We observed the surface potential of silicon pn junctions using a Kelvin probe force microscope whose sensitivity was about five times better than that of a conventional one. It was achieved by three major improvements: electrostatic force detection using the second cantilever resonance, cantilever Q-value enhancement by operating in a vacuum, and direct cantilever resonance frequency detection using the frequency modulation technique. It was demonstrated that the surface potential of the pn junctions made by thermal diffusion varies gradually compared to those made by ion implantation, possibly reflecting their gradual dopant concentration profile.

Although synaptic behaviours of memristors have been widely demonstrated, implementation of an even simple artificial neural network is still a great challenge. In this work, we demonstrate the associative memory on the basis of a memristive Hopfield network. Different patterns can be stored into the memristive Hopfield network by tuning the resistance of the memristors, and the pre-stored patterns can be successfully retrieved directly or through some associative intermediate states, being analogous to the associative memory behaviour. Both single-associative memory and multi-associative memories can be realized with the memristive Hopfield network.

We study the paired-pulse-induced response of a NiO x -based memristor. The behavior of the memristor is surprisingly similar to the paired-pulse facilitation of a biological synapse. When the memristor is stimulated with a pair of electrical pulses, the current of the memristor induced by the second pulse is larger than that by the first pulse. In addition, the magnitude of the facilitation decreases with the pulse interval, while it increases with the pulse magnitude or pulse width.

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