Memristors are nanometer size non-volatile tunable resistances. The resistance state of these devices can be changed by varying the voltage or the current across the structure. Depending on the memristor type, the resistive switching effects can be due to several different physical effects, ranging from red-ox to charge-induced, phase change or purely electronic phenomena. Practically, due to the possibility to easily manipulate their resistance state, these electronic nano-devices have a number of extremely promising applications, such as digital memories (Resistive Switching RAMs), switches and latches for advanced logic functions etc.
In addition, since their resistance can in general be tuned over several orders of magnitude, it should be possible to stack densely these components in large-scale cross-bar arrays. One of the most fascinating properties of memristors is that they intrinsically behave like synapses, which could be a key to the future development of hardware Artificial Neural Networks (ANNs), and revolutionize non-conventional neuromorphic computing.
This talk will be a review of the state of the art of memristor devices and their applications, with a special focus on their implementation as artificial synapses for on-chip neural networks.