Spatial Distribution Maps for Atom Probe Tomography

Geiser, B.; Kelly, Tom; Larson, David J.; Schneir, J.; Roberts, Jay P.

doi:10.1017/s1431927607070948

Cited by 177 publications

(108 citation statements)

References 12 publications

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“…[96] Crystallographic pole regions are often present when Al alloys are investigated with APT. With the use of spatial distribution maps (SDM) [108] or other techniques where the inter-planar lattice spacings can be measured, the reconstruction can be calibrated. Often the protocol based on a modified stereographic projection is used for the reconstruction, [109] here the two parameters (namely the image compression factor and the field factor times the evaporation field) can be used to tune the reconstruction, so that the inter-planar distances in the atom map fit to the real inter-planar distances.…”

Section: Functionalitymentioning

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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Section: Functionalitymentioning

confidence: 99%

Clustering in Age‐Hardenable Aluminum Alloys

et al. 2018

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“…Among the outputs of this approach are mean precipitate size, shape and composition. While this approach is well suited for crystallographic analysis, the extensive computer memory requirements and limited resolution away from the poles prevents the ability to define the detailed shape and interface of precipitates [6]. Finally, a friends-of-friends approach for analyzing phases has shown promise [10,17].…”

Section: Introductionmentioning

confidence: 99%

A graph-theoretic approach for characterization of precipitates from atom probe tomography data

Samudrala

Wodo

Suram

et al. 2013

Computational Materials Science

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“…For these types of systems, the crystallography serves as an internal calibration standard for constraining the reconstruction parameters [5]. A spatial distribution map (SDM) can be calculated to extract atomic-spacing information for feedback to the reconstruction to promote high accuracy [6].…”

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confidence: 99%

Approaches for Promoting Accurate Atom Probe Reconstruction

et al. 2016

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Comparison of atom probe tomography (APT) results from different instruments, different users, or different samples requires confidence in overall reconstruction accuracy. The conventional reconstruction algorithm utilizes a single point-projection onto a spherical surface [1,2]. Although there are a limited number of parameters used to prescribe how detector events are converted to a 3D set of reconstructed coordinates, some constraints are necessary to ensure minimal precision and accuracy. Key inputs in the reconstruction algorithm used in the commercially available IVAS software (CAMECA Instruments, Inc.) include ionic volume, detection efficiency, image compression factor (ICF), either tip radius (initial or final) or the product of geometrical field factor (k) and evaporation field (F), sphere-to-cone ratio, and radial evolution procedure (voltage, shank angle, or tip profile) [3]. When quality protocols are implemented, reliable comparisons can be made [4]. The available approaches for properly choosing reconstruction parameters will be the focus of this presentation.

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Spatial Distribution Maps for Atom Probe Tomography

Cited by 177 publications

References 12 publications

Clustering in Age‐Hardenable Aluminum Alloys

Clustering in Age‐Hardenable Aluminum Alloys

A graph-theoretic approach for characterization of precipitates from atom probe tomography data

Approaches for Promoting Accurate Atom Probe Reconstruction

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