Data-mining of in-situ TEM experiments: Towards understanding nanoscale fracture

Dominik Steinberger, Inas Issa, Rachel Strobl, Peter Julian Imrich, Daniel Kiener, Stefan Sandfeld

Publikation: Beitrag in FachzeitschriftArtikelForschungBegutachtung

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The lifetime and performance of any engineering component, from nanoscale sensors to macroscopic structures, are strongly influenced by fracture processes. Fracture itself is a highly localized event; originating at the atomic scale by bond breaking between individual atoms close to the crack tip. These processes, however, interact with defects such as dislocations or grain boundaries and influence phenomena on much larger length scales, ultimately giving rise to macroscopic behavior and engineering-scale fracture properties. This complex interplay is the fundamental reason why identifying the atomistic structural and energetic processes occurring at a crack tip remains a longstanding and still unsolved challenge. We develop a new analysis approach for combining quantitative in-situ observations of nanoscale deformation processes at a crack tip with three-dimensional reconstruction of the dislocation structure and advanced computational analysis to address plasticity and fracture initiation in a ductile metal. Our combinatorial approach reveals details of dislocation nucleation, their interaction process, and the local internal stress state, all of which were previously inaccessible to experiments. This enables us to describe fracture processes based on local crack driving forces on a dislocation level with a high fidelity that paves the way towards a better understanding and control of local failure processes in materials.
FachzeitschriftComputational materials science
Ausgabenummer5 January
Frühes Online-Datum2 Nov. 2022
PublikationsstatusVeröffentlicht - 5 Jan. 2023

Bibliographische Notiz

Funding Information:
D.S. and S. S. acknowledge financial support from the European Research Council through the ERC Grant Agreement No. 759419 (MuDiLingo: ’A Multiscale Dislocation Language for Data-Driven Materials Science’). I.I. and D.K. acknowledge funding by the European Research Council under ERC Grant Agreement No. 771146 (TOUGHIT: ’Tough Interface Tailored Nanostructured Metals’).

Publisher Copyright:
© 2022 The Authors

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