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The Novel Materials Discovery Laboratory

The Novel Materials Discovery Laboratory

Objective

Essentially every new commercial product, be they smart phones, solar cells, batteries, transport technology, artificial hips, etc., depends on improved or even novel materials. Computational materials science is increasingly influential as a method to identify such critical materials for both R&D. Enormous amounts of data, precious but heterogeneous and difficult to access or utilise, are already stored in repositories scattered across Europe. The NoMaD CoE will open new HPC opportunities by enabling access to this data and delivering powerful new tools to search, retrieve and manage it.
NoMaD will foster sharing of all relevant data, building on the unique CECAM, Psi-k and ETSF communities, putting Europe ahead of materials science in other continents. Unprecedented, already initialised networking with researchers, with industry, with students and with other stakeholders will guarantee relevance and end-user value. NoMaD will become a crucial tool for atomistic simulations and multi-scale modelling in the physical, materials, and quantum-chemical sciences. This field is characterised by a healthy but heterogeneous eco-system of many different codes that are used at all HPC centers worldwide, with millions of CPU hours spent every day, some of them at petascale performance. NoMaD will integrate the leading codes and make their results comparable by converting (and compressing) existing inputs and outputs into a common format, thus making these valuable data accessible to academia and industry:
NoMaD will develop “big-data analytics” for materials science. This will require novel algorithms, e.g., for statistical learning based on the created materials encyclopedia, offering complex searches and novel visualisations. These challenges exploit the essential resources of our HPC partners. Without the infrastructure and services provided by the NoMaD CoE, much of the information created with the above mentioned petascale (towards exascale) computations would be wasted.

Coordinator

MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV

Address

Hofgartenstrasse 8
80539 Muenchen

Germany

Activity type

Higher or Secondary Education Establishments

EU Contribution

€ 1 417 837,43

Participants (10)

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KING'S COLLEGE LONDON

United Kingdom

EU Contribution

€ 678 264,55

HUMBOLDT-UNIVERSITAET ZU BERLIN

Germany

EU Contribution

€ 561 929,83

THE CHANCELLOR MASTERS AND SCHOLARS OF THE UNIVERSITY OF CAMBRIDGE

United Kingdom

EU Contribution

€ 145 531,25

UNIVERSITAT DE BARCELONA

Spain

EU Contribution

€ 414 366,25

AALTO KORKEAKOULUSAATIO SR

Finland

EU Contribution

€ 450 000

DANMARKS TEKNISKE UNIVERSITET

Denmark

EU Contribution

€ 343 070,18

BAYERISCHE AKADEMIE DER WISSENSCHAFTEN

Germany

EU Contribution

€ 205 500

CSC-TIETEEN TIETOTEKNIIKAN KESKUS OY

Finland

EU Contribution

€ 205 375

BARCELONA SUPERCOMPUTING CENTER - CENTRO NACIONAL DE SUPERCOMPUTACION

Spain

EU Contribution

€ 238 749,99

PINTAIL LTD

Ireland

EU Contribution

€ 250 000

Project information

Grant agreement ID: 676580

Status

Closed project

  • Start date

    1 November 2015

  • End date

    31 October 2018

Funded under:

H2020-EU.1.4.1.3.

  • Overall budget:

    € 4 910 624,48

  • EU contribution

    € 4 910 624,48

Coordinated by:

MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV

Germany