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    About MAX

    MAX (MAterials design at the eXascale) is a European Centre of Excellence which enables materials modelling, simulations, discovery and design at the frontiers of the current and future High Performance Computing (HPC), High Throughput Computing (HTC) and data analytics technologies.

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    The software developed by MAX is made available to the whole community in open-source form. In this section you can find our main software output and how to obtain it.
     

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    MAX addresses the challenges of porting, scaling, and optimising material science application codes for the peta- and exascale platforms in order to deliver best code performance and improve users productivity on the upcoming architectures.

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    MAX is committed in supporting data stewardship by adhering to the FAIR-sharing principles. High-quality data is provided both in the format of curated scientific results and raw data, focusing on the tracking of provenance to ensure the full reproducibility of results.

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    MAX offers integrated training and education in the field of HPC developments and in the computational materials science domain, including workshops and schools, contributions to University courses and training through research in the CoE labs.

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    • Facts & Figures
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      • Open Online courses and videolectures
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June 23, 2022

Dynamic control of octahedral rotation in perovskites by defect engineering

Engineering oxygen octahedra rotation patterns in ABO3 perovskites is a powerful route to design...


June 22, 2022

MaX Happy Hour @ Psi-k Conference 2022 - Registration form


June 21, 2022

Microscopic picture of paraelectric perovskites from structural prototypes

M. Kotiuga, S. Halilov, B. Kozinsky, M. Fornari, N. Marzari, and G. Pizzi


June 21, 2022

Coexistence of vortex arrays and surface capillary waves in spinning prolate superfluid He 4 nanodroplets

M. Pi, J. M. Escartín, F. Ancilotto, and M. Barranco


June 6, 2022

Graphene decoupling through oxygen intercalation on Gr/Co and Gr/Co/Ir interfaces

D. A. Leon, A. Ferretti, D. Varsano, E. Molinari, and C. Cardoso


June 6, 2022

Graphene decoupling through oxygen intercalation on Gr/Co and Gr/Co/Ir interfaces

The authors perform a density functional theory study of the effects of oxygen adsorption on the...


May 27, 2022

MaX @ ISC 2022

MaX @ ISC 2022 - #TRANSFORMINGTHEFUTURE, the event for High Performance Computing, Machine Learning...


May 13, 2022

Numerically Precise Benchmark of Many-Body Self-Energies on Spherical Atoms

In this paper, the authors investigate the performance of beyond-GW approaches in many-body...


May 10, 2022

Young Researcher's Workshop on Machine Learning for Materials 2022

Event: Young Researcher's Workshop on Machine Learning for Materials 2022 Where: SISSA Miramare...


May 9, 2022

Exploring the robust extrapolation of high-dimensional machine learning potentials

C. Zeni, A. Anelli, A. Glielmo, and K. Rossi


May 9, 2022

Exploring the robust extrapolation of high-dimensional machine learning potentials

In this article appearing on Physical Reviews B, an international team comprised of young researchers from Italy and Switzerland show how, contrary to popular assumptions, predictions from machine learning potentials almost exclusively occur in an extrapolation regime.


May 5, 2022

Workflow Engineering in Materials Design within the BATTERY 2030+ Project

In recent years, modeling and simulation of materials have become indispensable to complement...


May 2, 2022

Anomalous screening in narrow-gap carbon nanotubes

G. Sesti, D. Varsano, E. Molinari, and M. Rontani


May 2, 2022

Anomalous screening in narrow-gap carbon nanotubes

The screening of Coulomb interaction controls many-body physics in carbon nanotubes, as it tunes...


May 2, 2022

Ranking the information content of distance measures

Aldo Glielmo, Claudio Zeni, Bingqing Cheng, Gábor Csányi, and Alessandro Laio


May 1, 2022

Coherence and de-coherence in the Time-Resolved ARPES of realistic materials: An ab-initio perspective

Coherence and de-coherence are the most fundamental steps that follow the initial photo-excitation...


April 26, 2022

Excitonic effects in graphene-like C3N

Carbon nitrides are gaining growing attention in recent years: they are metal-free carbon-based...


April 18, 2022

Phonon-Assisted Luminescence in Defect Centers from Many-Body Perturbation Theory

Phonon-assisted luminescence is a key property of defect centers in semiconductors, and can be...


April 14, 2022

Ranking the information content of distance measures

Real-world data typically contain a large number of features that are often heterogeneous in nature...


April 13, 2022

Flexibilities of wavelets as a computational basis set for large-scale electronic structure calculations

L. E. Ratcliff, W. Dawson, G. Fisicaro, D. Caliste, S. Mohr, A. Degomme, B. Videau, V. Cristiglio,...


April 13, 2022

Electronic-structure methods for materials design

N. Marzari, A. Ferretti, and C. Wolverton


April 13, 2022

Common workflows for computing material properties using different quantum engines

S. P. Huber, E. Bosoni, M. Bercx, J. Bröder, A. Degomme, V. Dikan, K. Eimre, E. Flage-Larsen, A...


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MaX - Materials design at the Exascale has received funding from the European High Performance Computing Joint Undertaking and Participating Countries in Project (Czechia, France, Germany, Italy, Slovenia and Spain) under grant agreement no. 101093374.

Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European High Performance Computing Joint Undertaking. Neither the European Union nor the granting authority can be held responsible for them.

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