Our Nature Physics paper in the BSC News

Interior view of Alcator C-Mod (left) and JET (right) tokamak reactors where experiments reported in the Nature Physics paper were carried out. Source: Plasma Science and Fusion Center, MIT and EUROfusion.

Our group members Mervi Mantsinen and Dani Gallart have participated in the paper “Efficient generation of energetic ions in multi-ion plasmas by radio-frequency heating”, currently available as Advance Online Publication on the Nature Physics website.

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BSC Fusion group presents results at the EUROfusion material modelling meeting in Zagreb

Picture of the meeting, Source: Institut Ruðer Bosković, EUROfusion.

Last week our group member Marc Eixarch and his supervisor Stephan Mohr from the Material Science Group at the Computer Applications in Science and Engineering Department of BSC participated at the Fusion Material Modelling meeting in Zagreb, organized by EUROfusion under the Work Package WPMAT-IREMEV and held by the Croatian Fusion Research Unit. This meeting had the objective of sharing the new results on radiation damage in fusion materials.

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Join us! We are looking for a Postdoctoral Researcher for neutron transport simulations

BSC team.

Barcelona Supercomputing Center (BSC) is looking for postdoctoral researcher with PhD in neutron transport simulations to work in our Fusion group.

The successful candidate will become an active member of our group’s research projects. The group is multidisciplinary and works in close collaboration with the EUROfusion programme and ITER.

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First first-principles-based simulation of a transition to high-confinement fusion plasma on Titan supercomputer

Simulation was performed on the Titan supercomputer. Source: Oak Ridge Leadership Computing Facility.

For the first time, scientists have been able to simulate the spontaneous transition of turbulence at the edge of a fusion plasma to the high-confinement mode (H-mode) that sustains fusion reactions. The detailed simulation is the first basic physics, or first-principles-based, modeling with few simplifying assumptions.

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