Project

Fluctuation phenomena in multistable memristive systems (StoLab)

Goal: The project is aimed at the application of latest statistical analysis methods in the study of fluctuation phenomena in multistable memristive systems in order to detect and study in detail the constructive role of noise, which will provide an advanced background for creating new generations of electronic devices and neuromorphic technologies of artificial intelligence based on memristive materials.

Research objectives:
1. The study of the influence of external and internal noise on the behavior of multistable systems. Study and analysis of the phenomena with constructive role of noise in multistable systems.
2. Experimental study of the behavior of oxide-based memristive nanostructures in the presence of external and internal noise. Development of an adequate physical memristor macromodel taking into account the influence of external and internal noise and its comparison with the micromodel of physico-chemical phenomena responsible for resistive switching.
3. The study of microscopic nature of the flicker and high-frequency noise in memristive nanostructures.
4. Experimental demonstration of fundamentally new oportunities for increasing stability, predicting the behavior and controlling the parameters of memristive devices in prototypes of emerging electronic devices and neuromorphic systems.

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Project log

Alexey Mikhaylov
added a research item
This work is dedicated to the review and perspective of the new direction that we call "Neuropunk revolution" resembling the cultural phenomenon of cyberpunk. This new phenomenon has its foundations in advances in neuromorphic technologies including memristive and bio-plausible simulations, BCI, and neurointerfaces as well as unconventional approaches to AI and computing in general. We present the review of the current state-of-the-art and our vision of near future development of scientific approaches and future technologies. We call the "Neuropunk revolution" the set of trends that in our view provide the necessary background for the new generation of approaches technologies to integrate the cybernetic objects with biological tissues in close loop system as well as robotic systems inspired by the biological processes again integrated with biological objects. We see bio-plausible simulations implemented by digital computers or spiking networks memristive hardware as promising bridge or middleware between digital and (neuro)biological domains.
Alexey Mikhaylov
added a research item
The results of experimental investigation of the relationship between low-frequency noise spectrum in an electric current through conducting filaments in Si3N4 films with thickness of 6 nm on n++-Si(001) conducting substrates and degradation characteristics of these films are reported. Two structures are investigated: (SN6) Si3N4/SiO2/Si, with 2 nm SiO2 sublayer between the film and substrate; (SN8) similar structure but without SiO2 sublayer. Detailed comparison of the structural parameters, such as average current through the filament, probability density function and spectrum, is presented with discussion of possible physical reasons for the difference between the testing samples and its effect on degradation characteristics.
Alexey Mikhaylov
added 8 research items
We propose a hybrid memristve neuromorphic system for stimulating hippocampus regions bypassing damaged areas. Synaptic plasticity properties of the system allow close-loop adaptive control of neural dynamics. We implement the simplest version of this system which consists of two neuron-like generators coupled by a memristive device, and two fiber-optic channels to transmit signals from the generators directly to living cells to stimulate hippocampus regions. The adaptive stimulation nature of the neural cells is provided by a stochastic response of the self-learning memristive device to the signal of the neuron-like generator. A biological model of impaired functioning of the perforating pathway in the rat hippocampus is implemented by damaging the CA3 region, on the base of the electrophysiological signal changes in normal and pathological conditions. The proposed adaptive stimulation technology demonstrates the possibility of restoring the functionality of the perforating pathway by introducing the neuromorphic system into the hippocampus to replace lost areas.
Here we present the current results of our cross-disciplinary group in the field of design and hardware implementation an artificial neural network based on memristors, which is a component of a bidirectional adaptive neural interface for automatic registration and stimulation of bioelectrical activity of a living neuronal culture. Building bidirectional biointerfaces is one of the key challenges of modern engineering and medicine, with dramatic potential impact on bioprosthetics. In this manner we place a key stepping stone towards building self-adjusting, low-power biointerfaces, themselves a foundational stepping stone towards adaptable, low-power bioprostheses.
Alexey Mikhaylov
added a research item
