Abstract
The development of brain-inspired neuromorphic computing, including artificial intelligence (AI) and machine learning, is of considerable importance because of the rapid growth in hardware and software capacities, which allows for the efficient handling of big data. Devices for neuromorphic computing must satisfy basic requirements such as multilevel states, high operating speeds, low energy consumption, and sufficient endurance, retention and linearity. In this study, inorganic perovskite-type amorphous strontium vanadate (a-SrVOx: a-SVO) synthesized at room temperature is utilized to produce a high-performance memristor that demonstrates nonvolatile multilevel resistive switching and synaptic characteristics. Analysis of the electrical characteristics indicates that the a-SVO memristor illustrates typical bipolar resistive switching behavior. Multilevel resistance states are also observed in the off-to-on and on-to-off transition processes. The retention resistance of the a-SVO memristor is shown to not significantly change for a period of 2 × 104 s. The conduction mechanism operating within the Ag/a-SVO/Pt memristor is ascribed to the formation of Ag-based filaments. Nonlinear neural network simulations are also conducted to evaluate the synaptic behavior. These results demonstrate that a-SVO-based memristors hold great promise for use in high-performance neuromorphic computing devices.
Highlights
The use of digital computing systems based on von Neumann architecture has led to the development of outstanding memory technologies following Moore’s law over the last several decades, with a consistent aim to manufacture integrated circuits with a higher number of transistors and a lower energy consumption within a smaller area
We characterized the electrical performance of a metal-insulator-metal (MIM) structure in which an a-SVO thin film was sandwiched between bottom Pt and top Ag electrodes and evaluated its resistive switching characteristics at room temperature
A 40-nm-thick a-SVO active layer is sandwiched between a Pt film as the bottom grounding electrode and an Ag film as the top terminal electrode
Summary
The use of digital computing systems based on von Neumann architecture has led to the development of outstanding memory technologies following Moore’s law over the last several decades, with a consistent aim to manufacture integrated circuits with a higher number of transistors and a lower energy consumption within a smaller area. To construct neuromorphic computing systems, artificial memristor-based synapses that have their synaptic characteristics updated by electrical stimuli are arranged in a circuit[5,6] With this structure in mind, resistive random access memory (RRAM) has emerged as a highly promising contender for use in future computing devices due to its great scalability, low energy consumption, quick switching (sub-ns), and simple two-terminal structure with a cell size of 4F2, where F is the minimum feature size[1,7,8,9,10]. Fabrication has to be carried out at low temperatures, and CMOS-compatible substrates need to be employed In this respect, it has been shown that nonstoichiometric perovskite-type oxides synthesized at room temperature can exhibit defect-related resistive switching characteristics, a general property of RRAM devices[25,41]. The synaptic behavior of the a-SVO film was investigated as a function of voltage stress in order to determine the suitability of the proposed a-SVO-based memristor for use in neuromorphic computing
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