Antonio C. Torrezan

Anatomy of a Nanoscale Conduction Channel Reveals the Mechanism of a High‐Performance Memristor

By employing a precise method for locating and directly imaging the active switching region in a resistive random access memory (RRAM) device, a nanoscale conducting channel consisting of an amorphous Ta(O) solid solution surrounded by nearly stoichiometric Ta(2) O(5) is observed. Structural and chemical analysis of the channel combined with temperature-dependent transport measurements indicate a unique resistance switching mechanism.

Measuring the switching dynamics and energy efficiency of tantalum oxide memristors

We measured the real-time switching of metal-oxide memristors with sub-nanosecond resolution and recorded the evolution of the current and voltage during both ON (set) and OFF (reset) events. From these we determined the dynamical behavior of the conductivity for different applied bias amplitudes. Quantitative analysis of the energy cost and switching dynamics showed 115 fJ for ON-switching and 13 pJ for OFF-switching when resistance change was limited to 200%. Results are presented that show a favorable scaling with speed in terms of energy cost and reducing unnecessary damage to the devices.

Electrical Performance and Scalability of Pt Dispersed SiO2 Nanometallic Resistance Switch

Highly reproducible bipolar resistance switching was recently demonstrated in a composite material of Pt nanoparticles dispersed in silicon dioxide. Here, we examine the electrical performance and scalability of this system and demonstrate devices with ultrafast (<100 ps) switching, long state retention (no measurable relaxation after 6 months), and high endurance (>3 × 10(7) cycles). A possible switching mechanism based on ion motion in the film is discussed based on these observations.

State Dynamics and Modeling of Tantalum Oxide Memristors

A key requirement for using memristors in circuits is a predictive model for device behavior that can be used in simulations and to guide designs. We analyze one of the most promising materials, tantalum oxide, for high density, low power, and high-speed memory. We perform an ensemble of measurements, including time dynamics across nine decades, to deduce the underlying state equations describing the switching in Pt/TaOx/Ta memristors. A predictive, compact model is found in good agreement with the measured data. The resulting model, compatible with SPICE, is then used to understand trends in terms of switching times and energy consumption, which in turn are important for choosing device operating points and handling interactions with other circuit elements.

Designing memristors: Physics, materials science and engineering

Recently, memory and storage have taken a front seat in computer hardware as it experiences an explosive growth at a rate faster than Moores law for the past 10 years. With the upcoming challenges for further FLASH scaling into the next generations, emerging technologies have appeared portraying perspectives with the potential to shift computer architecture concepts. Here we present a brief overview and progress in our quest to create a device with competitive attributes, with the ultimate goal of achieving a universal, non-volatile data storage solution.

Oxide based memristive devices

Memristive devices with fast speed, low-energy, high endurance and small footprint have attracted significant attention recently. In this article, we first briefly introduce the switching mechanisms and then discuss possible applications with these devices, including memory, logic and neuromorphic computing. Finally, the promises and challenges of these devices are discussed, together with some possible solutions.