Matthew D. Pickett

Switching dynamics in titanium dioxide memristive devices

Memristive devices are promising components for nanoelectronics with applications in nonvolatile memory and storage, defect-tolerant circuitry, and neuromorphic computing. Bipolar resistive switches based on metal oxides such as TiO2 have been identified as memristive devices primarily based on the “pinched hysteresis loop” that is observed in their current-voltage (i-v) characteristics. Here we show that the mathematical definition of a memristive device provides the framework for understanding the physical processes involved in bipolar switching and also yields formulas that can be used to compute and predict important electrical and dynamical properties of the device. We applied an electrical characterization and state-evolution procedure in order to capture the switching dynamics of a device and correlate the response with models for the drift diffusion of ionized dopants (vacancies) in the oxide film. The analysis revealed a notable property of nonlinear memristors: the energy required to switch a me...

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.

A scalable neuristor built with Mott memristors

The Hodgkin-Huxley model for action potential generation in biological axons is central for understanding the computational capability of the nervous system and emulating its functionality. Owing to the historical success of silicon complementary metal-oxide-semiconductors, spike-based computing is primarily confined to software simulations and specialized analogue metal-oxide-semiconductor field-effect transistor circuits. However, there is interest in constructing physical systems that emulate biological functionality more directly, with the goal of improving efficiency and scale. The neuristor was proposed as an electronic device with properties similar to the Hodgkin-Huxley axon, but previous implementations were not scalable. Here we demonstrate a neuristor built using two nanoscale Mott memristors, dynamical devices that exhibit transient memory and negative differential resistance arising from an insulating-to-conducting phase transition driven by Joule heating. This neuristor exhibits the important neural functions of all-or-nothing spiking with signal gain and diverse periodic spiking, using materials and structures that are amenable to extremely high-density integration with or without silicon transistors.

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.

Sub-100 fJ and sub-nanosecond thermally driven threshold switching in niobium oxide crosspoint nanodevices

We built and measured the dynamical current versus time behavior of nanoscale niobium oxide crosspoint devices which exhibited threshold switching (current-controlled negative differential resistance). The switching speeds of 110 × 110 nm(2) devices were found to be Δt(ON) = 700 ps and Δt(OFF) = 2:3 ns while the switching energies were of the order of 100 fJ. We derived a new dynamical model based on the Joule heating rate of a thermally driven insulator-to-metal phase transition that accurately reproduced the experimental results, and employed the model to estimate the switching time and energy scaling behavior of such devices down to the 10 nm scale. These results indicate that threshold switches could be of practical interest in hybrid CMOS nanoelectronic circuits.

SPICE modeling of memristors

In this paper we present a SPICE model for the titanium dioxide memristor device from its modeling equations as described in [1] and compare the SPICE simulations to the experimental data.

Metal precipitation at grain boundaries in silicon : Dependence on grain boundary character and dislocation decoration

Synchrotron-based analytical microprobe techniques, electron backscatter diffraction, and defect etching are combined to determine the dependence of metal silicide precipitate formation on grain boundary character and microstructure in multicrystalline silicon (mc-Si). Metal silicide precipitate decoration is observed to increase with decreasing atomic coincidence within the grain boundary plane (increasing Σ values). A few low-Σ boundaries contain anomalously high metal precipitate concentrations, concomitant with heavy dislocation decoration. These results provide direct experimental evidence that the degree of interaction between metals and structural defects in mc-Si can vary as a function of microstructure, with implications for mc-Si device performance and processing.

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.

Iron point defect reduction in multicrystalline silicon solar cells

In this work, we propose and demonstrate an annealing procedure designed to improve the performance of iron-contaminated silicon solar cells. Specifically, we put forward the idea that cells contaminated with iron should be annealed at appropriate times and temperatures to allow for the transformation from supersaturated point defects to distributed iron silicide precipitates. We examine the optimal transformation rate for string ribbon multicrystalline silicon and demonstrate that a 30min annealing can improve the efficiency of cells manufactured from low-purity feedstock.