TMS 2014 Supplemental Proceedings 2014
DOI: 10.1002/9781118889879.ch33
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Microstructural Characterization of Shape Memory Alloys on the Atomic Scale

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Cited by 2 publications
(2 citation statements)
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“…Since the focus is placed on the energy densities of dislocation networks, these grainboundaries are identified in a post-processing step that constructs a surface mesh as a representation of grain-or phase boundaries as described in [30]. In order to ignore the energy contribution in these defects, any atom within a distance of 1.2 nm (about three times the lattice constant) is marked as being biased by a grain-boundary and is not considered in the subsequent analysis steps.…”
Section: Methodsmentioning
confidence: 99%
“…Since the focus is placed on the energy densities of dislocation networks, these grainboundaries are identified in a post-processing step that constructs a surface mesh as a representation of grain-or phase boundaries as described in [30]. In order to ignore the energy contribution in these defects, any atom within a distance of 1.2 nm (about three times the lattice constant) is marked as being biased by a grain-boundary and is not considered in the subsequent analysis steps.…”
Section: Methodsmentioning
confidence: 99%
“…Within 200,000 time-steps the pillar is compressed by 10%. This simulation is a realistic use-case, as it is a shortened re-run of a simulation published in [34]. In this test, each domain is handling a fairly large number of atoms and the load is changing slowly but steadily due to two mechanisms: First of all, atoms are forced to move downwards, causing the upper part of the simulation box becoming void of atoms over time.…”
Section: Nanopillar Compressionmentioning
confidence: 99%