In this work, we evaluate a multitude of metal-oxide bi-layers and demonstrate the benefits from increased memory stability via multibit memory operation. We introduce a programming methodology that allows for operating metal-oxide memristive devices as multibit memory elements with highly packed yet clearly discernible memory states. We finally demonstrate a 5.5-bit memory cell (47 resistive states) with excellent retention and power consumption performance. This paves the way for neuromorphic and non-volatile memory applications.
Reversible bipolar nano-switches that can be set and read electronically in a solid-state two-terminal device are very promising for applications. We have performed molecular-dynamics simulations that mimic systems with oxygen vacancies interacting via realistic potentials and driven by an external bias voltage. The competing short- and long-range interactions among charged mobile vacancies lead to density fluctuations and short-range ordering, while illustrating some aspects of observed experimental behavior, such as memristor polarity inversion.
Memristors have been at the forefront of nanoelectronics research for the last decade, offering a valuable component to reconfigurable computing. Their attributes have been studied extensively along with applications that leverage their state-dependent programmability in a static fashion. However, practical applications of memristor-based AC circuits have been rather sparse, with only a few examples found in the literature where their use is emulated at higher frequencies. In this work, we study the behavior of metal-oxide memristors under an AC perturbation in a range of frequencies, from 10^3 to 10^7 Hz. Metal-oxide memristors are found to behave as RC low-pass filters and they present a variable cut-off frequency when their state is switched, thus providing a window of reconfigurability when used as filters. We further study this behaviour across distinct material systems and we show that the usable reconfigurability window of the devices can be tailored to encompass specific frequency ranges by amending the devices capacitance. This study extends current knowledge on metal-oxide memristors by characterising their frequency dependent characteristics, providing useful insights for their use in reconfigurable AC circuits.
We have extended our recent molecular-dynamic simulations of memristors to include the effect of thermal inhomogeneities on mobile ionic species appearing during operation of the device. Simulations show a competition between an attractive short-ranged interaction between oxygen vacancies and an enhanced local temperature in creating/destroying the conducting oxygen channels. Such a competition would strongly affect the performance of the memristive devices.
We extend the notion of memristive systems to capacitive and inductive elements, namely capacitors and inductors whose properties depend on the state and history of the system. All these elements show pinched hysteretic loops in the two constitutive variables that define them: current-voltage for the memristor, charge-voltage for the memcapacitor, and current-flux for the meminductor. We argue that these devices are common at the nanoscale where the dynamical properties of electrons and ions are likely to depend on the history of the system, at least within certain time scales. These elements and their combination in circuits open up new functionalities in electronics and they are likely to find applications in neuromorphic devices to simulate learning, adaptive and spontaneous behavior.
The nonlinear transport properties of nanometer-scale junctions formed between an inert metallic tip and an Ag film covered by a thin Ag$_{2}$S layer are investigated. Suitably prepared samples exhibit memristive behavior with technologically optimal ON and OFF state resistances yielding to resistive switching on the nanosecond time scale. Utilizing point contact Andreev reflection spectroscopy we studied the nature of electron transport in the active volume of the memristive junctions showing that both the ON and OFF states correspond to truly nanometer scale, highly transparent metallic channels. Our results demonstrate the merits of Ag$_{2}$S nanojunctions as nanometer-scale memory cells with GHz operation frequencies.