilistic binary and multi-state memristors. Our SPICE results are in perfect agreement with known analytical solutions. Examples of LTspice code are…
Fabrication and characterization of micrometer-scale ZnO memristors
2015
Memristors are an interesting class of resistive random access memory (RRAM) based on the electrical switching of metal oxide film resistivity . They are characterized for exhibiting resistive switching between a high-resistance state (HRS) and a low-resistance state (LRS) and have been recently considered as one of the most promising candidates for next-generation nonvolatile memory devices because of their low power consumption, fast switching operation, nondestructive readout, and remarkable scalability. The device structure is simply an oxide layer sandwiched between two metal electrodes. The switching behaviour is dependent both on the oxide material and the choice of metal electrodes.…
Importance of the Window Function Choice for the Predictive Modelling of Memristors
2021
Window functions are widely employed in memristor models to restrict the changes of the internal state variables to specified intervals. Here, we show that the actual choice of window function is of significant importance for the predictive modelling of memristors. Using a recently formulated theory of memristor attractors, we demonstrate that whether stable fixed points exist depends on the type of window function used in the model. Our main findings are formulated in terms of two memristor attractor theorems, which apply to broad classes of memristor models. As an example of our findings, we predict the existence of stable fixed points in Biolek window function memristors and their absenc…