Researchers from MaX advanced the predictive design of tantalum-based components, significantly enhancing the ability to model and understand how tantalum behaves under extreme conditions such
MaX CoE congratulates Professor Stefano Baroni on this outstanding achievement and thanks him for his lasting contributions to computational physics and open scientific collaboration. MaX
CASTIEL 2 launches the HPC in Europe Portal, gathering EU-funded HPC resources, training, and expertise in one platform to enhance accessibility, collaboration, and visibility within
MaX researchers performed microsecond, first-principles simulations of glass-forming toluene by integrating Quantum ESPRESSO with machine-learned interatomic potentials. The researchers demonstrated that the temperature-dependent increase in
MaX is on a mission to harness HPC and AI to accelerate the design and discovery of next-generation materials for energy, health, and quantum technologies.
A new HPC-driven method for accurate estimation of transport coefficients in complex materials. Understanding how heat, charge, and mass move through materials is essential for
Researchers from MaX deliver a unified, high-accuracy method to compute transport coefficients from molecular dynamics, reducing simulation cost while improving statistical reliability across liquids and
The CASTIEL2 – EuroCC2 – EuroCC4SEE “All-Hands Meeting” gathered the NCCs and the CoEs to strengthen collaboration, share strategies, and advance the European HPC and
MaX Centre of Excellence participated in its second project review to assess progress, achievements, and future directions for materials simulation at the exascale level. On
Researchers from MaX optimized Quantum ESPRESSO to run many k-point calculations in parallel on GPUs, significantly speeding up electronic structure and phonon computations for metals
MaX researchers from CNR and SISSA take part in the 7th Psi-k General Conference in Lausanne and strengthen collaboration in electronic-structure theory and materials modelling.
New MaX GPU strategy speeds up plane-waves DFT for metals with dense k-point sampling, improving simulations for small-unit-cell systems. Researchers from MaX CoE, Xuejun Gong