Scientific Scope

Electrochemical energy devices are key technologies to enable the transition into a more sustainable and fossil-free future society. The energy infrastructure based on renewable electricity production, as well as the electri cation of the transportation sector will rely on effective electrochemical energy conversion and storage in batteries or on fuels produced through electrolysis and used in fuel cells or as value-added products. The devices have to be designed to an acceptable cost and be ef cient, robust, and reliable. It is therefore essential that the processes occurring in the device and its state of health can be monitored during operation and understood to ensure and plan for a safe operation, and to further develop the technologies.

For this purpose, advanced electrochemical methods in combination with in-situ or in-operando physical or chemical techniques will be very useful. Mathematical models, describing the different processes in the system, are valuable for the interpretation of experimental data and for prediction of the future performance and lifetime of the device. Advanced experimental and modelling methods, including artificial Intelligence/machine learning techniques, are also needed for the development, optimization and design of new devices for various applications. Speci cally, the conference addresses:


•Electrochemical Energy Devices: all kinds of batteries, supercapacitors, fuel cells, electrolyzers (water, CO2 and others), and photo- or bioelectrochemical devices, focusing on cell, component or interface level.


•Experimental tools: in-situ and in-operando characterization techniques, including electrochemical, physical, or chemical methods to obtain qualitative and quantitative data that could stand alone or be used as parameters in theoretical models.


•Modelling tools: data-driven or physics-based modelling of electrochemical, electrical, mechanical or thermal processes in components or at the device level for performance evaluation, optimization, validation or prediction.