This deliverable presents an updated Communication, Exploitation, and Dissemination (CED) plan refined after two years of practical experience. As MaX Centre of Excellence (CoE) entered its third phase, its strategic role in advancing computational materials science and driving innovation at the exascale level has been reaffirmed. Building on the success of previous phases, MaX continues to strengthen the European high-performance computing (HPC) ecosystem thanks to the support of member states working on the development of innovative hardware and software for the advancement of computational materials science. MaX technical and scientific efforts are structured across two key domains: Software for next-generation computing 2. Enabling scientific advances for global societal and industrial challenges through excellent codes Our CED actions have been therefore strategically designed to cover these two axes, to make sure that the expected outcomes of the project are effectively promoted and will resonate well beyond the project lifetime. Key features of this updated CED plan are more targeted, impact-oriented actions to engage with industry stakeholders, policymakers, and developers, and a better alignment with the overarching objectives of the EuroHPC Joint Undertaking. The CED Plan is structured around three pillars: 1. Stakeholder Engagement 2. Training and Education 3. Communication, Dissemination, and Exploitation Each pillar contributes to a coordinated effort to broaden MaX reach, deepen collaborations within the materials and HPC communities and beyond, and foster the uptake of project results across the different target audiences. Particular emphasis is placed on inclusivity, gender balance, accessibility, and the communication of scientific challenges and success cases to society at large. As a foundation for all our activities and initiatives, we consistently seek to strengthen collaborations with the other Centres of Excellence (CoEs), National Competence Centres (NCCs), and CASTIEL2.
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Marina Corradini
Daniele Varsano
Andrea Ferretti
University of Modena and Reggio Emilia
Institut Català de Nanociència i Nanotecnologia
Istituto Nanoscienze
Building similarity graph...
Analyzing shared references across papers
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Corradini et al. (Mon,) studied this question.
www.synapsesocial.com/papers/69ec5a8888ba6daa22dac170 — DOI: https://doi.org/10.5281/zenodo.19681842