Projects within the Max Planck Society (MPG)

Ten institutions of the Max Planck Society and Humboldt-Universität zu Berlin combine their know-how in data-driven materials science. The aim is a better use of the possibilities associated with analyzing large amounts of data. Which alloying constituents lend a steel unique bending strength, extreme hardness and non-rusting properties? Are semiconductors that promise greater efficiencies for solar modules available, and do they offer greater flexibility than silicon? What would be the best catalyst for a very specific chemical reaction? Or, how should a surface be coated to achieve the best possible thermal protection? To more easily find answers to these typical problems facing materials scientist in future, researchers from the above cited Institutions hope to better exploit the opportunities presented by analyzing large volumes of data. To this end, they cooperate in MaxNet on Big-Data-Driven Materials Science or, simply, BiGmax.

Movebank is a free online platform that helps researchers manage, share, analyze and archive animal movement data. Movebank is hosted by the Max Planck Institute of Animal Behavior (formerly the Max Planck Institute for Ornithology) in coordination with the North Carolina Museum of Natural Sciences, the Ohio State University and the University of Konstanz. Movebank works with many partners including government agencies, universities and conservation organizations and is intended to serve as a global archive for animal movement and bio-logging data. Movebank has long-term (>20 years) funding through the Max Planck Society and the University of Konstanz and has been developed with support from the National Science Foundation, the German Aerospace Center, the German Science Foundation and NASA.

Sample sizes for human science research projects as well as the amount of data collected per participant are on the rise. The informative value of data such as genetic data, imaging data, and extensive social and health data makes data protection increasingly challenging. The Max Planck Society's three-year joint project aims to develop a platform for the management of participant data in accordance with data protection regulations for use in Max Planck Institutes. "Castellum — A Subject Database Meeting Data Protection Standards" sets standards in terms of technical solutions that meet the demands of both data protection and research requirements. The goal is a coordinated central infrastructure for the management of personal data that can replace previous local, sometimes error-prone approaches.

The publicly available ELPA library provides highly efficient and highly scalable direct eigensolvers for symmetric matrices. Though especially designed for use for PetaFlop/s applications solving large problem sizes on massively parallel supercomputers, ELPA eigensolvers have proven to be also very efficient for smaller matrices. All major architectures are supported.
The MPCDF is the founder of the project and has been a core developer, leading and coordinating the development and release cycle.

ESPResSo++ is a software package for the scientific simulation and analysis of coarse-grained atomistic or bead-spring models as they are used in soft matter research. ESPResSo++ has a modern C++ core and flexible Python user interface. ESPResSo and ESPResSo++ have common roots however their development is independent and they are different software packages.
The MPCDF is an active contributor and collaborator.

FHI-aims is an efficient, accurate all-electron, full-potential electronic structure code package for computational molecular and materials science (non-periodic and periodic systems). The code supports DFT (semilocal and hybrid) and many-body perturbation theory. FHI-aims is particularly efficient for molecular systems and nanostructures, while maintaining high numerical accuracy for all production tasks. Production calculations handle up to several thousand atoms and can efficiently use (ten) thousands of cores.
The MPCDF has been a long-term contributor to FHI-aims, with a focus on comprehensive optimization, scalability and porting.

DFTB+ is a widely-used open-source code for atomistic quantum mechanical simulations. It implements the density functional tight binding (DFTB) method facilitating electronic-structure calculations of large systems. For the Fritz Haber Institute of the MPG and in collaboration with the main DFTB+ developers from the University of Bremen and the University of Strathclyde, the MPCDF contributes to the code base with new features and performance optimizations.

GENE (Gyrokinetic Electromagnetic Numerical Experiment) is an open source plasma microturbulence code which can be used to efficiently compute gyroradius-scale fluctuations and the resulting transport coefficients in magnetized fusion/astrophysical plasmas. GENE is physically comprehensive, well benchmarked, portable, and highly scalable. GENE is freely available via this webpage, and it is further developed by an international collaboration of physicists and computational scientists which is always open for new contributers. GENE has been used, among other things, to address both fundamental issues in plasma turbulence research and to perform comparisons with tokamak and stellarator experiments. GENE is coupled to the geometry interface code GIST.
The MPCDF has been a main long-term contributor to the development and optimization of GENE, and - more recently - also its offsprings, GENE-X and GENE-3D

Octopus is a scientific program aimed at the ab initio virtual experimentation on a hopefully ever-increasing range of system types. Electrons are described quantum-mechanically within density-functional theory (DFT), in its time-dependent form (TDDFT) when doing simulations in time. Nuclei are described classically as point particles. Electron-nucleus interaction is described within the pseudopotential approximation. For optimal execution performance Octopus is parallelized using MPI and OpenMP and can scale to tens of thousands of processors. It also has support for graphical processing units (GPUs) through OpenCL, CUDA and HIP.
The MPCDF is part of the core development team.