Memristive and neuromorphic behavior in a LixCoO2 nanobattery
نویسندگان
چکیده
The phenomenon of resistive switching (RS), which was initially linked to non-volatile resistive memory applications, has recently also been associated with the concept of memristors, whose adjustable multilevel resistance characteristics open up unforeseen perspectives in cognitive computing. Herein, we demonstrate that the resistance states of Li(x)CoO2 thin film-based metal-insulator-metal (MIM) solid-state cells can be tuned by sequential programming voltage pulses, and that these resistance states are dramatically dependent on the pulses input rate, hence emulating biological synapse plasticity. In addition, we identify the underlying electrochemical processes of RS in our MIM cells, which also reveal a nanobattery-like behavior, leading to the generation of electrical signals that bring an unprecedented new dimension to the connection between memristors and neuromorphic systems. Therefore, these LixCoO2-based MIM devices allow for a combination of possibilities, offering new perspectives of usage in nanoelectronics and bio-inspired neuromorphic circuits.
منابع مشابه
Nanobatteries in redox-based resistive switches require extension of memristor theory
Redox-based nanoionic resistive memory cells are one of the most promising emerging nanodevices for future information technology with applications for memory, logic and neuromorphic computing. Recently, the serendipitous discovery of the link between redox-based nanoionic-resistive memory cells and memristors and memristive devices has further intensified the research in this field. Here we sh...
متن کاملHardware neuromorphic learning systems utilizing memristive devices
Hardware Neuromorphic Learning Systems Utilizing Memristive Devices
متن کاملLong-term Potentiation in Memristive Neuromorphic Systems
The memristor, a recently developed electronic component, behaves analogously to synapses in biological neural networks. Neuromorphic systems, which model biological neurons as electronic circuits, can implement memristors as synapses. Memristive devices were fabricated at the University of Michigan using tungsten oxide. These devices were to be used in neuromorphic systems, but they did not su...
متن کاملWaveform Driven Plasticity in BiFeO3 Memristive Devices: Model and Implementation
Memristive devices have recently been proposed as efficient implementations of plastic synapses in neuromorphic systems. The plasticity in these memristive devices, i.e. their resistance change, is defined by the applied waveforms. This behavior resembles biological synapses, whose plasticity is also triggered by mechanisms that are determined by local waveforms. However, learning in memristive...
متن کاملMemristive Crossbar Mapping for Neuromorphic Computing Systems on 3D IC
In recent years, neuromorphic computing systems based on memristive crossbar have provided a promising solution to enable acceleration of neural networks. Meanwhile, most of the neural networks used in realistic applications are often sparse. If such sparse neural network is directly implemented on a single memristive crossbar, it would result in inefficient hardware realizations. In this work,...
متن کامل