Imatge de la portada

Beschleunigtes Materialdesign durch künstliche Intelligenz im Forschungsdatenmanagement

Using the example of polyurethane foam structures, this work develops a modular, FAIR workflow for data-driven materials development. Through AI-based segmentation, generative 3D models, and simulations, microstructural properties are automatically analysed and mechanical characteristics are reliabl...

Descripció completa

Guardat en:
Autor principal: Griem, Lars Christoph
Format: Online
Idioma:alemany
Publicat: KIT Scientific Publishing 2026
Matèries:
FAIR
Generative AI
Generative KI
Materialentwicklung
Materials Design
Research Data Management
Segmentation
Segmentierung
Forschungsdatenmanagement
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TG Mechanical engineering and materials::TGB Mechanical engineering
Accés en línia:2192-9963 (Online)
Etiquetes: Afegir etiqueta
Sense etiquetes, Sigues el primer a etiquetar aquest registre!
Sumari:Using the example of polyurethane foam structures, this work develops a modular, FAIR workflow for data-driven materials development. Through AI-based segmentation, generative 3D models, and simulations, microstructural properties are automatically analysed and mechanical characteristics are reliably predicted. The generic workflows and transparent data management accelerate the development process and can be flexibly applied to other materials.

Ítems similars