May 27, 2024
Investigating adsorption behaviours induced by chemical functionality replacement towards electro-galvanised steel corrosion.
Using both experimental and theoretical approaches, a team of researchers presented new insights for rational inhibitor engineering, enabling the realization of tailored corrosion inhibition properties.
May 20, 2024
The Future of Scientific Computing: A Global Perspective
ICTP celebrates its 60th anniversary with an International Symposium to discuss the impact of artificial intelligence, high-performance computing, and quantum computing on scientific discovery.
May 16, 2024
CASTIEL2, EuroCC2, and CoE "All Hands Meeting" (AHM)
Representatives from NCCs, CoEs, and all CASTIEL2 gather in Slovakia.
May 8, 2024
PWTK: a scripting interface for Quantum ESPRESSO
The tutorial on PWTK will be held online between 20-24 May 2024.
May 2, 2024
European-Japanese Collaboration in High-Performance Computing Kicks Off with HANAMI Project
The HANAMI project officially kicked off in Paris on April 23.
April 30, 2024
MaX @ High Performance Computing in Science and Engineering 2024
MaX participate at the High Performance Computing in Science and Engineering 2024 conference (HPCSE 2024).
April 30, 2024
MaX @ ISC High Performance 2024
ISC High Performance 2024 will connect public and industry users and technology developers in Hamburg (DE) from May 12 – 16, 2024.
April 15, 2024
MaX Technical Poster 2024
Explore the technical results achieved by the MaX team in the first two years of the project. Download a copy!
April 2, 2024
"use-case" tutorial about materials modeling on HPC machines
A tutorial organized by MaX and NCC Slovenia. Details will be defined soon!
April 2, 2024
MaX school: materials and molecular modelling with QUANTUM ESPRESSO
MaX school: materials and molecular modelling with Quantum ESPRESSO. An online school organized by...
March 26, 2024
CASTIEL2 Communication workshop
On Friday, 22 March 2024, CASTIEL2 hosted a Communication workshop featuring champions from various European locations.
March 26, 2024
MAX and CoEs drive European supercomputing forward at EuroHPC Summit 2024
Together with fellow Centers of Excellence (CoEs), MAX participated in the EuroHPC Summit week 2024.
March 26, 2024
Women in the eXascale era
February 11 marked the International Day of Women and Girls in Science.
March 14, 2024
First-principles study of the gap in the spin excitation spectrum of the CrI 3 honeycomb ferromagnet
T. Gorni, O. Baseggio, P. Delugas, I. Timrov, and S. Baroni
March 13, 2024
Unveiling the Influence of Self-Interaction on Dissolved Electron Behavior in Molten Salts
A team of researchers reveals self-interaction effects on dissolved electrons in molten salts, advancing understanding of electron dynamics in complex salt solutions.
March 12, 2024
Investigating Luminescence in Monolayer Hexagonal Boron Nitride: Examining Exciton-Phonon Interaction and Substrate Influence
A team of researchers investigated the optical response of monolayer hexagonal boron nitride (m-hBN) using a novel approach that considers the influence of atomic vibrations on luminescence spectra.
March 11, 2024
Investigating ultrafast transient responses: broadband optical pump–probe microscopy on semiconducting monolayer 2H-MoTe2 encapsulated with hBN
A team of researchers used broadband optical pump–probe microscopy to explore the ultrafast transient response of semiconducting monolayer 2H-MoTe2 encapsulated with hBN. Their findings underscore the sensitivity of optical properties in monolayer transition-metal dichalcogenides to subtle structural changes and their manipulation with light.
March 5, 2024
Successful First-Year Project Review in Luxembourg (February 22, 2024)
In a pivotal event hosted in Luxembourg, the first-year review of MAX unfolded seamlessly, leaving a mark on the progress and success achieved.
March 4, 2024
Machine learning modalities for materials science
Supported by MAX, the workshop gathers introductory lectures, hands-on tutorials, invited talks, industry talks, and panel discussions with a focus on multi-modal, multi-objective, and multi-fidelity machine learning methods in materials science.