The further progress of CMOS technology is obviously limited in many aspects: the possibility for further downscaling is questionable, the continuous data transfer between the physically separated processor and memory units (the so-called von Neumann bottleneck) is inefficient and the excessive heat dissipation in the semiconductor integrated circuits is also a major problem. Knowing these limitations, many fields of science are targeting the development of novel IT building blocks as well as novel computing architectures. Among these the rising technology of resistive switching memory devices offers extremely promising solutions in the field of mass data storage, brain inspired computing architectures and in-memory computing. In particular, the active region of resistive switching memory units can reach the ultimate atomic dimensions thank to the metallic nature of the nanofilaments that are established or degraded in a voltage-controlled way in these devices. Moreover, ‘scaling down’ means not only reducing the physical device size, but also the ability to control the device operation at atomic scales, promising enhanced stability, reduced device-to-device variations, and technologically exploitable, new physics at the verge of ballistic-to-diffusive conductance regimes.
The PhD candidate will develop novel on-chip resistive switching memory devices with the common goal of confining the resistive switching to ultra-small dimensions being well below the resolution of electron-beam lithography techniques. To achieve these small dimensions special techniques will be applied, like the controlled electrical breakdown of graphene or metallic nanowires, or the establishment of ultra-small resistive switching nanoholes in a vertical geometry. The operation principle of these devices will be studied with a broad variety of measurement techniques, like superconducting Andreev spectroscopy, point-contact spectroscopy, or time resolved measurements mapping the various internal physical timescales of the devices. Finally, the individual devices will be assembled to small networks.
Deep knowledge in nanophysics, long experience in experimental physics