In this paper, we classify the instantaneous response of resistors with memory into three types: linear (L), separable nonlinear (SN), and non-separable nonlinear (NSN). A particular model of an NSN-type memristive device is introduced and used to demonstrate the possibility of rich dynamics in the memristor-capacitor circuit subjected to a sinusoidal voltage. In particular, our numerical simulations reveal the regimes of double period oscillations, multiple period oscillations, and chaotic oscillations. The comparison with L-type and SN-type memristive devices described by the same differential state equation indicates the importance of the NSN-type response to achieve such complex dynamics in the memristor-capacitor circuit with a first-order memristive device. Moreover, we demonstrate that a compound NSN-type memristive device can be assembled using one L-type memristive device, two resistors, and two diodes. The complex behavior of such compound devices is verified using SPICE modeling.
Alexey Mikhaylov
added a research item
We investigate the constructive role of an external noise signal, in the form of a low-rate Poisson sequence of pulses supplied to all inputs of a spiking neural network, consisting in maintaining for a long time or even recovering a memory trace (engram) of the image without its direct renewal (or rewriting). In particular, this unique dynamic property is demonstrated in a single-layer spiking neural network consisting of simple integrate-and-fire neurons and memristive synaptic weights. This is carried out by preserving and even fine-tuning the conductance values of memristors in terms of dynamic plasticity, specifically spike-timing-dependent plasticity-type, driven by overlapping pre-and postsynaptic voltage spikes. It has been shown that the weights can be to a certain extent unreliable, due to such characteristics as the limited retention time of resistive state or the variation of switching voltages. Such a noise-assisted persistence of memory, on one hand, could be a prototypical mechanism in a biological nervous system and, on the other hand, brings one step closer to the possibility of building reliable spiking neural networks composed of unreliable analog elements.
Alexey Mikhaylov
added a research item
Memristor-based crossbar architecture has emerged as a promising candidate for 3-D memory, logic, and neuromorphic computing system as it offers remarkably high integration density, low power consumption, fast operation, and easy integration with CMOS technology. However, the fundamental obstacle for their development is the sneak current, which causes misreading and write-crosstalk. In this regard, we present the TiN/NbO2/TiN/TaOx/TiN based self-selective memristor by combining the threshold switching properties of niobium oxide (NbO2) and memory switching properties of tantalum oxide (TaOx) in a single device. The performance investigation is carried out using the finite element simulation method, based on self-consistent solutions of joule heating equation, drift-diffusion continuity equation, and current continuity for accurately capturing the temperature and field-dependent transport of vacancies. The results reveal that NbO2-TaOx based self-selective memristor can allow significantly lower OFF current (1.22 μA), higher read window (32.6), and higher non-linearity (141) than that of TiN/TaOx/TiN based memristor. We demonstrate that the self-selective memristor exhibits good speed with the operation time constant of 70 ns. Furthermore, the crossbar array using a self-selective memristor has shown excellent performance with an improved readout margin up to 27 word lines. Our material-to-circuit performance analysis promises a reliable and energy-efficient crossbar array using NbO2-TaOx cell that can be further utilized for implementing 3-D cross-bar array.
Alexey Mikhaylov
added a research item
In this paper we analyze cycle-to-cycle variations in the dynamics of an abstract second-order system with memory whose response involves both resistive and capacitive components. The internal state variables in the model are the filament length and charge accumulated within the device. The dynamics is studied under the condition of periodic driving. Even with the simplest assumptions on the shape of window and capture functions, periodic, intermittent and chaotic dynamical modes are found. Bifurcation diagrams are presented showing the variety of dynamical modes. Our results indicate that the system posses a chaotic attractor in state space, and the transition to chaos occurs via the intermittency scenario. Some analytical results are presented.
Alexey Mikhaylov
added a research item
The stochastic resonance phenomenon has been studied experimentally and theoretically for a state-of-art metal-oxide memristive device based on yttria-stabilized zirconium dioxide and tantalum pentoxide, which exhibits bipolar filamentary resistive switching of anionic type. The effect of white Gaussian noise superimposed on the sub-threshold sinusoidal driving signal is analyzed through the time series statistics of the resistive switching parameters, the spectral response to a periodic perturbation and the signal-to-noise ratio at the output of the nonlinear system. The stabilized resistive switching and the increased memristance response are revealed in the observed regularities at an optimal noise intensity corresponding to the stochastic resonance phenomenon and interpreted using a stochastic memristor model taking into account an external noise source added to the control voltage. The obtained results clearly show that noise and fluctuations can play a constructive role in nonlinear memristive systems far from equilibrium.
Alexey Mikhaylov
added an update
Special Issue on Memristors and Nonequilibrium Stochastic Multistable Systems is announced in a reputable journal of Chaos, Solitons and Fractals with Prof. Bernardo Spagnolo as a Special Issue Managing Guest Editor:
 
