Speaker
Descrizione
The increasing complexity of advanced materials design requires digital infrastructures capable of integrating modelling, simulation, data management, and analysis across multiple scales. In this context, automated and interoperable workflows can support more efficient, reproducible, and traceable computational studies, while providing structured data that can be reused within broader materials informatics approaches.
In this work, we present automated multiscale simulation workflows for the design and characterization of advanced materials for industrial applications. The workflows orchestrate heterogeneous physics-based modelling tools across different length and time scales, supporting computational tasks such as simulation setup, execution, property evaluation, data aggregation, analysis, and post-processing. Their modular architecture allows individual components to be adapted, extended, or reused according to different materials systems, modelling requirements, and application domains.
A key aspect of the approach is the systematic organization of simulation data and metadata throughout the workflow lifecycle, with the aim of supporting FAIR data principles. By linking input parameters, computational procedures, software versions, simulation outputs, and derived properties, the workflows improve the findability, accessibility, interoperability, and reusability of computational results. Automated metadata capture and provenance tracking enhance reproducibility and traceability, while enabling simulation data to be more easily compared with experimental information and reused in broader materials informatics contexts. This structured data handling also provides a basis for the integration of workflows with data-driven and AI-assisted frameworks.
The workflow environment supports scalable execution, from exploratory calculations to larger high-performance computing campaigns, and has been applied in industrial case studies within European research projects focused on innovative and bio-based materials, following the Safe-and-Sustainable-by-Design (SSbD) approach. These examples show how automated multiscale simulation workflows can contribute to more efficient and reproducible materials development by connecting predictive modelling, FAIR-oriented data management, and interoperable computational protocols within a unified digital framework.
| Giovane Ricercatore (under 40) | Yes |
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