The NeuromorPrint project introduces a groundbreaking methodology in neuromorphic computing, focusing on the development of a self-assembled 3D ZnO tetrapod network platform. The innovative spray-coating method facilitates scalable and efficient production of ZnO tetrapod networks (TN), mimicking 3D topologies akin to biological neural networks. The project’s scientific contributions encompass advancements in neuromorphic computing capabilities, insights into material-light interaction for synaptic functions, and the development of scalable devices with potential applications in various industries.
Project funding:
Research Council of Lithuania, Information technologies for the development of science and knowledge society
Project results:
Optimizing ZnO tetrapod networks is expected to significantly enhance cognitive computing, fostering more efficient and adaptable artificial intelligence systems. The project also emphasizes open science principles by transparently sharing datasets. Anticipated outcomes include the potential development of patentable technologies, contributing to intellectual property and potential commercial applications. Societal impact extends to environmental sustainability through green electronics manufacturing and a potential regional economic boost by enabling local electronics manufacturing. The project actively engages in educational outreach, participating in science festivals and public lectures, to inspire and educate students in the field of science and technology. In summary, NeuromorPrint emerges as a pioneering project in neuromorphic computing, integrating cutting-edge methodologies with environmental and economic considerations.
Period of project implementation: 2024-10-01 - 2026-09-30
Project coordinator: Kaunas University of Technology
