Insights into grain boundary energy structure-property relationships by examining computed [1 0 0] disorientation axis grain boundaries in Nickel

Erickson, Hunter; Homer, Eric R.

doi:10.1016/j.scriptamat.2020.03.062

Cited by 7 publications

(8 citation statements)

References 25 publications

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“…Using these BP fundamental zones, they found that GB energy in the Olmsted dataset varied smoothly for similar BP orientations of the same disorientation as a function of disorientation angle. This trend was later confirmed more generally by Erickson and Homer in their dataset of 346 [1 0 0] disorientation axis GBs [58].…”

Section: Introductionmentioning

confidence: 55%

“…This is readily solved when using CSL disorientations because the GB plane will be periodic for both grains if CSL lattice points are used when defining the supercell of the simulation. As such, all GBs used in this work are CSLs, but it should be noted that while low Σ CSLs are typically considered to be special, there is evidence against associating CSLs with special properties [58,[90][91][92]. Recent work showed that disorientation angle and BP are a better indicator of low GB energy than a low CSL Σ value [58].…”

Section: Gb Selection Proceduresmentioning

confidence: 99%

“…As such, all GBs used in this work are CSLs, but it should be noted that while low Σ CSLs are typically considered to be special, there is evidence against associating CSLs with special properties [58,[90][91][92]. Recent work showed that disorientation angle and BP are a better indicator of low GB energy than a low CSL Σ value [58]. In other words, the CSL framework is used for its utility, not any attempt to sample "special" GBs.…”

Section: Gb Selection Proceduresmentioning

confidence: 99%

“…Tschopp et al created a dataset of 174 symmetric and asymmetric tilt GBs in both Al and Cu [56], which are available for download [57]. Priedeman et al created a dataset of 126 [1 0 0] symmetric tilt grain boundaries [18] and Erickson and Homer created a dataset of 346 GBs, all with [1 0 0] disorientation axes [58], both of which are available for download [59]. Guziewski et al modified a Monte Carlo GB optimization approach by Banadaki and Patala [60] to create a dataset of 344 grain boundaries in Si and SiC [61].…”

Section: Introductionmentioning

confidence: 99%

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Examination of computed aluminum grain boundary structures and interface energies that span the 5D space of crystallographic character

Homer,

Hart,

Owens

et al. 2022

Preprint

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The space of possible grain boundary structures is vast, with 5 macroscopic, crystallographic degrees of freedom that define the character of a grain boundary. While numerous datasets of grain boundaries have examined this space in part or in full, we present a computed dataset of over 7304 unique aluminum grain boundaries in the 5D crystallographic space. Our sampling also includes a range of possible microscopic, atomic configurations for each unique 5D crystallographic structure, which total over 43 million structures. We present an overview of the methods used to generate this dataset, an initial examination of the energy trends that follow the Read-Shockley relationship, hints at trends throughout the 5D space, variations in GB energy when non-minimum energy structures are examined, and insights gained in machine learning of grain boundary energy structure-property relationships. This dataset, which is available for download, has great potential for insight into GB structure-property relationships.

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Section: Introductionmentioning

confidence: 55%

Section: Gb Selection Proceduresmentioning

confidence: 99%

Section: Gb Selection Proceduresmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Examination of computed aluminum grain boundary structures and interface energies that span the 5D space of crystallographic character

Homer,

Hart,

Owens

et al. 2022

Preprint

Self Cite

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“…All these calculations indicate that there is a simple linear relationship of GBEs between different metals having the same crystal structure. Furthermore, the functions that can quantitatively describes the GBE variations in the 5-D space of the five parameters defining GB structures were proposed for some FCC [ 24 , 31 ] and BCC [ 32 , 33 ] metals, based on the large GB sets. However, any variable of the five parameters is difficult to extract from the fitted functions for arbitrary GBs.…”

Section: Introductionmentioning

confidence: 99%

Survey of Grain Boundary Energies in Tungsten and Beta-Titanium at High Temperature

Wang

2021

Materials

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Heat treatment is a necessary means to obtain desired properties for most of the materials. Thus, the grain boundary (GB) phenomena observed in experiments actually reflect the GB behaviors at relatively high temperature to some extent. In this work, 405 different GBs were systematically constructed for body-centered cubic (BCC) metals and the grain boundary energies (GBEs) of these GBs were calculated with molecular dynamics for W at 2400 K and β-Ti at 1300 K and by means of molecular statics for Mo and W at 0 K. It was found that high temperature may result in the GB complexion transitions for some GBs, such as the Σ11{332}{332} of W. Moreover, the relationships between GBEs and sin(θ) can be described by the functions of the same type for different GB sets having the same misorientation axis, where θ is the angle between the misorientation axis and the GB plane. Generally, the GBs tend to have lower GBE when sin(θ) is equal to 0. However, the GB sets with the <110> misorientation axis have the lowest GBE when sin(θ) is close to 1. Another discovery is that the local hexagonal-close packed α phase is more likely to form at the GBs with the lattice misorientations of 38.9°/<110>, 50.5°/<110>, 59.0°/<110> and 60.0°/<111> for β-Ti at 1300 K.

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Inference and uncertainty propagation of GB structure-property models: H diffusivity in [100] tilt GBs in Ni

et al. 2021

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Insights into grain boundary energy structure-property relationships by examining computed [1 0 0] disorientation axis grain boundaries in Nickel

Cited by 7 publications

References 25 publications

Examination of computed aluminum grain boundary structures and interface energies that span the 5D space of crystallographic character

Examination of computed aluminum grain boundary structures and interface energies that span the 5D space of crystallographic character

Survey of Grain Boundary Energies in Tungsten and Beta-Titanium at High Temperature

Inference and uncertainty propagation of GB structure-property models: H diffusivity in [100] tilt GBs in Ni

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