Doctoral network for high-throughput screening, synthesis and characterization of active materials for flow batteries
Doctoral network for high-throughput screening, synthesis and characterization of active materials for flow batteries
France
15 Rue Baudelocque
80039 Amiens Cedex
PREDICTOR involves Prof. Alejandro A. Franco’s group who is located at the Laboratoire de Réactivité et Chimie des Solides -LRCS-, a joint research unit between CNRS and UPJV, in Amiens, France. LRCS is the headquarters of the French Network on Electrochemical Energy Storage (RS2E) and member of the ALISTORE European Research Institute.
LRCS is very active in performing research on energy technologies, in particular batteries, spanning a wide spectrum of techniques for advanced materials synthesis, advanced characterization, battery prototyping among others. Prof. Alejandro A. Franco’s group works since 23+ years in the field of electrochemical energy storage and conversion devices such as batteries and fuel cells. It has a unique expertise encompassing computational multiscale modeling techniques, advanced experimental characterization, Data Science, Artificial Intelligence/Machine Learning & Virtual/Mixed Reality tools.
Prof. Franco’s group develops advanced Artificial Intelligence systems for inverse design of anolytes and catholytes used in the redox flow battery technology studied in this project. Furthermore, it develops advanced Artificial Intelligence systems to process multimodal experimental characterization data in an efficient and in a human-in-the loop fashion.
"PREDICTOR gives us the opportunity to demonstrate how our digital optimization tools that we previously developed for lithium ion, sodium and solid state battery manufacturing optimization can be adapted and used to assist in the design and the optimization of redox flow batteries. The intended coupling between our digital tools and cutting edge experimentation in this project is very promising and we are very much looking forward to contribute at pushing the boundaries of this important energy storage technology and AI methodologies."
Funded by the European Union (Grant Agreement no. 101168943).
Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union.
Neither the European Union nor the granting authority can be held responsible for them.