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Atom probe tomography data analysis procedure for precipitate and cluster identification in a Ti-Mo steel.


ABSTRACT: An atom probe tomography data analysis procedure for identification of particles in a Ti-Mo steel is presented. This procedure has been used to characterise both carbide precipitates (larger particles) and solute clusters (smaller particles), as reported in an accompanying Mater. Sci. Eng. A paper [1]. Particles were identified using the maximum separation method (cluster-finding algorithm) after resolving peak overlaps at several locations in the mass spectrum. The cluster-finding algorithm was applied to the data in a two-stage process to properly identify particles having a bimodal size distribution. Furthermore, possible misidentification of matrix atoms (mainly Fe) due to the local magnification effect (from the difference in field evaporation potential between the matrix and precipitates) has been resolved using an atomic density approach, comparing that measured experimentally using APT to the theoretical density of both the matrix and particles.

SUBMITTER: Dhara S 

PROVIDER: S-EPMC5996495 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Atom probe tomography data analysis procedure for precipitate and cluster identification in a Ti-Mo steel.

Dhara S S   Marceau R K W RKW   Wood K K   Dorin T T   Timokhina I B IB   Hodgson P D PD  

Data in brief 20180327


An atom probe tomography data analysis procedure for identification of particles in a Ti-Mo steel is presented. This procedure has been used to characterise both carbide precipitates (larger particles) and solute clusters (smaller particles), as reported in an accompanying Mater. Sci. Eng. A paper [1]. Particles were identified using the maximum separation method (cluster-finding algorithm) after resolving peak overlaps at several locations in the mass spectrum. The cluster-finding algorithm was  ...[more]

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