Fraunhofer Institute for Mechanics of Materials IWMEuropean materials research becomes more integrated – however, data from laboratories, simulations and manufacturing currently reside in separate repositories, presenting opportunities to streamline the development of new materials. MaterialsCommons creates a federated digital infrastructure that, for the first time, connects all major European platforms, data sources, workflows and tools for materials research via a common access point and a shared semantic framework. This infrastructure enables data exchange, artificial intelligence (AI) and simulation workflows as well as self-driving labs to accelerate the materials development process by up to a factor of four. Six industry-relevant use cases in the fields of batteries, steel, additive manufacturing and microelectronics demonstrate the concrete benefits for companies.
Federated Digital Infrastructure for European Advanced Materials Research and Development
Ongoing research project
Project description
Market Needs and Opportunities
Although advanced materials are key to competitiveness, climate neutrality and strategic autonomy, European materials research remains digitally fragmented. Data from experiments, simulations and industrial manufacturing are stored in isolated silos. Different formats, incompatible platforms and a lack of semantic standards prevent efficient exchange. This fragmentation increases costs and delays the market introduction of new materials by years.
Contribution of the Project
MaterialsCommons addresses this challenge by establishing a federated digital infrastructure that, for the first time, connects all relevant European materials data repositories, workflow systems and artificial intelligence (AI) tools through a single access point. The project focuses on three technological domains: (1) semantic interoperability, ensuring that data from different systems and organizations is automatically compatible, (2) interoperable workflows that link simulations, experiments and machine learning across disciplines, and (3) secure, federated data spaces with IP protected data exchange in an industrial context.
The project’s economic relevance is demonstrated through six use cases with renowned industry partners in the battery, steel, additive manufacturing and microelectronics sectors. MaterialsCommons creates shared digital tools, data structures and workflows that simplify data exchange across organizational boundaries as well as creating the foundation for faster and more secure development processes. These include, among other things, AI supported analyses, the integration of simulation and experimentation, self-driving labs for automated experiments and secure, IP protected data exchange. In this way, MaterialsCommons strengthens Europe’s industrial leadership in the global competition for advanced materials while simultaneously supporting the European Green Deal by accelerating the development of sustainable, recyclable materials.
Via MaterialsCommons, in the future Fraunhofer IWM will be able to offer companies the following new services for research and development:
Automatic processing of measurement data into structured, reusable datasets (FAIR compliant)
Software solutions that automatically generate structured, machine-readable and standards-compliant datasets from raw measurement data such as mechanical tests or microstructure analyses.
The benefits include:
- Drastic reduction in the manual effort required for data documentation and processing
- Immediate usability of the generated data for artificial intelligence (AI) analyses and cross-company collaborations
- A robust data foundation for certification processes, standards compliance and digital twins
Target audience: Testing laboratories, materials manufacturers, R&D departments in the process and manufacturing industries
Connecting and leveraging materials data across the supply chain
Fraunhofer IWM supports companies in structuring and standardizing their materials data so that it can be automatically exchanged and utilized throughout the entire supply chain - both internally and in shared data spaces with partners - while eliminating the need for time-consuming interface development.
The benefits include:
- Automated materials data exchange throughout the entire supply chain, from raw materials processing to the final product
- Streamlined coordination processes through standardized, machine-readable data formats
- Data-driven optimization across company boundaries with minimal integration effort
Target Audience: Manufacturing companies, suppliers and companies participating in data space initiatives such as Catena-X or GAIA-X
Digital product passports for materials - EU-compliant and seamlessly integrated into industrial ecosystems
Development and implementation of digital materials passport solutions that comply with the European Union’s Ecodesign for Sustainable Products Regulation (ESPR) and can be seamlessly integrated into industrial data ecosystems based on the Asset Administration Shell (AAS, Industry 4.0 standard interface).
The benefits include:
- Efficient compliance with the regulatory requirements of the ESPR through standardized solutions
- Transparency regarding sustainability and circularity metrics for the organization's own products
- Future-proof data infrastructure for upcoming reporting obligations and regulatory requirements
Target audience: Product manufacturers, Original Equipment Manufacturers (OEMs) and companies with sustainability and compliance requirements
AI-based prediction of materials properties using distributed data - IP secure while protecting confidential production information
Accurate AI predictions of materials properties in components and products require data from various companies along the supply chain. Federated machine learning solves this problem and enables powerful predictive models while keeping production and formulation data within each company.
The benefits include:
- AI-powered property prediction while preserving confidential and sensitive production or formulation data
- Reduced experimental effort in materials qualification
- Faster time-to-market for new materials and alloys through data-driven development
Target Audience: Materials manufacturers, alloy developers and companies with confidential production data
