Probabilistic model of resistance jumps in memristive devices.

Resistance switching memory cells such as electrochemical metallization cells and valence change mechanism cells have the potential to revolutionize information processing and storage. However, the creation of deterministic resistance switching devices is a challenging problem that is still open. At present, the modeling of resistance switching cells is dominantly based on deterministic models that fail to capture the cycle-to-cycle variability intrinsic to these devices.

Memristive Ising circuits.

The Ising model is of prime importance in the field of statistical mechanics. Here we show that Ising-type interactions can be realized in periodically driven circuits of stochastic binary resistors with memory. A key feature of our realization is the simultaneous coexistence of ferromagnetic and antiferromagnetic interactions between two neighboring spins-an extraordinary property not available in nature.

Custodial Chiral Symmetry in a Su-Schrieffer-Heeger Electrical Circuit with Memory.

Custodial symmetries are common in the standard model of particle physics. They arise when quantum corrections to a parameter are proportional to the parameter itself. Here, we show that a custodial symmetry of the chiral type is also present in a classical Su-Schrieffer-Heeger (SSH) electrical circuit with memory.

On the validity of memristor modeling in the neural network literature.

An analysis of the literature shows that there are two types of non-memristive models that have been widely used in the modeling of so-called "memristive" neural networks. Here, we demonstrate that such models have nothing in common with the concept of memristive elements: they describe either non-linear resistors or certain bi-state systems, which all are devices without memory. Therefore, the results presented in a significant number of publications are at least questionable, if not completely irrelevant to the actual field of memristive neural networks.

Snap-through transition of buckled graphene membranes for memcapacitor applications.

Using computational and theoretical approaches, we investigate the snap-through transition of buckled graphene membranes. Our main interest is related to the possibility of using the buckled membrane as a plate of capacitor with memory (memcapacitor). For this purpose, we performed molecular-dynamics (MD) simulations and elasticity theory calculations of the up-to-down and down-to-up snap-through transitions for membranes of several sizes.

Switching synchronization in one-dimensional memristive networks: An exact solution.

We study a switching synchronization phenomenon taking place in one-dimensional memristive networks when the memristors switch from the high- to low-resistance state. It is assumed that the distributions of threshold voltages and switching rates of memristors are arbitrary. Using the Laplace transform, a set of nonlinear equations describing the memristors dynamics is solved exactly, without any approximations.

Surface effects on ionic Coulomb blockade in nanometer-size pores.

Ionic Coulomb blockade in nanopores is a phenomenon that shares some similarities but also differences with its electronic counterpart. Here, we investigate this phenomenon extensively using all-atom molecular dynamics of ionic transport through nanopores of about one nanometer in diameter and up to several nanometers in length. Our goal is to better understand the role of atomic roughness and structure of the pore walls in the ionic Coulomb blockade.

Metastable memristive lines for signal transmission and information processing applications.

Traditional studies of memristive devices have mainly focused on their applications in nonvolatile information storage and information processing. Here, we demonstrate that the third fundamental component of information technologies-the transfer of information-can also be employed with memristive devices. For this purpose, we introduce a metastable memristive circuit.

Nanoscale Tipping Bucket Effect in a Quantum Dot Transistor-Based Counter.

Electronic circuits composed of one or more elements with inherent memory, that is, memristors, memcapacitors, and meminductors, offer lower circuit complexity and enhanced functionality for certain computational tasks. Networks of these elements are proposed for novel computational paradigms that rely on information processing and storage on the same physical platform. We show a nanoscaled memdevice able to act as an electronic analogue of tipping buckets that allows reducing the dimensionality and complexity of a sensing problem by transforming it into a counting problem.

Finding Stable Graphene Conformations from Pull and Release Experiments with Molecular Dynamics.

Here, we demonstrate that stable conformations of graphene nanoribbons can be identified using pull and release experiments, when the stretching force applied to a single-layer graphene nanoribbon is suddenly removed. As it is follows from our numerical experiments performed by means of molecular dynamics simulations, in such experiments, favorable conditions for the creation of folded structures exist. Importantly, at finite temperatures, the process of folding is probabilistic.

Computing with volatile memristors: an application of non-pinched hysteresis.

The possibility of in-memory computing with volatile memristive devices, namely, memristors requiring a power source to sustain their memory, is demonstrated theoretically. We have adopted a hysteretic graphene-based field emission structure as a prototype of a volatile memristor, which is characterized by a non-pinched hysteresis loop. A memristive model of the structure is developed and used to simulate a polymorphic circuit implementing stateful logic gates, such as the material implication.

The theory of spin noise spectroscopy: a review.

Direct measurements of spin fluctuations are becoming the mainstream approach for studies of complex condensed matter, molecular, nuclear, and atomic systems. This review covers recent progress in the field of optical spin noise spectroscopy (SNS) with an additional goal to establish an introduction into its theoretical foundations. Various theoretical techniques that have been recently used to interpret results of SNS measurements are explained alongside examples of their applications.

Memristive Sisyphus circuit for clock signal generation.

