Memristive Devices and Systems for Neuromorphic Applications

This research is focused on memristive devices or resistive random access memories (RRAMs), that is, devices that under electrical, physical or chemical stimuli change their resistance state and retain its value even when the power is turned off. This is a nonvolatile effect and the phenomenon is called resistive switching, which could potentially be used as a data storage device. These devices can also exhibit multilevel behavior, which greatly expands their range of applications towards analog applications, including their suitability for fabricating artificial synapses that are very useful for applications such as neuromorphic circuits, neural networks, deep learning, and many more. It is common to apply voltage and measure current in such materials, we plan to also apply current or charge stimuli, which are more similar to what occurs in biological neural systems. That provides additional information about what kind of stimulus leads a better memristor state control.