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ATOMIC-scale foundation of a Physics-based Interface Engineering in crystalline materials

CORDIS · observation · Publication date unknown

perties. Despite extensive studies, a comprehensive understanding of slip transfer—how dislocations propagate across interfaces—remains elusive. AtomicPIE integrates atomistic simulations, generative machine learning models, and enhanced discrete dislocation dynamics to address this gap. By simulating crystalline defects and their interactions, the project employs Nye dislocation densities to bridge atomic- to micro-scale modeling. A key innovation is the use of machine learning to predict complex Nye dislocation fields for mesoscale simulations. The framework developed within AtomicPIE will be validated through experiments and cross-scale molecular dynamics, focusing on ultra-fine-grain aluminum alloys. AtomicPIE aims to establish a physics-based understanding of slip transfer at interfaces, paving the way for advanced materials design and interface engineering.

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recordType

award

status

SIGNED

region

EU

value

1999357

unit

EUR