Alexey Mikhaylov
added 2 research items
The peculiarities of resistive switching in capacitors with yttria-stabilized hafnia layers were studied. The characteristics of current transport in the initial state and after electroforming and resistive switching at different temperatures were examined. The parameters of a small-signal equivalent circuit of a capacitor were determined for switching into low- and high-resistance states. These parameters suggest that the resistance of filaments changes after each successive switching. This provides an opportunity to use such measurements to determine the nature of resistive switching and verify the reproducibility of its parameters. The contribution of electron traps to switching was revealed. Ion migration polarization was observed at temperatures above 500 K, and the activation energy of ion migration and the ion concentration were determined. The effect of resistive switching under the influence of temperature was observed and interpreted for the first time.
Resistive switching (RS) is studied in a memristor based on a ZrO2(Y)/Ta2O5 stack under a white Gaussian noise voltage signal. We have found that the memristor switches between the low resistance state and the high resistance state in a random telegraphic signal (RTS) mode. The effective potential profile of the memristor shows from two to three local minima and depends on the input noise parameters and the memristor operation. These observations indicate the multiplicative character of the noise on the dynamical behavior of the memristor, that is the noise perceived by the memristor depends on the state of the system and its electrical properties are influenced by the noise signal. The detected effects manifest the fundamental intrinsic properties of the memristor as a multistable nonlinear system.
Alexey Mikhaylov
added a research item
Here we provide a perspective concept of neurohybrid memristive chip based on the combination of living neural networks cultivated in microfluidic/microelectrode system, metal-oxide memristive devices or arrays integrated with mixed-signal CMOS layer to control the analog memristive circuits, process the decoded information, and arrange a feedback stimulation of biological culture as parts of a bidirectional neurointerface. Our main focus is on the state-of-the-art approaches for cultivation and spatial ordering of the network of dissociated hippocampal neuron cells, fabrication of a large-scale crossbar array of memristive devices tailored using device engineering, resistive state programming, or non-linear dynamics, as well as hardware implementation of spiking neural networks (SNNs) based on the arrays of memristive devices and integrated CMOS electronics. The concept represents an example of a brain-on-chip system belonging to a more general class of memristive neurohybrid systems for a new-generation robotics, artificial intelligence, and personalized medicine, discussed in the framework of the proposed roadmap for the next decade period.
Alexey Mikhaylov
added a research item
We propose a stochastic model for a memristive system by generalizing known approaches and experimental results. We validate our theoretical model by experiments carried out on a memristive device based on Au/Ta/ZrO2(Y)/Ta2O5/TiN/Ti multilayer structure. In the framework of the proposed model we obtain the exact analytic expressions for stationary and nonstationary solutions. We analyze the equilibrium and non-equilibrium steady-state distributions of the internal state variable of the memristive system and study the influence of fluctuations on the resistive switching, including the relaxation time to the steady-state. The relaxation time shows a nonmonotonic dependence, with a minimum, on the intensity of the fluctuations. This paves the way for using the intensity of fluctuations as a control parameter for switching dynamics in memristive devices.
Alexey Mikhaylov
added an update
From 18 to 21 of October 2019, the International Conference "New Trends in Nonequilibrium Stochastic Multistable Systems and Memristors - NES2019 (https://nes2019.sciencesconf.org/)" has been successfully held in Italy, which belongs to a course of the International School of Statistical Physics organized by renowned scientists Peter Hänggi and Fabio Marchesoni at the ETTORE MAJORANA FOUNDATION AND CENTRE FOR SCIENTIFIC CULTURE in Erice (Sicily). This event was organized by the Laboratory of Stochastic Multistable Systems (StoLab) of Lobachevsky University in collaboration with the University of Palermo under the direction of Bernardo Spagnolo, Oleg Gorshkov and Davide Valenti in the framework of the megagrant of the Government of the Russian Federation (Agreement No. 074-02-2018-330). While keeping a general focus on the fundamental problems of complex systems, multistability, and the role of noise in nonlinear systems, the present conference for the first time has been addressed to discussion of relevant phenomena in the context of their application for understanding and describing the memristive effect, tailoring the behavior of memristive nanomaterials, devices, and systems. Conference sessions were opened by plenary talks of such recognized leaders of the world memristive community as Sergey Savel'ev (UK), Massimiliano Di Ventra (USA) and Yury Pershin (USA), on new-generation memristor-based neuromorphic and computing systems, as well as on dynamical approach to describe memristive systems. The participants of the event were especially impressed by the invited reports of leading researchers from Germany, Italy, Spain, Greece, South Korea and Russia. The culmination of the event was a special section on the results obtained at the StoLab Laboratory in the framework of the megagrant of the Government of the Russian Federation. A large delegation from Lobachevsky University and partner organizations has demonstrated significant progress at the conference in the field of development and creation of new generations of electronic devices and neuromorphic artificial intelligence technologies based on memristive materials owing to original technological and design solutions, new neural network architectures and the established positive role of both internal and external noise in the devices and systems.
 
