Materials Materials design

The design of new materials with optimized properties is the key to solutions for current and emerging global challenges. BAM's expertise ranges from materials for the generation and storage of renewable energy to functional building blocks for high-precision sensors, from new raw materials for bio-based polymers and nanocomposites to new structural materials for demanding applications. In synthesis, we rely on green processes and apply recycling-by-design.

We use computational design to gain a fundamental understanding of structure-property relationships and accelerate the discovery of new materials. We conduct research on robotic platforms that enable automated material synthesis and AI-driven property optimization. With our application-oriented approach and the direct link to characterization, the Material Design activity field is connected to all BAM topics and offers competent support and specific know-how for material development.

Priority theme CCMAT

We investigate chemically complex materials (CCMat) to utilize the chemical diversity of highly concentrated multi-component materials, to determine the influence on the material properties and to determine the consequences for the stability and safety as well as the sustainability and environmental impact of multi-component materials.

Selected projects

ERC Starting Grant Mulitbonds

LME - Mitigating grain-boundary decohesion during liquid-metal embrittlement in advanced high-strength steels

Heat4Energy: Magnetic energy conversion of waste heat

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Selected publications

Intermittent cluster dynamics and temporal fractional diffusion in a bulk metallic glass, in: Nature Communications, 2024

Trapping and diffusion in high-pressure hydrogen charged CoCrFeMnNi high entropy alloy compared to austenitic steel 316L - ScienceDirect

Synergistic Catalytic Sites in High‐Entropy Metal Hydroxide Organic Framework for Oxygen Evolution Reaction

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Priority theme MAPs@BAM

BAM's Material Acceleration Platform bundles our automation expertise in the field of materials science and testing. We develop modular experiment modules, automatic testing and evaluation procedures and use artificial intelligence for efficient and autonomous test planning, prediction and data analysis.

Selected publications

Machine learning for efficient grazing-exit x-ray absorption near edge structure spectroscopy analysis: Bayesian optimization approach

Materials Acceleration Platforms (MAPs): Accelerating Materials Research and Development to Meet Urgent Societal Challenges

A Self-Driving Lab for Nano- and Advanced Materials Synthesis

Coordination of the European Research Community on Nuclear Materials for Energy Innovation

Further publications can be found in our database PUBLICA