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@ARTICLE{Steinberger:910955,
author = {Steinberger, Dominik and Issa, Inas and Strobl, Rachel and
Imrich, Peter J. and Kiener, Daniel and Sandfeld, Stefan},
title = {{D}ata-mining of in-situ {TEM} experiments: {T}owards
understanding nanoscale fracture},
journal = {Computational materials science},
volume = {216},
issn = {0927-0256},
address = {Amsterdam [u.a.]},
publisher = {Elsevier Science},
reportid = {FZJ-2022-04283},
pages = {111830 -},
year = {2023},
abstract = {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.},
cin = {IAS-9},
ddc = {530},
cid = {I:(DE-Juel1)IAS-9-20201008},
pnm = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
(SDLs) and Research Groups (POF4-511) / MuDiLingo - A
Multiscale Dislocation Language for Data-Driven Materials
Science (759419)},
pid = {G:(DE-HGF)POF4-5111 / G:(EU-Grant)759419},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000882200400008},
doi = {10.1016/j.commatsci.2022.111830},
url = {https://juser.fz-juelich.de/record/910955},
}