PREDICTOR
High-throughput screening, synthesis and characterization of active materials for flow batteries.
About the project
PREDICTOR aims to establish a rapid, high-throughput method to identify and develop materials for electrochemical energy storage.
This method will comprise:
- A modelling and simulation tool for the computational screening of organic chemicals based on their potential performance in energy storage systems.
- Automated chemical synthesis, electrolyte production and characterization methods, so that the chemicals identified in the screening step can be rapidly produced and tested for their suitability in energy storage applications.
- Artificial-intelligence-based self-optimization methods that allow experimental data from material characterization to be fed back into automated experimental methods to enable self-driving laboratory platforms and for modelling and simulation tools, improving their accuracy.
- Data management systems to standardize and store the data generated for further use in model validation and self-optimization procedures
This approach will allow the rapid identification, synthesis and characterization of materials within a coherent development chain, replacing conventional trial-and-error developments.
Type of project
MSCA Doctoral Networks
Section members involved in the project
Contact: Piotr de Silva
Piotr de Silva Professor Department of Energy Conversion and Storage Mobile: +45 93510819 pdes@dtu.dk
Antonio Sessa PhD student Department of Energy Conversion and Storage Mobile: +39 3454693145 antse@dtu.dk
Rita Villar Parajó PhD student Department of Energy Conversion and Storage Mobile: +45 91789823 rvipa@dtu.dk