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

Publikationen: Beitrag in FachzeitschriftArtikelForschung(peer-reviewed)

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Data-mining of in-situ TEM experiments: Towards understanding nanoscale fracture. / Steinberger, Dominik; Issa, Inas; Strobl, Rachel et al.
in: Computational materials science, Jahrgang 216.2023, Nr. 5 January, 111830, 05.01.2023.

Publikationen: Beitrag in FachzeitschriftArtikelForschung(peer-reviewed)

Vancouver

Steinberger D, Issa I, Strobl R, Imrich PJ, Kiener D, Sandfeld S. Data-mining of in-situ TEM experiments: Towards understanding nanoscale fracture. Computational materials science. 2023 Jan 5;216.2023(5 January):111830. Epub 2022 Nov 2. doi: 10.1016/j.commatsci.2022.111830

Author

Steinberger, Dominik ; Issa, Inas ; Strobl, Rachel et al. / Data-mining of in-situ TEM experiments : Towards understanding nanoscale fracture. in: Computational materials science. 2023 ; Jahrgang 216.2023, Nr. 5 January.

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@article{dbbd0eb2600a46c59b35e2f354e1fba4,
title = "Data-mining of in-situ TEM experiments: Towards understanding nanoscale fracture",
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.",
keywords = "Computational analysis, Data-mining, Dislocations, In-situ TEM, Nanoscale fracture",
author = "Dominik Steinberger and Inas Issa and Rachel Strobl and Imrich, {Peter Julian} and Daniel Kiener and Stefan Sandfeld",
note = "Publisher Copyright: {\textcopyright} 2022 The Authors",
year = "2023",
month = jan,
day = "5",
doi = "10.1016/j.commatsci.2022.111830",
language = "English",
volume = "216.2023",
journal = "Computational materials science",
issn = "0927-0256",
publisher = "Elsevier",
number = "5 January",

}

RIS (suitable for import to EndNote) - Download

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 -