Abstract

Memristive devices are attracting a great attention for memory, logic, neural networks, and sensing applications due to their simple structure, high density integration, low-power consumption, and fast operation. In particular, multi-terminal structures controlled by active gates, able to process and manipulate information in parallel, would certainly provide novel concepts for neuromorphic systems. In this way, transistor-based synaptic devices may be designed, where the synaptic weight in the postsynaptic membrane is encoded in a source-drain channel and modified by presynaptic terminals (gates). In this work, we show the potential of reversible field-induced metal-insulator transition (MIT) in strongly correlated metallic oxides for the design of robust and flexible multi-terminal memristive transistor-like devices. We have studied different structures patterned on YBa2Cu3O7−δ films, which are able to display gate modulable non-volatile volume MIT, driven by field-induced oxygen diffusion within the system. The key advantage of these materials is the possibility to homogeneously tune the oxygen diffusion not only in a confined filament or interface, as observed in widely explored binary and complex oxides, but also in the whole material volume. Another important advantage of correlated oxides with respect to devices based on conducting filaments is the significant reduction of cycle-to-cycle and device-to-device variations. In this work, we show several device configurations in which the lateral conduction between a drain-source channel (synaptic weight) is effectively controlled by active gate-tunable volume resistance changes, thus providing the basis for the design of robust and flexible transistor-based artificial synapses.

Highlights

  • Digital computers can process a large amount of data with high precision and speed

  • We have recently demonstrated stable volume field-induced resistive switching in structures based on strongly correlated metallic perovskite oxides (La1−x Srx MnO3 (LSMO) and YBa2 Cu3 O7-δ (YBCO)), modulated through oxygen diffusion [23,24]

  • Resistance experiments directly confirm that the conductance between a drain-source channel be effectively modulated by using different active gates and that the oxygen redistribution in it strongly can be effectively modulated by using different gates that the oxygen redistribution in it depends on the switching performance of each active gate, and theand applied voltage pulse. These results strongly depends on the switching performance of each gate, and the applied voltage pulse. These provide a proof-of-concept of resistance modulation in multi-gate memristor structures based on the results provide a proof-of-concept of resistance modulation multi-gate memristor structures based strongly correlated materials showing the metal-insulator transition (MIT)

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Summary

Introduction

Digital computers can process a large amount of data with high precision and speed. Neuromorphic computing, operating with a parallel architecture connecting low-power computing elements (neurons) with multiple adaptive memory elements (synapses), appears as a very attractive alternative to von-Neuman based algorithms in future cognitive computers [1,2]. Design of computational systems mimicking the way that brain works, with intrinsically massive parallel information processing, is completely unfeasible. Stable learning has been achieved with digital logic for low-precision applications using binary weights [4,5], the development of novel functional materials, and individual device components able to resemble the properties of neurons and synapses, are mandatory to bring a revolutionary technological leap toward the implementation of a fully neuromorphic computer

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