Learning Atom Probe Tomography time-of-flight peaks for mass-to-charge ratio spectrometry

Ultramicroscopy(2022)

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摘要
In laser-assisted atom probe tomography, an important goal is to reconstruct the mass-to-charge ratio, (m/z), spectrum due to various ion species. In general, the probability mass function (pmf) associated with the time-of-flight (TOF) spectrum produced by each ion species is unknown and varies from species-to-species. Moreover, measuring pmfs for distinct ion species in calibration experiments is not practical. Here, we present a mixture model method to determine TOF pmfs that can vary from peak-to-peak. In this approach, we determine weights of candidate pmfs with a maximum likelihood method. In a proof-of-principle study, we apply our method to a TOF spectrum acquired from a silicon sample and determine intensity estimates of singly charged isotopes of silicon.
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关键词
Atom Probe Tomography,Cross-validation,Expectation Maximization algorithm,Machine learning,Maximum likelihood,Mixture model,Silicon isotopes
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