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Quantifying Uncertainty from Mass-Peak Overlaps in Atom Probe Microscopy

Published online by Cambridge University Press:  14 February 2019

Andrew J. London Open the ORCID record for Andrew J. London [Opens in a new window]
Andrew J. London*
Affiliation:
United Kingdom Atomic Energy Authority, Culham Science Centre, Abingdon, Oxon, OX14 3DB, UK
*
Author for correspondence: Andrew J. London, E-mail: andy.london@ukaea.uk
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Abstract

There are many sources of random and systematic error in composition quantification by atom probe microscopy, often, however, only statistical error is reported. Significantly larger errors can occur from the misidentification of ions and overlaps or interferences of peaks in the mass spectrum. These overlaps can be solved using maximum likelihood estimation (MLE), improving the accuracy of the result, but with an unknown effect on the precision. An analytical expression for the uncertainty of the MLE solution is presented and it is demonstrated to be much more accurate than the existing methods. In one example, the commonly used error estimate was five times too small.

Literature results containing overlaps most likely underestimate composition uncertainty because of the complexity of correctly dealing with stochastic effects and error propagation. The uncertainty depends on the amount of overlapped intensity, for example being ten times worse for the CO/Fe overlap than the Cr/Fe overlap. Using the methods described here, accurate estimation of error, and the minimization of this could be achieved, providing a key milestone in quantitative atom probe. Accurate estimation of the composition uncertainty in the presence of overlaps is crucial for planning experiments and scientific interpretation of the measurements.

Keywords

APTatom probe tomographyconfidence intervaldecompositionerror barsmass spectrum analysismaximum likelihoodoverlap solvingpeak deconvolution
Type
Data Analysis
Information
Microscopy and Microanalysis , Volume 25 , Special Issue 2: Atom Probe Tomography and Microscopy APT&M 2018 , April 2019 , pp. 378 - 388
Copyright
Copyright © Microscopy Society of America 2019 

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