TY  - JOUR
AU  - Steinberger, Dominik
AU  - Issa, Inas
AU  - Strobl, Rachel
AU  - Imrich, Peter J.
AU  - Kiener, Daniel
AU  - Sandfeld, Stefan
TI  - Data-mining of in-situ TEM experiments: Towards understanding nanoscale fracture
JO  - Computational materials science
VL  - 216
SN  - 0927-0256
CY  - Amsterdam [u.a.]
PB  - Elsevier Science
M1  - FZJ-2022-04283
SP  - 111830 -
PY  - 2023
AB  - 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.
LB  - PUB:(DE-HGF)16
UR  - <Go to ISI:>//WOS:000882200400008
DO  - DOI:10.1016/j.commatsci.2022.111830
UR  - https://juser.fz-juelich.de/record/910955
ER  -