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

Abstract

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.

A comprehensive approach to decipher biological computation to achieve next generation high-performance exascale computing.

“…Similar to TiO 2 , the motion of oxygen vacancies and the development of a conductive filament have been discussed; however, their exact role in the switching mechanism is still under debate with concern that their role changes depending on the device structure. In TaO Conversely, in bilayer memristors of TaO x and Ta, the lateral motion of oxygen vacancies or anions is thought to be key, with the oxygen concentration of a Ta rich conducting filament the purported state variable [83,86]. Quantitative models describing the physics of phenomena such as retention have been demonstrated [87], however, as summarized above, modeling of the physics of switching dynamics in TaOx memristors has been primarily qualitative.…”

Hierarchical Temporal Memory Based on Spin-Neurons and Resistive Memory for Energy-Efficient Brain-Inspired Computing

“…More importantly, devices that can facilitate direct 'in-memory' processing, may be highly attractive for such memory intensive computing. Several device solutions have been proposed for fabricating nano-scale programmable resistive elements, generally categorized under the term 'memristor' [9][10][11][12][13][14][15][16][17]. Of special interest are those which are amenable to integration with state of the art CMOS technology, like memristors based on Ag-Si filaments [14][15][16].…”

“…Of special interest are those which are amenable to integration with state of the art CMOS technology, like memristors based on Ag-Si filaments [14][15][16]. Such devices can be integrated into metallic cross-bars to obtain high density resistive cross-bar networks (RCN) [9][10][11][12][13][14][15][16]. Continuous range of resistance values obtainable in these devices can facilitate the design of multilevel, non-volatile memory [9][10][11].…”

“…Such devices can be integrated into metallic cross-bars to obtain high density resistive cross-bar networks (RCN) [9][10][11][12][13][14][15][16]. Continuous range of resistance values obtainable in these devices can facilitate the design of multilevel, non-volatile memory [9][10][11]. The RCN technology has led to interesting possibilities of combining memory with computation [9][10][11][12][13].…”

“…Continuous range of resistance values obtainable in these devices can facilitate the design of multilevel, non-volatile memory [9][10][11]. The RCN technology has led to interesting possibilities of combining memory with computation [9][10][11][12][13]. RCN can be highly suitable for large number of non-Boolean computing applications that involve pattern-matching [13,19].…”