Frequency generators are widely used in electronics. Here, we report the design and experimental realization of a memristive frequency generator employing a unique combination of only digital logic gates, a single-supply voltage and a realistic thresholdtype memristive device. In our circuit, the oscillator frequency and duty cycle are defined by the switching characteristics of the memristive device and external resistors.

Switching synchronization in one-dimensional memristive networks.

We report on a switching synchronization phenomenon in one-dimensional memristive networks, which occurs when several memristive systems with different switching constants are switched from the high- to low-resistance state. Our numerical simulations show that such a collective behavior is especially pronounced when the applied voltage slightly exceeds the combined threshold voltage of memristive systems. Moreover, a finite increase in the network switching time is found compared to the average switching time of individual systems.

Memcomputing with membrane memcapacitive systems.

We show theoretically that networks of membrane memcapacitive systems-capacitors with memory made out of membrane materials-can be used to perform a complete set of logic gates in a massively parallel way by simply changing the external input amplitudes, but not the topology of the network. This polymorphism is an important characteristic of memcomputing (computing with memories) that closely reproduces one of the main features of the brain. A practical realization of these membrane memcapacitive systems, using, e.

Electric field cycling behavior of ferroelectric hafnium oxide.

HfO2 based ferroelectrics are lead-free, simple binary oxides with nonperovskite structure and low permittivity. They just recently started attracting attention of theoretical groups in the fields of ferroelectric memories and electrostatic supercapacitors. A modified approach of harmonic analysis is introduced for temperature-dependent studies of the field cycling behavior and the underlying defect mechanisms.

Dynamic computing random access memory.

The present von Neumann computing paradigm involves a significant amount of information transfer between a central processing unit and memory, with concomitant limitations in the actual execution speed. However, it has been recently argued that a different form of computation, dubbed memcomputing (Di Ventra and Pershin 2013 Nat. Phys.

Memory models of adaptive behavior.

Adaptive response to varying environment is a common feature of biological organisms. Reproducing such features in electronic systems and circuits is of great importance for a variety of applications. We consider memory models inspired by an intriguing ability of slime molds to both memorize the period of temperature and humidity variations and anticipate the next variations to come, when appropriately trained.

Giant up-conversion efficiency of InGaAs quantum dots in a planar microcavity.

Self-assembled InGaAs quantum dots (QDs) were fabricated inside a planar microcavity with two vertical cavity modes. This allowed us to excite the QDs coupled to one of the vertical cavity modes through two propagating cavity modes to study their down- and up-converted photoluminescence (PL). The up-converted PL increased continuously with the increasing temperature, reaching an intensity level comparable to that of the down-converted PL at ~120 K.

Nonequilibrium spin noise spectroscopy.

Spin noise spectroscopy is an experimental approach to obtain correlators of mesoscopic spin fluctuations in time by purely optical means. We explore the information that this technique can provide when it is applied to a weakly nonequilibrium regime when an electric current is driven through a sample by an electric field. We find that the noise power spectrum of conducting electrons experiences a shift, which is proportional to the strength of the spin-orbit coupling for electrons moving along the electric field direction.

Self-organization and solution of shortest-path optimization problems with memristive networks.

We show that memristive networks, namely networks of resistors with memory, can efficiently solve shortest-path optimization problems. Indeed, the presence of memory (time nonlocality) promotes self organization of the network into the shortest possible path(s). We introduce a network entropy function to characterize the self-organized evolution, show the solution of the shortest-path problem and demonstrate the healing property of the solution path.

On the physical properties of memristive, memcapacitive and meminductive systems.

We discuss the physical properties of realistic memristive, memcapacitive and meminductive systems. In particular, by employing the well-known theory of response functions and microscopic derivations, we show that resistors, capacitors and inductors with memory emerge naturally in the response of systems-especially those of nanoscale dimensions-subjected to external perturbations. As a consequence, since memristances, memcapacitances and meminductances are simply response functions, they are not necessarily finite.

Changing the state of a memristive system with white noise.

Can we change the average state of a resistor by simply applying white noise? We show that the answer to this question is positive if the resistor has memory of its past dynamics (a memristive system). We also prove that, if the memory arises only from the charge flowing through the resistor-an ideal memristor-then the current flowing through such memristor cannot charge a capacitor connected in series and, therefore, cannot produce useful work. However, the memristive system may skew the charge probability density on the capacitor, an effect that can be measured experimentally.

Complex dynamics and scale invariance of one-dimensional memristive networks.

Memristive systems, namely, resistive systems with memory, are currently attracting considerable attention. Here we show that even the simplest one-dimensional network formed by the most common memristive elements with voltage threshold bears nontrivial physical properties. In particular, by taking into account the single element variability we find (1) dynamical acceleration and slowing down of the total resistance in adiabatic processes, (2) dependence of the final state on the history of the input signal with same initial conditions, (3) existence of switching avalanches in memristive ladders, and (4) independence of the dynamics voltage threshold with respect to the number of memristive elements in the network (scale invariance).