Neuromorphic superconducting memristive electronics

Growing data throughput on the Internet, cloud computing, the use of smartphones and the possibility and requirement of carrying out very complex calculation processes on mainframe computers have become attributes of the current information society. At the same time, the processing, storage and provision of information is accompanied by extreme demands on the energy, storage space and data security required.

The project focuses on the transfer of neurobiological information processing principles and information storage into superconducting memristive systems with the aim of realizing energetically highly efficient microelectronic circuits for self-adapting (neuromorphic) systems with parallel architecture. Technologically, the aim is to combine superconducting microelectronics and neuromorphic memristor electronics. This approach should rigorously push the limits of today's microelectronic system concepts in terms of signal processing speed and energy efficiency. To solve these questions, novel material systems, components and computing architectures will be developed. Methodologically, the project is based on the physical investigation and description of quantum mechanical effects in order to make them usable for electronic components, the process and technology development for the hardware realization of such components on wafer level by means of thin film technologies and the development of circuit design concepts (system design).

On the basis of the funding guideline "Forschungslabore Mikroelektronik Deutschland (ForLab)", the Federal Ministry of Education and Research supports investments in universities with a strong focus on microelectronics.

The "Forschungslabor Mikroelektronik Ilmenau für neuromorphe Elektronik" (Research Laboratory Microelectronics Ilmenau for Neuromorphic Electronics) is being technologically expanded with the aim of developing highly energy-efficient microelectronic circuits for self-adapting systems with parallel architecture.

Funding period: 2019 - 2021