Using machine learning is a promising trend in modelling the behaviour of the plasma inside a nuclear fusion reactor. DIFFER-researchers are pioneering very fast neural network models for plasma turbulence.
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DIFFER PhD student Karel van de Plassche came up with a clever approach to improve the system that is crucial for sharing information and performing experiments in the international ITER Organization.
Using more eyes to control fusion reactions: EUROfusion granted a project on multivariable feedback control of radiative loss processes.
A relatively unknown type of battery – the redox-flow battery – is very promising for large-scale energy storage. To improve the electrochemical reactions in this battery, a team of researchers from Eindhoven University of Technology (TU/e), DIFFER and MIT developed a completely new electrode with ‘honeycomb’ pores.
September 2020, MJ Pueschel started his new research group. The staunch idealist brings unique theoretical expertise to DIFFER.