The goal of our research is to achieve a paradigm shift in information processing, which allows to build energetically highly efficient microelectronics. At the core of our research activity is the transfer of biological processes of information processing into solid-state electronic systems. In detail this includes the following research topics:
Memristive devices for neuromorphic systems
Analysis, characterization and simulation of memristive devices and systems
Neuromorphic systems and modelling of biological information processing
Within this research area, memristive devices are fabricated by means of thin film technology (material deposition processes, lithography, etching processes). These devices shall meet the special requirements of bio-inspired computing architectures, so-called neuromorphic systems, and enable the realization of novel electronics. In addition to the required replication of the mechanisms of biological information processing within the memristive components, the development of suitable manufacturing technologies that allow component production at wafer level is of central importance.
To reproduce neurobiological mechanisms of information processing and storage within nanoionic and nanoelectronic material systems, quantum mechanical laws are transferred into electronic devices, i.e. devices whose geometric dimensions are of the order of the matter wavelength of electrons. This requires a close interplay between state-of-the-art technological manufacturing processes, interface investigations in the atomic range, metrology, and the theoretical description of the underlying fundamental physical laws. In this context, the scientific work of this focal point is divided into two synergistically closely related thematic blocks, i.e. material analysis and electronic characterization, as well as component modeling.
The development of analog memristive circuits based on neurobiologically inspired models is the goal of this research area. To this end, we pursue a strongly interdisciplinary approach in order to bridge the gap between neurobiology and electrical engineering. Specifically, this includes the neurobiological modeling of learning and memory processes and the integration, design and realization of neuromorphic circuits.