Future Development

Within the JARA-FIT consortia and support from the department of computer science the research of the institute will aim to the development of brain-inspired computing architectures. Next to the development of neuromorphic logic and memory, this activity will involve the integration of optical interposer/interconnects in collaboration with the acitivities in PGI-9 and the Department of Electrical Engineering at RWTH Aachen University (Prof. J. Witzens). It is envisioned that this will require highly complex integration processes, involving 3-D architectures. The technology will require hybrid structures merging the materials mentioned above as well as new paths for nano-lithography. To this end, to obtain patterns of desired shape with nm-resolution and sufficient contrast by the use of diffraction and interference of EUV radiation in combination with the proximity printing. The development of algorithms based on inverse propagation of the radiation field between mask and wafer for designing the mask layout for generating the desired photoresist patterns is essential. The elaboration of architectures making use of self-assembly methods to produce hybrid nanostructures in 2- and 3-dimensional arrays in combination with nanolithography, material development and integration of logic, memory as well as optical components will be explored to gather insights into the feasibility of brain inspired architectures for future information technology

On the NanoCluster tool, our efforts will be mainly focused to really demonstrate high quality in-situ grown nanostructures combining III-V semiconductors, high-k dielectrics and metal gates. In this sense, vertical InAs/GaSb NW TFETs will be processed and characterized. Additionally, low charge noise GaAs/AlGaAs based nanostructures to support qubit fabrication will be studied. We shall continue the work regarding the superconductor/semiconductor core-shell NWs and start to investigate the in-situ growth hybrid semiconductor/phase change material NW structures for neuromorphic and quantum computing.

Last Modified: 04.10.2022