Clustering and nearest neighbour distances in atom probe tomography: The influence of the interfaces

T. Philippe; O. Cojocaru-MirÉdin; S. Duguay; D. Blavette

doi:10.1111/j.1365-2818.2009.03359.x

Clustering and nearest neighbour distances in atom probe tomography: The influence of the interfaces

T. Philippe
, O. Cojocaru-MirÉdin
, S. Duguay
, D. Blavette

Research output: Contribution to journal › Article › peer-review

Abstract

Summary The statistical 1NN method is an elegant way to derive the composition of small B-enriched clusters in a random AB solid solution from 3D atomic fields. An extension of this method is proposed that includes the contribution of interface region and provides an estimate of the core composition of clusters. This model is applied to boron-implanted silicon containing boron-enriched clusters. A comparison with the previous model is performed. This new approach gives relevant information, i.e. the core composition of clusters and the cluster-matrix interface width.

Original language	English
Pages (from-to)	72-77
Number of pages	6
Journal	Journal of Microscopy
Volume	239
Issue number	1
DOIs	https://doi.org/10.1111/j.1365-2818.2009.03359.x
Publication status	Published - 1 Jan 2010
Externally published	Yes

Keywords

1NN method
Atom-probe tomography
Clustering
Interface
Nearest neighbour distances
Statistics

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10.1111/j.1365-2818.2009.03359.x

Cite this

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abstract = "Summary The statistical 1NN method is an elegant way to derive the composition of small B-enriched clusters in a random AB solid solution from 3D atomic fields. An extension of this method is proposed that includes the contribution of interface region and provides an estimate of the core composition of clusters. This model is applied to boron-implanted silicon containing boron-enriched clusters. A comparison with the previous model is performed. This new approach gives relevant information, i.e. the core composition of clusters and the cluster-matrix interface width.",

keywords = "1NN method, Atom-probe tomography, Clustering, Interface, Nearest neighbour distances, Statistics",

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AU - Philippe, T.

AU - Cojocaru-MirÉdin, O.

AU - Duguay, S.

AU - Blavette, D.

PY - 2010/1/1

Y1 - 2010/1/1

N2 - Summary The statistical 1NN method is an elegant way to derive the composition of small B-enriched clusters in a random AB solid solution from 3D atomic fields. An extension of this method is proposed that includes the contribution of interface region and provides an estimate of the core composition of clusters. This model is applied to boron-implanted silicon containing boron-enriched clusters. A comparison with the previous model is performed. This new approach gives relevant information, i.e. the core composition of clusters and the cluster-matrix interface width.

AB - Summary The statistical 1NN method is an elegant way to derive the composition of small B-enriched clusters in a random AB solid solution from 3D atomic fields. An extension of this method is proposed that includes the contribution of interface region and provides an estimate of the core composition of clusters. This model is applied to boron-implanted silicon containing boron-enriched clusters. A comparison with the previous model is performed. This new approach gives relevant information, i.e. the core composition of clusters and the cluster-matrix interface width.

KW - 1NN method

KW - Atom-probe tomography

KW - Clustering

KW - Interface

KW - Nearest neighbour distances

KW - Statistics

U2 - 10.1111/j.1365-2818.2009.03359.x

DO - 10.1111/j.1365-2818.2009.03359.x

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SP - 72

EP - 77

JO - Journal of Microscopy

JF - Journal of Microscopy

IS - 1

ER -

Clustering and nearest neighbour distances in atom probe tomography: The influence of the interfaces

Abstract

Keywords

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