Projects in the Business Area Virtual Material Design

Our projects include research, development, and applications in:

  • Multiscale modeling and numerical simulation for material science, chemistry and nanotechnology.
  • High performance computing in quantum mechanics, molecular dynamics and continuum mechanics.

SONAR – Better Batteries for Electricity from Renewable Energy Sources

Electricity from renewable energy sources contributes to combat climate change. One of the challenges is to develop technologies for storing excesses in energy supplies quickly and without loss. Organic redox flow batteries (RFBs) promise a viable route to this end: operated where needed, they rely on matter-bound storage – just in analogy to nature's example.

The benefits of an RFB system depend on many aspects: The perfect, redox-active material should smoothly accept or release electrons, while being soluble, stable, non-toxic and inexpensive. Moreover, the battery and tank systems should be customized to the specific requirements of the redox material and the site's conditions.

The SONAR project funded by the European Commission aims at capturing the entire development process with all relevant aspects in a digital manner in order to accelerate the screening for suitable substances and the optimization of a battery system's design for specific operating conditions.

The project partners develop tools and workflows for investigating electroactive materials up to whole battery systems. To this end, they combine simulation methods on different physical scales – ranging from the electronic/quantum mechanical level to the visible, macroscopic behavior. Factors such as cost, lifetime and performance are taken into account in order to compare competing energy storage technologies comprehensively.

To increase screening throughput, SONAR uses intelligent methods of data integration and data analysis, utilizing the growing amount of data generated during the project, For maximum reliability, the results of simulations and models are compared continuously to experimental data and the predictions are validated by lab measurements.

In SONAR, six project partners cooperate with five associated industrial companies. This will ensure the economic relevance of the results. Fraunhofer SCAI uses the models developed independently as well as in a comprehensive screening service to assess the technical and economic potential of a new technology in the early development phase. This reduces costs, shortens the time to market and thus strengthens the competitiveness of the battery industry in the European Union in the field of organic RFBs.

Project duration: 01/2020 - 12/2023

Deep Learning for Virtual Material Design

Empirical analysis potentials and ab-initio methods such as density function theory have been the pillars of computer-aided materials science. With theoretical advances in machine learning and the rapid increase in computing power, data-based approaches have emerged a new class of models with the goal of combining the predictive power of ab-initio methods and the computational efficiency of empirical potentials.

Standard machine learning techniques such as kernel learning (e.g. for the Gaussian approximation potential), deep neural networks (e.g. neural network potentials by Behler et al.), and generalized linear models (e.g. for momentum tensor potentials) have been employed to develop fast and accurate force fields from data without the need for human knowledge about the underlying chemistry.

In this project we develop high-quality, easy-to-use implementations of such machine learning potentials and investigate possibilities to improve the existing approaches by utilizing modern tools from the constantly growing toolbox of data science.

Human Brain Project

In the »Human Brain Project« (HBP), which is funded by the European Commission, leading research institutions work together to better understand the human brain. For that purpose the project partners will develop new simulation methods, for example on high performance computers. The project aims to develop new therapeutic approaches for the treatment of brain diseases and new methods of High Performance Computing. Fraunhofer SCAI participates in a HBP sub-project through researchers of its Department of Virtual Material Design (VMD). In particular, they develop software, numerical algorithms and methods to realize neuroscientific simulations on high performance computers. SCAI’s researchers provide their expertise in multiscale simulation and numerical simulation for Molecular Dynamics.

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