So-called resistive switching devices (memristive systems) promote novel, energy-efficient, fast, and compact technologies in the fields of nonvolatile data storage, in-memory computing, the hardware implementation of artificial neural networks, probabilistic optimization or autonomous signal detection. All these applications, however, strongly rely on the material properties of the involved memristive system, like the conduction mechanisms, the dynamical characteristics or the device noise.

Latter, the device noise, is typically considered a disturbing factor in traditional engineering; however, it can also serve as a unique tool for characterization [1]. The so-called noise diagnostics, i.e. the investigation of resistance, voltage, and frequency dependence of 1/f-like noise can provide deep insight into the noise phenomena and the underlying physics of device operation. Along this concept, our research group places great emphasis on the investigation of 1/f-like noise in various memristive systems. Our goal is to examine and compare the noise of memristors based on different materials, addressing both basic research and technologically relevant questions.

The PhD student will perform noise spectroscopy measurements on memristive systems both in the linear and non-linear current-voltage characteristics regimes. We expect that the analysis of the noise characteristics can reveal not only the noise properties themself, but also the conduction and the switching mechanisms in various memristive systems.

[1] Balogh, Z., Mezei, G., Pósa, L., Sánta, B., Magyarkuti, A., Halbritter, A., 1/f noise spectroscopy and noise tailoring of nanoelectronic devices, Nano Futures 5, 042002 (2021)