John Paul Strachan

High switching endurance in TaOx memristive devices

We demonstrate over 1×1010 open-loop switching cycles from a simple memristive device stack of Pt/TaOx/Ta. We compare this system to a similar device stack based on titanium oxides to obtain insight into the solid-state thermodynamic and kinetic factors that influence endurance in metal-oxide memristors.

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.

Direct Identification of the Conducting Channels in a Functioning Memristive Device

Structures composed of transition metal oxides can display a rich variety of electronic and magnetic properties including superconductivity, multiferroic behavior, and colossal magnetoresistance. [ 1 ] An additional property of technological relevance is the bipolar resistance switching phenomenon [ 2–4 ] seen in many perovskites [ 5–7 ] and binary oxides [ 8 ] when arranged in metal/insulator/metal (MIM) structures. These devices exhibit electrically driven switching of the resistance by 1000x or greater and have recently been identifi ed [ 9 ] as memristive systems, the fourth fundamental passive circuit element. [ 10 , 11 ] A full understanding of the atomic-scale mechanism and identifi cation of the material changes within the oxide remains an important goal. [ 12 ] Here, we probe within a functioning TiO 2 memristor using synchrotron-based x-ray absorption spectromicroscopy and transmission electron microscopy (TEM). We observed that electroforming of the device generated an ordered Ti 4 O 7 Magnéli phase within the initially deposited TiO 2 matrix. In a memristive system, [ 11 ] the fl ow of charge dynamically changes the material conductivity, which is “remembered” even with the removal of bias. While bipolar resistance switching of metal oxides has been observed since the 1960s, [ 2 , 4 ] only recently has the connection to the analytical theory of the memristor been made. [ 9 ] In an attempt to describe microscopically the source of the resistance change, many physical models have been put forth, including generation and dissolution of conductive channels, [ 3 , 6 ] electronic trapping and space-charge current limiting effects, [ 13 ] strongly correlated electron effects such as a metal-insulator transition, [ 14 ] and changes localized to the interface. [ 15 ] Identifying the correct model and quantifying its physical parameters has been diffi cult using primarily electrical characterization. Meanwhile, direct physical characterization [ 7 ]

Engineering nonlinearity into memristors for passive crossbar applications

Although TaOx memristors have demonstrated encouraging write/erase endurance and nanosecond switching speeds, the linear current-voltage (I-V) characteristic in the low resistance state limits their applications in large passive crossbar arrays. We demonstrate here that a TiO2-x/TaOx oxide heterostructure incorporated into a 50 nm× 50 nm memristor displays a very large nonlinearity such that I(V/2) ≈ I(V)/100 for V ≈ 1 volt, which is caused by current-controlled negative differential resistance in the device.

ISAAC: a convolutional neural network accelerator with in-situ analog arithmetic in crossbars

A number of recent efforts have attempted to design accelerators for popular machine learning algorithms, such as those involving convolutional and deep neural networks (CNNs and DNNs). These algorithms typically involve a large number of multiply-accumulate (dot-product) operations. A recent project, DaDianNao, adopts a near data processing approach, where a specialized neural functional unit performs all the digital arithmetic operations and receives input weights from adjacent eDRAM banks. This work explores an in-situ processing approach, where memristor crossbar arrays not only store input weights, but are also used to perform dot-product operations in an analog manner. While the use of crossbar memory as an analog dot-product engine is well known, no prior work has designed or characterized a full-fledged accelerator based on crossbars. In particular, our work makes the following contributions: (i) We design a pipelined architecture, with some crossbars dedicated for each neural network layer, and eDRAM buffers that aggregate data between pipeline stages. (ii) We define new data encoding techniques that are amenable to analog computations and that can reduce the high overheads of analog-to-digital conversion (ADC). (iii) We define the many supporting digital components required in an analog CNN accelerator and carry out a design space exploration to identify the best balance of memristor storage/compute, ADCs, and eDRAM storage on a chip. On a suite of CNN and DNN workloads, the proposed ISAAC architecture yields improvements of 14.8×, 5.5×, and 7.5× in throughput, energy, and computational density (respectively), relative to the state-of-the-art DaDianNao architecture.

The switching location of a bipolar memristor: chemical, thermal and structural mapping

Memristors are memory resistors promising a rapid integration into future memory technologies. However, progress is still critically limited by a lack of understanding of the physical processes occurring at the nanoscale. Here we correlate device electrical characteristics with local atomic structure, chemistry and temperature. We resolved a single conducting channel that is made up of a reduced phase of the as-deposited titanium oxide. Moreover, we observed sufficient Joule heating to induce a crystallization of the oxide surrounding the channel, with a peculiar pattern that finite element simulations correlated with the existence of a hot spot close to the bottom electrode, thus identifying the switching location. This work reports direct observations in all three dimensions of the internal structure of titanium oxide memristors.

Continuous Electrical Tuning of the Chemical Composition of TaOx-Based Memristors

TaO(x)-based memristors have recently demonstrated both subnanosecond resistance switching speeds and very high write/erase switching endurance. Here we show that the physical state variable that enables these properties is the oxygen concentration in a conduction channel, based on the measurement of the thermal coefficient of resistance of different TaO(x) memristor states and a set of reference Ta-O films of known composition. The continuous electrical tunability of the oxygen concentration in the channel, with a resolution of a few percent, was demonstrated by controlling the write currents with a one transistor-one memristor (1T1M) circuit. This study demonstrates that solid-state chemical kinetics is important for the determination of the electrical characteristics of this relatively new class of device.

Diffusion of Adhesion Layer Metals Controls Nanoscale Memristive Switching

First prominent more than 40 years ago, [ 1 ] electrical resistance switching in conductor/insulator/conductor structures has regained signifi cant attention in the last decade, [ 2–16 ] motivated by the search for alternatives to conventional semiconductor electronics. [ 17 ] Recent results have shown promising device behaviors, such as reversible, non-volatile, fast ( < 10 ns), lowpower ( ∼ 1 pJ/operation) and multiple-state switching, [ 18–26 ]

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.

Local Temperature Redistribution and Structural Transition During Joule‐Heating‐Driven Conductance Switching in VO2

Joule-heating induced conductance-switching is studied in VO2 , a Mott insulator. Complementary in situ techniques including optical characterization, blackbody microscopy, scanning transmission X-ray microscopy (STXM) and numerical simulations are used. Abrupt redistribution in local temperature is shown to occur upon conductance-switching along with a structural phase transition, at the same current.