| Summary: | Recent advances in materials modelling, characterization and materials informatics suggest that deep integration of such methods can be a crucial aspect of the Industry 5.0 revolution, where the fourth industrial revolution paradigms are combined with the concepts of transition to a sustainable, human-centric and resilient industry. We pose a specific deep integration challenge beyond the ordinary multidisciplinary modelling/characterization research approach in this short communication with research and innovation as drivers for scientific excellence. Full integration can be achieved by developing common ontologies across different domains, enabling meaningful computational and experimental data integration and interoperability. On this basis, fine-tuning of adaptive materials modelling/characterization protocols can be achieved and facilitate computational and experimental efforts. Such interoperable and meaningful data combined with advanced data science tools (including machine learning and artificial intelligence) become a powerful asset for materials scientists to extract complex information from the large amount of data generated by last generation characterization techniques. To achieve this ambitious goal, significant collaborative actions are needed to develop common, usable, and sharable digital tools that allow for effective and efficient twinning of data and workflows across the different materials modelling and characterization domains.
|
|---|