By clicking on “Allow”, you enable us to gather statistical information that will help us better understand how visitors use our website.
This is done ✓ anonymously and without collecting personal data, ✓ without cookies, ✓ on servers in Germany ✓ and without any data being transmitted to third parties.
The behaviour of materials is controlled by properties and processes at the atomic level. A fundamental understanding of structure-property relationships and how they change at every step of the materials value chain is key to the development of technical innovations and solutions to the major challenges associated with their safety and sustainability. The ever-increasing power of digital tools for simulation and data-driven materials science enables more targeted materials development for the reliable use of functional and structural materials and thus high-performance components. Ab initio simulations allow the calculation of material parameters without relying on empirical assumptions and experimental adjustments. Digital twins significantly accelerate material development, material testing and life cycle assessment. With a broad range of methods, it is therefore possible to predict new materials and their properties with the help of computer simulations and thus contribute to their safety and sustainability.
The newly founded Materials Informatics division is integrated into BAM's digital materials research initiative and focuses on computer-aided materials design and materials testing on an atomic, meso and nano scale. The entire length scale is covered in cooperation with the Materials Engineering Department, the Safety of Structures Department and the Component Safety Department.
The work of the department is carried out in close cooperation with experimental groups at BAM and our network partners with the aim of jointly identifying relevant/exciting issues in materials science and gaining a comprehensive understanding of materials under real conditions.
Projects:
SFB1394: Structural and Chemical Atomic Complexity: From Defect Phase Diagrams to Material Properties (2. Phase, C05 + T01n)
NFDI-MatWerk: National research data infrastructure for materials science & engineering
MaterialDigital:Innovation platform Material Digital (MaterialDigital) - Sub-project: Networking
further information
Fields of expertise
• Developing an understanding of materials in the context of fundamental principles of solid state physics, materials chemistry and quantum mechanics
• Simulation of material properties on the electronic and atomic scale with ab initio simulations, as well as their use for multiscale simulations
• Prediction of phase stabilities and transitions at finite temperatures based on methods of ab initio thermodynamics (incl. anharmonicities, magnetism, configurational entropy and coupling effects)
• Study of the chemistry and physics of defects and their significance for the behavior of microstructures and components (defect phase diagrams
• Design of materials for both structural and functional requirements using high-throughput calculations and machine learning
• Understanding the role of hydrogen in the failure of materials and new energy materials
• Development of workflow solutions for complex simulation protocols
Main activities
• Ab initio simulation of metallic alloys and other materials
• Explanation of experimental phenomena under consideration of real conditions (temperature, impurities, mechanical load, ...)
• Development of multiphysical and multiscale approaches to materials research
• Calculations on the thermodynamics of defects with a focus on interfaces, grain boundaries and surfaces
• Studies of the interaction of microstructure and corrosion
• Studies of the interaction of hydrogen with the microstructure of metallic materials (hydrogen embrittlement and storage)
• Application of machine learning methods for the prediction and understanding of materials and their safety
• Development and coordination of working and development environments for workflows (simulation protocols and experimental processes)
• Combination of workflows with FAIR databases in which experimental and calculated results are merged
• Development of concepts for data quality in material simulation and prediction of descriptors
Publications of the division
In the database PUBLICA you will find publications by BAM employees.
