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PosgenPy: An Automated and Reproducible Approach to Assessing the Validity of Cluster Search Parameters in Atom Probe Tomography Datasets

Published online by Cambridge University Press:  21 September 2021

Przemysław Klupś Open the ORCID record for Przemysław Klupś [Opens in a new window] ,
Daniel Haley ,
Andrew J. London ,
Hazel Gardner ,
James Famelton ,
Benjamin M. Jenkins ,
Jonathan M. Hyde Open the ORCID record for Jonathan M. Hyde [Opens in a new window] ,
Paul A.J. Bagot Open the ORCID record for Paul A.J. Bagot [Opens in a new window]  and
Michael P. Moody
Przemysław Klupś*
Affiliation:
Department of Materials, University of Oxford, Oxford OX1 3PH, UK
Daniel Haley
Affiliation:
Department of Materials, University of Oxford, Oxford OX1 3PH, UK
Andrew J. London
Affiliation:
UK Atomic Energy Authority, Culham Science Centre, Abingdon OX14 3DB, UK
Hazel Gardner
Affiliation:
Department of Materials, University of Oxford, Oxford OX1 3PH, UK
James Famelton
Affiliation:
Department of Materials, University of Oxford, Oxford OX1 3PH, UK
Benjamin M. Jenkins
Affiliation:
Department of Materials, University of Oxford, Oxford OX1 3PH, UK
Jonathan M. Hyde
Affiliation:
National Nuclear Laboratory, Culham Science Centre, Abingdon OX14 3DB, UK
Paul A.J. Bagot
Affiliation:
Department of Materials, University of Oxford, Oxford OX1 3PH, UK
Michael P. Moody
Affiliation:
Department of Materials, University of Oxford, Oxford OX1 3PH, UK
*
*Corresponding author: Przemysław Klupś, E-mail: [email protected]
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Abstract

One of the main capabilities of atom probe tomography (APT) is the ability to not only identify but also characterize early stages of precipitation at length scales that are not achievable by other techniques. One of the most popular methods to identify nanoscale clustering in APT data, based on the density-based spatial clustering of applications with noise (DBSCAN), is used extensively in many branches of research. However, it is common that not all of the steps leading to the selection of certain parameters used in the analysis are reported. Without knowing the rationale behind parameter selection, it may be difficult to compare cluster parameters obtained by different researchers. In this work, a simple open-source tool, PosgenPy, is used to justify cluster search parameter selection via providing a systematic sweep through parameter values with multiple randomizations to minimize a false-positive cluster ratio. The tool is applied to several different microstructures: a simulated material system and two experimental datasets from a low-alloy steel . The analyses show how values for the various parameters can be selected to ensure that the calculated cluster number density and cluster composition are accurate.

Keywords

atom probe tomographycluster analysisDBSCANmaximum separation methodparameter selection
Type
Development and Computation
Information
Microscopy and Microanalysis , Volume 28 , Issue 4 , August 2022 , pp. 1066 - 1075
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Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Microscopy Society of America

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