FHI
The NOMAD Laboratory

Novel Materials Discovery at the FHI of the Max-Planck-Gesellschaft
and IRIS-Adlershof of the Humboldt-Universit├Ąt zu Berlin

 

About NOMAD: Revealing new and novel materials, mechanisms, and insight

The NOMAD Laboratory works in condensed-matter theory, materials science, and artificial intelligence. A particular focus is on density-functional theory and many-electron quantum mechanics and on developments of multiscale approaches. The latter, is summarized by the appeal "Get Real!", introducing environmental factors (e. g. partial pressures, deposition rates, and temperature) into ab initio calculations.[1] In recent years, the work is increasingly concerned with data-centric scientific concepts and methods (the 4th paradigm of materials science)[2][3] and the goal that materials-science data must become "Findable and Artificial Intelligence Ready".

 

1) H.J. Freund, G. Meijer, M. Scheffler, R. Schlögl, and M. Wolf, CO Oxidation as a Prototypical Reaction for Heterogeneous Processes, Angewandte Chemie International Edition 50: 10064 (2011), https://doi:10.org/10.1002/anie.201101378.

2) C. Draxl, M. Scheffler, Big Data-Driven Materials Science and Its FAIR Data Infrastructure, in Handbook of Materials Modeling, edited by W. Andreoni and S. Yip: Springer International Publishing, pp. 49 (2021); ISBN 978-3-319-44676-9, S2CID 242594698. https://doi:10.org/10.1007/978-3-319-44677-6_104.

3) T. Hey, S. Tansley, and K. Tolle, The Fourth Paradigm: Data-Intensive Scientific Discovery (2009), Microsoft Research, ISBN 978-0-9825442-0-4.

Special Collaborations & Activities

1_FAIR-DI The association FAIR-DI e.V (FAIR Data Infrastructure for Physics, Chemistry, Materials Science, and Astronomy)
NOMAD_Logo_srgb_web_whigh_2

The NOMAD Centre of Excellence 

NOMAD_Logo_srgb_web_whigh

The NOMAD database including Repository & Archive, Encyclopedia, and Artificial Intelligence Toolkit

FHI-aims-logo4

FHI-aims: Ab initio Materials Simulations

big.max.icon BigMax, the Max Planck Research Network on Big-Data-Driven Materials Science
grafox_icon_2 Leibniz ScienceCampus GraFOx (Growth and Fundamentals of Oxides)
mpgcqm_desktop

 Max Planck Graduate Center for Quantum Materials