Defining clusters in APT reconstructions of ODS steels

Williams, Ceri A.; Haley, Daniel; Marquis, Emmanuelle A.; Smith, George Davey; Moody, Michael P.

doi:10.1016/j.ultramic.2012.12.011

Cited by 71 publications

(51 citation statements)

References 27 publications

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“…Clusters containing fewer solute atoms than a user-specified term N min are rejected to eliminate any small random clustering. An optimum d max value was selected for each irradiation condition/alloy combination based on the procedure proposed by Chen et al [22] and by Williams et al [23]. This method relies on the generation of a nearest neighbour distribution, comparing distances between the clustering species (Re in this case) with those from a randomized data set; d max is selected at a threshold value that excludes randomized clusters from the analysis.…”

Section: Apt Analysesmentioning

confidence: 99%

Ion-irradiation-induced clustering in W–Re and W–Re–Os alloys: A comparative study using atom probe tomography and nanoindentation measurements

et al. 2015

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This study examines clustering and hardening in W-2 at.% Re and W-1 at.% Re-1 at.% Os alloys induced by 2 MeV W + ion irradiation at 573 and 773 K. Such clusters are known precursors to the formation of embrittling precipitates, a potentially life-limiting phenomenon in the operation of fusion reactor components. Increases in hardness were studied using nanoindentation. The presence of osmium significantly increased postirradiation hardening. Atom probe tomography analysis revealed clustering in both alloys, with the size and number densities strongly dependent on alloy composition and irradiation temperature. The highest cluster number density was found in the ternary alloy irradiated at 773 K. In the ternary alloy, Os was found to cluster preferentially compared to Re. The implications of this result for the structural integrity of fusion reactor components are discussed. Crown

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Section: Apt Analysesmentioning

confidence: 99%

Ion-irradiation-induced clustering in W–Re and W–Re–Os alloys: A comparative study using atom probe tomography and nanoindentation measurements

et al. 2015

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“…Rigorous approaches to using the maximum separation algorithm have been developed; exploring the sensitivity of maximum separation, [127] examining a manifold of results with the variation of parameters, [128] and using simulations to determine optimal parameters. [129] It can be hoped that unsupervised machine learning approaches can be developed and trained in combination with APT data simulations.…”

Section: Clusterfinding and Algorithmsmentioning

confidence: 99%

Clustering in Age‐Hardenable Aluminum Alloys

et al. 2018

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This review gives an overview of the effects of clusters in various aluminum alloys. Characterization methods are discussed in general and results for the important AlMgSi alloys are presented in detail. Indirect characterization methods, such as hardness, tensile testing, electrical resistivity, differential scanning calorimetry, and positron annihilation spectroscopy are discussed, as well as atom probe tomography for the direct measurement of clusters. A particular focus is set on atom probe tomography, where possible artifacts influencing the cluster measurements as well as different cluster finding methods are summed up. A comprehensive summary of investigated alloys and cluster algorithm parameters is given. Moreover, the findings in AlMgSi alloys regarding clusters and changes upon different heat treatments are discussed, starting from early to the latest works. Drawn conclusions are discussed and compared to give a r esum e.

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“…The analysis is most sensitive to the selection of dmax and Nmin, which depend upon the amount of solute concentration in the alloy and the relative distribution of the solutes within the matrix [172,173]. Since other authors have observed composition changes of nanoclusters under irradiation [8,9,13,59,104,124,174], it is considered likely that the dmax and Nmin values may also differ for each specimen.…”

Section: Reconstructionmentioning

confidence: 99%

“…Note that the measured amounts of Fe and Cr may be overinflated within the clusters due to trajectory aberrations [173,177]. Additional calculations enabled by the cluster analysis output data are conducted.…”

Section: Reconstructionmentioning

confidence: 99%

“…In recent years, much effort has been placed on developing a standardized methodology for "best practices" of cluster analysis within the IVAS software, particularly by appropriate selection of analysis parameters dmax and Nmin [171][172][173]175,[200][201][202][203] (see Section 4.5.3). However, some aspects of the reconstruction process prior to the cluster analysis still lack standardization.…”

Section: Reconstruction and Cluster Analysis In Ivasmentioning

confidence: 99%

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The Mechanism of Radiation-Induced Nanocluster Evolution in Oxide Dispersion Strengthened and Ferritic-Martensitic Alloys

Swenson¹

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Defining clusters in APT reconstructions of ODS steels

Cited by 71 publications

References 27 publications

Ion-irradiation-induced clustering in W–Re and W–Re–Os alloys: A comparative study using atom probe tomography and nanoindentation measurements

Ion-irradiation-induced clustering in W–Re and W–Re–Os alloys: A comparative study using atom probe tomography and nanoindentation measurements

Clustering in Age‐Hardenable Aluminum Alloys

The Mechanism of Radiation-Induced Nanocluster Evolution in Oxide Dispersion Strengthened and Ferritic-Martensitic Alloys

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