Bernardo Spagnolo
added 6 research items
We investigate how the combined effects of strong Ohmic dissipation and monochromatic driving affect the stability of a quantum system with a metastable state. We find that, by increasing the coupling with the environment, the escape time makes a transition from a regime in which it is substantially controlled by the driving, displaying resonant peaks and dips, to a regime of frequency-independent escape time with a peak followed by a steep falloff. The escape time from the metastable state has a nonmonotonic behavior as a function of the thermal-bath coupling, the temperature, and the frequency of the driving. The quantum noise-enhanced stability phenomenon is observed in the investigated system.
The stabilizing effect of quantum fluctuations on the escape process and the relaxation dynamics from a quantum metastable state are investigated. Specifically, the quantum dynamics of a multilevel bistable system coupled to a bosonic Ohmic thermal bath in strong dissipation regime is analyzed. The study is performed by a non-perturbative method based on the real-time path integral approach of the Feynman-Vernon influence functional. We consider a strongly asymmetric double well potential with and without a monochromatic external driving, and with an out-of-equilibrium initial condition. In the absence of driving we observe a nonmonotonic behavior of the escape time from the metastable region, as a function both of the system-bath coupling coefficient and the temperature. This indicates a stabilizing effect of the quantum fluctuations. In the presence of driving our findings indicate that, as the coupling coefficient γ increases, the escape time, initially controlled by the external driving, shows resonant peaks and dips, becoming frequency-independent for higher γ values. Moreover, the escape time from the metastable state displays a nonmonotonic behavior as a function of the temperature, the frequency of the driving, and the thermal-bath coupling, which indicates the presence of a quantum noise enhanced stability phenomenon. Finally, we investigate the role of different spectral densities, both in sub-Ohmic and super-Ohmic dissipation regime and for different cutoff frequencies, on the relaxation dynamics from the quantum metastable state. The results obtained indicate that, in the crossover dynamical regime characterized by damped intrawell oscillations and incoherent tunneling, the spectral properties of the thermal bath influence non-trivially the short time behavior and the time scales of the relaxation dynamics from the metastable state.
In this tutorial paper we present a comprehensive review of the escape dynamics from quantum metastable states in dissipative systems and related noise-induced effects. We analyze the role of dissipation and driving in the escape process from quantum metastable states with and without an external driving force, starting from a nonequilibrium initial condition. We use the Caldeira–Leggett model and a non-perturbative theoretical technique within the Feynman–Vernon influence functional approach in strong dissipation regime. In the absence of driving, we find that the escape time from the metastable region has a nonmonotonic behavior versus the system-bath coupling and the temperature, producing a stabilizing effect in the quantum metastable system. In the presence of an external driving, the escape time from the metastable region has a nonmonotonic behavior as a function of the frequency of the driving, the thermal-bath coupling and the temperature. The quantum noise enhanced stability phenomenon is observed in both systems investigated. Finally, we analyze the resonantly activated escape from a quantum metastable state in the spin-boson model. We find quantum stochastic resonant activation, that is the presence of a minimum in the escape time as a function of the driving frequency. Background and introductory material has been added in the first three sections of the paper to make this tutorial review reasonably self-contained and readable for graduate students and non-specialists from related areas.
Alexey Mikhaylov
added an update
UNN Media-Center about Memristive devices and systems at Lobachevsky University: https://youtu.be/Hr2rTL7nAUo
 
