The scientific program presented a cross-section of ongoing work in data-driven modeling, simulation workflows, and structured information extraction. NFDI-MatWerk contributed three lectures, a short pitch, one poster and a booth that introduced its data solutions and invited discussions on practical use cases.
The plenary lecture by Tillmann Hickel discussed how data science technologies support AI-driven material design. Several talks contributed further perspectives. Abril Azocar Guzman examined grain boundary segregation mechanisms using data-driven approaches. Yousef Rezek, together with Alexander Hartmaier, presented a unified data schema for microstructure evolution that enables multi-tool workflows in processing simulations. Elaheh Akhoundi contributed a poster on evaluating large language models for reliable structured data extraction in materials science.
NFDI-MatWerk was present with a booth that introduced participants to current solutions, tools and services, and possible applications for individual research scenarios. Throughout the conference, many discussions highlighted the importance of accessible data structures, interoperable tools, and shared knowledge resources in advancing AI-supported materials research. Sebastian Slawik provided a short presentation that invited attendees to explore the initiative in more detail and engage with its growing community.
The meeting underlined how interdisciplinary exchange contributes to practical and method-focused progress in the field. Additional information on the conference series, organized by the German Society for Materials Science (DGM), is available on the event homepage.