Luxembourg-based Next Step Fusion and Lisbon’s Instituto Superior Técnico (IST) have signed an agreement to collaborate on the development of fusion energy research.
Fusion power, a method of generating electricity under development, is taking its first steps in Luxembourg with local company Next Step Fusion (NSF) using digital twins and simulation software to aid research but also to put it into practice.
With most of its partners already abroad, NSF has just signed an agreement with Lisbon’s Instituto Superior Técnico (IST). Under this new agreement, the two institutions will focus on improving plasma control in IST’s ISTTOK tokamak device.
“The agreement with IST initiates a new era in fusion research in Portugal and Europe. Fusion research and development have been ongoing for several decades. Now, with modern technologies and platforms using machine learning and data from multiple fusion devices worldwide, we may be at a turning point to unlock the full potential of fusion,” said Aleksei Zolotarev, founder and CEO of Next Step Fusion.
The ISTTOK tokamak at Instituto Superior Técnico, a research infrastructure of Instituto de Plasmas e Fusão Nuclear (IPFN), operational since 1990, is Portugal’s sole fusion device. Its main goals, beyond education and training in nuclear fusion, include cutting-edge engineering and technology advancements, the development of new diagnostic techniques, control and data acquisition concepts, and physics modelling.
“Efficient plasma control remains one of the most challenging aspects of developing fusion devices. With access to real-time control systems and advanced simulation, the predictability of plasma behavior can reach new heights. The partnership with Next Step Fusion opens a significant phase for IST, providing our scientists with new data, tools, and systems to enhance the scientific progress of our fusion facility,” said Bruno Soares, President of Instituto de Plasmas e Fusão Nuclear, IST
This partnership marks a significant milestone in IST’s R&D efforts, granting access to advanced real-time plasma control systems powered by machine learning.
