Data-mining of in-situ TEM experiments: Towards understanding nanoscale fracture
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In: Computational materials science, Vol. 216.2023, No. 5 January, 111830, 05.01.2023.
Research output: Contribution to journal › Article › Research › peer-review
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TY - JOUR
T1 - Data-mining of in-situ TEM experiments
T2 - Towards understanding nanoscale fracture
AU - Steinberger, Dominik
AU - Issa, Inas
AU - Strobl, Rachel
AU - Imrich, Peter Julian
AU - Kiener, Daniel
AU - Sandfeld, Stefan
N1 - Publisher Copyright: © 2022 The Authors
PY - 2023/1/5
Y1 - 2023/1/5
N2 - 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.
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.
KW - Computational analysis
KW - Data-mining
KW - Dislocations
KW - In-situ TEM
KW - Nanoscale fracture
UR - http://www.scopus.com/inward/record.url?scp=85143820226&partnerID=8YFLogxK
U2 - 10.1016/j.commatsci.2022.111830
DO - 10.1016/j.commatsci.2022.111830
M3 - Article
AN - SCOPUS:85143820226
VL - 216.2023
JO - Computational materials science
JF - Computational materials science
SN - 0927-0256
IS - 5 January
M1 - 111830
ER -