RESUMEN
A recoverable pseudo-electroforming process was discovered in Pt/WO3/FTO devices. Unlike conventional electroforming, which is usually destructive, pseudo-electroforming can be recovered when the electrical stimulation is removed. Furthermore, the time-dependent recovery process can be tuned by diverse voltage pulses applied in pseudo-electroforming; therefore, the device can be used as a time-delay switch in memristor-based neuromorphic networks. This "volatile" electroforming process can be attributed to the high oxygen vacancy concentration in the fluorine-doped tin oxide (FTO) bottom electrode, which acts as a non-blocking electrode in the resistive switching.
RESUMEN
Inappropriate operation could make a memristive device "dead" and cause the loss of resistive switching performance. In this study, the revival of "dead" devices was investigated in the case of WO3-x-based memristive devices. It is believed that inappropriate operation with a high-voltage pulse creates an ordered structure of oxygen vacancies and such an ordered structure makes the normal reset process fail. By precisely controlled voltage sweeping at certain compliance currents, a "dead" device can be revived. The revival operation disrupts the ordered structure by Joule heating and recovers Schottky-like barrier modulation-based switching.
RESUMEN
To implement the complex brain functions of learning, forgetting and memory in a single electronic device is very advantageous for realizing artificial intelligence. As a proof of concept, memristive devices with a simple structure of Ni/Nb-SrTiO3/Ti were investigated in this work. The functions of learning, forgetting and memory were successfully mimicked using the memristive devices, and the "time-saving" effect of implicit memory was also demonstrated. The physics behind the brain functions is simply the modulation of the Schottky barrier at the Ni/SrTiO3 interface. The realization of various psychological functions in a single device simplifies the construction of the artificial neural network and facilitates the advent of artificial intelligence.
RESUMEN
Single crystalline SrTiO3 doped with 0.1 wt% Nb was used as a model system to evaluate the role of the Schottky barrier in the resistive switching of perovskites. The Ti bottom electrode formed an ohmic contact in the Ni/Nb:SrTiO3/Ti stack, whereas the Ni top electrode created a strong Schottky barrier, which was reflected in a huge semi-circle in the impedance spectrum of the stack. Bipolar switching was achieved in the voltage range of -4 to 4 V for the stack, two clear resistance states were created by electric pulses, and the Schottky barrier heights corresponding to the high/low resistance states were experimentally determined. A direct relationship between the resistance state and the Schottky barrier height was thus established.
RESUMEN
Pavlovian conditioning, a classical case of associative learning in a biological brain, is demonstrated using the Ni/Nb-SrTiO3/Ti memristive device with intrinsic forgetting properties in the framework of the asymmetric spike-timing-dependent plasticity of synapses. Three basic features of the Pavlovian conditioning, namely, acquisition, extinction and recovery, are implemented in detail. The effects of the temporal relation between conditioned and unconditioned stimuli as well as the time interval between individual training trials on the Pavlovian conditioning are investigated. The resulting change of the response strength, the number of training trials necessary for acquisition and the number of extinction trials are illustrated. This work clearly demonstrates the hardware implementation of the brain function of the associative learning.
Asunto(s)
Aprendizaje por Asociación , Encéfalo/fisiología , Condicionamiento Clásico , Electrónica/instrumentación , Electrónica/métodos , Modelos TeóricosRESUMEN
Metaplasticity, a higher order of synaptic plasticity, as well as a key issue in neuroscience, is realized with artificial synapses based on a WO3 thin film, and the activity-dependent metaplastic responses of the artificial synapses, such as spike-timing-dependent plasticity, are systematically investigated. This work has significant implications in neuromorphic computation.