Related papers: Ideal memristor based on viscous magnetization dyn…

We report here gate-tunable memristors based on monolayer MoS2 grown by chemical vapor deposition (CVD). These memristors are fabricated in a field-effect geometry with the channel consisting of polycrystalline MoS2 films with grain sizes…

Highly accurate and predictive models of resistive switching devices are needed to enable future memory and logic design. Widely used is the memristive modeling approach considering resistive switches as dynamical systems. Here we introduce…

In this paper, we show that the dynamics of a wide variety of nonlinear systems such as engineering, physical, chemical, biological, and ecological systems, can be simulated or modeled by the dynamics of memristor circuits. It has the…

Magnetricity- the magnetic equivalent of electricity- was recently verified experimentally for the first time. Indeed, just as the stream of electric charges produces electric current, emergent magnetic monopoles have been observed to roam…

We present a computationally inexpensive yet accurate phenomenological model of memristive behavior in titanium dioxide devices by fitting experimental data. By design, the model predicts most accurately I-V relation at small non-disturbing…

To design fast memory devices, we need material combinations which can facilitate fast read and write operation. We present a heterostructure comprising a two-dimensional (2D) magnet and a 2D topological insulator (TI) as a viable option…

We address optimization of the spin current intensity profile needed to achieve spin torque switching of a nanomagnet. For systems with Ohmic dissipation we prove that the optimal current drives the magnetization along the trajectory, which…

The scaling of magnetic memory into nanometer size calls for a theoretical model to accurately predict the switching current. Previous models show large discrepancy with experiments in studying the spin-orbit torque switching of…

The ability of spintronic devices to utilize an electric current for manipulating the magnetization has resulted in large-scale developments, such as, magnetic random access memories and boosted the spintronic research area. In this regard,…

We propose a method for inducing magnetization reversal using an AC spin current polarized perpendicular to the equilibrium magnetization of the free magnetic layer. We show that the critical AC spin current is significantly smaller than…

Memristors stand out as promising components in the landscape of memory and computing. Memristors are generally defined by a conductance equation containing a state variable that imparts a memory effect. The current-voltage cycling causes…

The development of memristive device technologies has reached a level of maturity to enable the design of complex and large-scale hybrid memristive-CMOS neural processing systems. These systems offer promising solutions for implementing…

Ferroelectric memristors are intensively studied due to their potential implementation in data storage and processing devices. In this work we show that the memristive behavior of metal/ferroelectric oxide/metal devices relies on the…

A memristor is a two-terminal nanodevice that its properties attract a wide community of researchers from various domains such as physics, chemistry, electronics, computer and neuroscience.The simple structure for manufacturing, small…

Memristors based on two-dimensional materials (2DMs) have garnered significant attention due to their fast resistive switching (RS) behavior and atomic-level thickness, which enables low power consumption, making them promising candidates…

There are three theoretical models which purport to relate experimentally-measurable or fabrication-controllable device properties to the memristor's operation: 1. Strukov et al's phenomenological model; 2. Georgiou et al's Bernoulli…

Voltage-driven spin transfer torques in magnetic tunnel junctions provide an outstanding tool to design advanced spin-based devices for memory and reprogrammable logic applications. The non-linear voltage dependence of the torque has a…

Volatile memristors have recently gained popularity as promising devices for neuromorphic circuits, capable of mimicking the leaky function of neurons and offering advantages over capacitor-based circuits in terms of power dissipation and…

Memristors are nonlinear two-terminal circuit elements whose resistance at a given time depends on past electrical stimuli. Recently, networks of memristors have received attention in neuromorphic computing since they can be used as a tool…

We study the implications of the anisotropic magnetic resistance on permalloy nanowires, and in particular on the property of the resistance depending on the type of lattice. We discuss how the internal spin configuration of artificial spin…