The project will demonstrate a science-based approach to the development of electrode materials forming key parts of reversible chemical-to-power cells. Such devices operate in two modes: in fuel cell (FC) mode, it converts hydrogen into electricity whereas when operating as electrolyser cell (EC), it uses excess electricity to form hydrogen from water electrolysis. This versatility enables the integration of intermittent renewable energy sources with the electrical grid by storing the excess energy as carbon-free chemical fuel. In particular, the project targets mixed oxides with perovskite structure with minimised critical content while keeping highest possible performances and targeting fair economic viability.
Project
Objectives
The main objective of the KNOWSKITE-X project is to boost the development of materials for energy applications by combining state-of-art approaches together with the empowerment of knowledge discovery allowed by artificial intelligence (AI). In particular, the project integrates a smart combination of advanced technologies, involving tailor-made materials preparation, harmonised and ground-breaking characterisation methods, multi-scale modelling and AI-enabled tools. This corpus of open-minded, innovative, reliable, and use-relevant methodologies targets the discovery of the scientific knowledge required to sustain the rational design of optimized candidate electrode materials.
Impacts
- Develop an open repository for knowledge transfer, data sharing for integration between modelling and advanced materials characterisation
- Enable a model-based innovation processes covering all stages from materials design to product development, including validation, characterisation and life cycle assessment
- Increase the efficiency and effectiveness of materials and product development by reducing costs and time for product design
- Improve handling of missing data by means of artificial intelligence/machine learning methods
