Accounting for the Dead Time in Analysis of Time of Flight Secondary Ion Mass Spectrometry Data

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2018-12

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Abstract

Time of Flight Secondary Ion Mass Spectrometry (ToF SIMS) is a powerful tool for advanced surface analysis. It produces large data sets, which consist of mass spectra at each pixel at an imaged area. Many ToF SIMS instruments use a type of detector that suffers from two problems that lead to non-linearity in the measured sample properties: detector saturation and dead time. Linearity in this type of system is defined as the proportionality of the measured and true ion counts. Non-linearity can influence the interpretation of the data with methods such as multivariate analysis. “Detector saturation” happens when more than one ion arrives at the detector in the time interval related to one specific channel but the detector records only a single count. “Dead time” is when one event happens at a certain channel and the detector become insensitive to subsequent ions arriving within the dead time window. These problems both lead to under-counting of ions. In this thesis, we mainly focus on correcting for the dead time effects. Using extensive simulations, we first characterize the adverse effects of dead time on the output and evaluate quality of existing ways to “correct” for dead time effects. Then, we propose a novel method using the Maximum Likelihood Estimation (MLE) to estimate the true spectrum for the measured data. Specifically, we incorporate the statistical distribution of the dead time affected data in MLE, which leads to a new method for dead time correction.

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Time-of-flight mass spectrometry, Secondary ion mass spectrometry, Multivariate analysis, Surfaces (Technology)—Analysis

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