Material chemist Dr. Michael J. Bojdys from IRIS Adlershof and the Institute of Chemistry at Humboldt-Universität zu Berlin and astrobiologist Prof. Dr. Dirk Schulze-Makuch from Technische Universität Berlin will both receive a Proof of Concept Grant (PoC) from the European Research Council (ERC). Dr. Bojdys is investigating Li anode materials for high-capacity applications, and Dr. Schulze-Makuch is working on an automated detection of cholera pathogens.

The grant is intended exclusively for researchers who have already obtained an ERC Grant and wish to exploit a research result from their current or already completed project before it is commercially available. The aim of a proof of concept project is to determine the market potential of a given idea, which is the first step towards technological transfer.

As a part of his ERC PoC grant, “Ultra-high energy storage Li-anode materials” (LiAnMAT), together with VARTA Micro Innovation GmbH and the Adlershof startup INURU GmbH, Dr. Michael J. Bojdys from IRIS Adlershof and the Institute of Chemistry at Humboldt-Universität zu Berlin has been developing Li anode materials for high capacity applications. Lithium-ion batteries used in electronic devices could store 10 to 40 times more energy with LiAnMAT than commercially available anodes. These initially promising results are part of a patent application filed by both Humboldt-Universität zu Berlin and the start-up incubator Humboldt Innovation GmbH.

Prof. Dr. Dirk Schulze-Makuch, head of the Department of Astrobiology and a specialist in the field of planetary habitability at the Centre for Astronomy and Astrophysics at Technische Universität Berlin, is currently working on developing a new approach to the automated detection of pathogens, particularly cholera pathogens. The new project is called “Portpath. A Portable Device for Detecting Pathogens.” The new PortPath approach is designed to make use of user-friendly software and affordable hardware to quickly and cost-effectively analyze whether pathogens are present in a water sample. The hardware comprises the latest developments in computer technology, and the software utilizes machine learning strategies. During the development process, the team placed particular emphasis on ensuring that the mobile PortPath unit could be operated by amateurs, meaning that it could also be used in poorer countries affected by water contamination.