Fraunhofer Institute for Mechanics of Materials IWMMaterials Informatics
Materials informatics involves the research, development and application of information regarding material properties, both physical data and theoretical and empirical models, and software tools for querying and evaluating these databases.
The materials informatics specialists at Fraunhofer IWM apply computer science methodologies to materials science problems. In this context, the "Software Solutions for Materials Informatics" team develops generic tools and methods for materials science, which are then applied to actual materials science problems by the "Applied Materials Informatics" team. These are adapted as necessary.
Innovations in the fields of materials science and manufacturing technology can ideally be supported by modern simulation methods and advanced experiments. The associated experimental, model and simulation data are taking on an ever-increasing volume and true treasures are hidden in this heterogeneous data world. In order to discover these treasures and to integrate further data in a simple way, we are working on innovative approaches from computer science. One goal is the seamless integration of data, models and simulation tools. This is achieved, among other things, with semantic methods, in which meta-information is made easier for the computer to process with the help of ontologies, and data transparency is also increased for the human user.
Current research topics
- Ontology: An important part of our research activity is the development of ontologies for different domains: materials development and representation including their microstructure and aggregate states (solid, liquid and gas), different manufacturing processes such as forming, machining or powder technology processes as well as component behavior in different application scenarios. In this context, we are also working on the further development of the European Materials Modeling Ontology (EMMO).
- Interoperability: Interoperability is of utmost importance for an efficient meshing of different systems (e.g. simulation software, databases, data rooms). This is possible via the introduction of a semantic layer using our Open Simulation Platform (OSP)/SimPhoNy technology.
- Data space: We are working on data spaces to digitally represent heterogeneous data including materials, processes and components as well as the life cycle itself. The associated knowledge graphs are managed based on a Data Space Management System (DSMS) and provide data analysis capabilities.
- Digital Twin: Semantic methods structure and enrich data from testing, simulation and production into an interoperable digital knowledge twin and facilitate the realization of data-reduced or data-enriched variants.
- Machine learning: Artificial intelligence (AI) and machine learning (ML) enable us to discover new relationships in the data and to realize data-driven models. Furthermore, we use machine learning to substitute simulation models, for example, in the form of surrogate models, where simulation data is used to train machine learning models, allowing optimizers to access fast ML models.
Select project examples and applications
- MarketPlace (EU) - Materials Modelling Marketplace for Increased Industrial Innovation
- Oyster (EU) - Open characterisation and modelling environment; Open Innovation Environment (OIE)
- NanoMECommons (EU) - Harmonisation of EU-wide nanomechanics protocols and relevant data exchange procedures
- Apache (EU) - Active & intelligent Packaging materials and display cases as a tool for preventive conservation of Cultural Heritage
- ReaxPro (EU) - Software Platform for Multiscale Modelling of Reactive Materials and Processes
- SimDome (EU) - Digital Ontology-based Modelling Environment for Simulation of materials
- Intersect (EU) - Interoperable Material-to-Device simulation box for disruptive electronics
- EOSC-Pillar (EU) - EOSC-Pillar aims to coordinate national Open Science efforts across Austria, Belgium, France, Germany and Italy, and ensure their contribution and readiness for the implementation of the European Open Science Cloud (EOSC)
- FORCE (EU) - Formulations and Computational Engineering
- OntoTrans (EU) - Provides an ontology-based Open Translation Environment
- OntoCommons (EU) - Ontology-driven data-documentation for industry commons
- SimPhoNy and Open Simulation Platform - SimPhoNy is an ontology-based open-source Python framework that promotes and enables interoperability between any 3rd-party software tool
Range of services in the field of material informatics
- Development and embedding of domain ontologies into higher-level ontologies (e.g. EMMO, BFO). Consideration of systematic approaches for the transformation of domain knowledge into a vocabulary and glossary in order to formulate sustainably usable ontologies via taxonomy.
- Interoperability is our topic: development and adaptation of software solutions for interoperable workflows with respect to data exchange, experimental and simulation workflows as well as the networking of experiment and simulation.
- Configuration and further development of data spaces for material, process and component data as well as development of tools for automated data upload
- Conception and realization of digital representations (digital twins) of materials, processes and components
- Application of machine learning
2024
Fliegener, S.; Rosenberger, J.; Luke, M.; Dominguez, J.; Morgado, J.; Kobialka, H.; Kraft, T.; Tlatlik, J., Digital methods for the fatigue assessment of engineering steels, Advanced Engineering Materials (2024) Art. 2400992, 17 pp. Link
Nahshon, Y.; Morand, L.; Büschelberger, M.; Helm, D.; Kumaraswamy, K.; Zierep, P.; Weber, M.; de Andres, P., Semantic orchestration and exploitation of material data: A dataspace solution demonstrated on steel and copper applications, Advanced Engineering Materials (2024) Art. 2401448, 21 pp. Link