FAIR-DI e.V.
FAIRmat
NOMAD Laboratory
NOMAD CoE
NOMAD Centre of Excellence

Bringing computational materials science to exascale

Exascale Codes

  • Bringing DFT, Green-function methods, and coupled-cluster theory to exascale
  • Supporting entire code families, covering planewaves (PW), linearized augmented PWs, and atom-centred orbitals
  • Follow us on GitHub

Exascale Workflows

  • Enabling exascale computations by advanced workflows
  • Covering high-throughput computations and beyond-DFT workflows
  • Learn how to work with ASE/ASR and FireWorks in this tutorial

Extreme-scale data

  • Advance the NOMAD AI toolkit and bring it towards near-real-time performance
  • Like to visit the NOMAD Laboratory and its services for up- and downloading, and exploring materials data? 
  • Watch our video tutorials to learn how to work with the AI toolkit
Jan 4, 2018

NOMAD competition for transparent conducting oxides on kaggle


NOMAD has launched a crowd-sourced data-analytics competition with Kaggle, the most famous data science platform for predictive modelling and analytics competitions.

The challenge is to build predictive models for both formation and bandgap energies for a dataset, obtained by DFT calculations, consisting of binary, ternary and quaternary group-III oxides.  
The winners will share a prize of 5,000€ and will be invited to NOMAD Summer 2018, the CECAM conference organized by NOMAD in Lausanne (September 24 - 27, 2018).

February 8, 2018 - Entry and team merger deadline. You must accept the competition rules before this date in order to compete.
February 15, 2018 - Final submission deadline.