698 citations
- Technische Universität DresdenDE116 papers
- Leibniz Institute for Solid State and Materials ResearchDE26 papers
- Max Bergmann Zentrum für BiomaterialienDE18 papers
- Center for Advancing Electronics DresdenDE17 papers
- Chemnitz University of TechnologyDE8 papers
- Complexity and Topology in Quantum MatterDE8 papers
- Fraunhofer Institute for Electronic Nano SystemsDE8 papers
- Oakland UniversityUS8 papers
- Center for Systems Biology DresdenDE7 papers
- Centre National de la Recherche ScientifiqueFR6 papers
- Institució Catalana de Recerca i Estudis AvançatsES6 papers
- Institut Català de Nanociència i NanotecnologiaES6 papers
4 papers · 1 filter
Precise, efficient and flexible modeling of crystallizing elastomers based on physics-augmented neural networks
Konrad Friedrichs, Franz Dammaß, Karl A. Kalina +1
We propose a precise and efficient physics-augmented neural network (PANN) to model strain-induced crystallization in rubbery polymers. We demonstrate that the model can be flexibl…
Solid-State Dewetting of Polycrystalline Thin Films: a Phase Field Approach
Paul Hoffrogge, Nils Becker, Daniel Schneider +3
Solid-state dewetting is the process by which thin solid films break up and retract on a substrate, forming nanostructures. While dewetting of single-crystalline films is understoo…
Modeling dislocations in quasicrystals through amplitude equations
Marcello De Donno, Luiza Angheluta, Marco Salvalaglio
Quasicrystals (QCs) are a class of aperiodic ordered structures that emerge in various systems, from metallic alloys to soft matter and driven non-equilibrium systems. Within a mes…
When invariants matter: The role of I1 and I2 in neural network models of incompressible hyperelasticity
Franz Dammaß, Karl A. Kalina, Markus Kästner
For the formulation of machine learning-based material models, the usage of invariants of deformation tensors is attractive, since this can a priori guarantee objectivity and mater…