Alexey Mikhaylov
added an update
The head of StoLab Prof. Bernardo Spagnolo and the Project coordinator Dr. Nikolay Agudov took part in the traditional Conference "Science of the Future" and Forum "Science of the Future – Science of the Youth", May 14-17, Sochi, Russia (https://www.sfy-conf.com). The programme included Megagrant Project presentation, round table and important meetings with scientists and officials.
 
Alexey Mikhaylov
added an update
Dear Colleagues,
Below you will find information about the International Conference in Erice kindly provided by its chairman Prof. Bernardo Spagnolo.
"New Trends in Nonequilibrium Stochastic Multistable Systems and Memristors” - NES2019, (https://nes2019.sciencesconf.org/), that will be held at the Ettore Majorana Foundation and Centre for Scientific CultureErice, Italy, in the period of 18-21 October 2019.
The Conference, while focusing on memristors, fits the general context of complex systemsmetastability, and the constructive role of noise in nonlinear systems. The Conference indeed brings together leading experts and research groups, working on the development of memristors as building blocks for quantum and neuromorphic computing, but it is also addressed to scientists interested in the challenging problems connected with the dynamics of nonequilibrium multistable systems and memristor devices, from both theoretical and experimental point of view. The Conference will be a discussion forum to promote new ideas in this promising research field, concerning stochastic nonlinear modelsphase transitions phenomena in memristive devices, the control of memory lifetime, and memcomputing.
The link of the Conference, with all details is https://nes2019.sciencesconf.org/
The registration is open.
Thank you very much for attention.
Best Wishes,
Bernardo Spagnolo
Chairman of the Conference
 
Alexey Mikhaylov
added an update
The useful information is attached about International Conferences and Workshops on the Project theme kindly provided by Prof. Alex Dubkov.
 
Alexey Mikhaylov
added an update
StoLab Logo
 
Alexey Mikhaylov
added a research item
The time dynamics of the spatial distribution of the potential induced by the electrons locally injected from an atomic force microscope (AFM) probe into the ultrathin (< 10 nm thick) yttria stabilized zirconia (YSZ) ZrO2(Y) films with embedded Au nanoparticles (NPs) on Si substrates was studied using Scanning Kelvin Probe Microscopy (SKPM). The SKPM images and profiles of surface potential induced by the electrons confined inside the Au NPs subject to the time elapsed after the injection have been measured and analyzed. The parameters of the charge relaxation in the YSZ:NP-Au films were determined.
Alexey Mikhaylov
added a project goal
The project is aimed at the application of latest statistical analysis methods in the study of fluctuation phenomena in multistable memristive systems in order to detect and study in detail the constructive role of noise, which will provide an advanced background for creating new generations of electronic devices and neuromorphic technologies of artificial intelligence based on memristive materials.
Research objectives:
1. The study of the influence of external and internal noise on the behavior of multistable systems. Study and analysis of the phenomena with constructive role of noise in multistable systems.
2. Experimental study of the behavior of oxide-based memristive nanostructures in the presence of external and internal noise. Development of an adequate physical memristor macromodel taking into account the influence of external and internal noise and its comparison with the micromodel of physico-chemical phenomena responsible for resistive switching.
3. The study of microscopic nature of the flicker and high-frequency noise in memristive nanostructures.
4. Experimental demonstration of fundamentally new oportunities for increasing stability, predicting the behavior and controlling the parameters of memristive devices in prototypes of emerging electronic devices and neuromorphic systems.