Single-Ion Deconvolution of Mass Peak Overlaps 301
composition measurements, and similarly London et al. (2015a) implemented a method for deconvoluting peak overlaps of individual clusters. Therefore, it is possible to use the additional spatial information available in the data to improve the reliability of the mass spectrum analysis. This is especially important when the extent of peak overlaps varies spatially across an analyzed volume. Recently, algorithmic development has allowed mea-
surements of local concentration (Chen et al., 2014), solute distribution (Stephenson et al., 2014), and spectral analysis (Cairney et al., 2015), made at the atomic scale. These analyses use the ions themselves as the spatial basis of the calculations. This transfers the selection of the scale of the digitization of the data from a voxel size (Miller, 1992) to an environment around every ion, such as by a sphere size or number of nearest neighbors. Therefore, we aim to couple this local, atomic scale, spatial
basis with mass spectrum analysis to resolve peak overlaps with the maximum possible spatial resolution. As such, we detail an implementation of a new ion-by-ion methodology where the identity of each ion, obscured by peak overlap, is resolved by examining the isotopic abundance of their immediate sur- roundings. By confining the deconvolution to the smallest volume possible, we retain the best possible spatial resolution. Equipped with this new tool, we demonstrate how existing compositional and spatial analysis can be improved. The new method is explained and applied to real data, and discussions of the limits are given.
MATERIALS ANDMETHODS
We present two case studies from two different materials. One material is an oxide dispersion strengthened (ODS) steel (Fe–0.3Ti–0.3Y2O3 wt%, London et al., 2015b), which contains Y–Ti–oxide clusters, and the other is a maraging steel (Fe–7Ni–10Cr–8Co–3Mo–1.80Al wt%, Martin et al., 2016), which contains Mo and NiAl particles. Both data sets were acquired on a LEAP 3000X HR (Imago, USA) in laser pulsing mode with a 0.4 nJ pulse energy and 532nm laser. In the ODS steel, the principal overlaps occur between the oxide-containing species of the oxide clusters (e.g., TiO2+ andO2
+). In the maraging steel, an overlap exists between the
Al+ and Fe2+ ions. Now we turn to the per-ion deconvolution method, which
has four main steps, detailed below, which includes the following: (1) defining the ions whose identities are obscured by peak overlap in the mass spectrum, (2) characterizing the local environment around each of these ions in the recon- struction, (3) deconvoluting the overlap, and (4) assigning the new ionic identity. The required inputs are the 3D positions andm/z values, a definition of what constitutes a peak overlap, and a definition of the ions present in the data.
Defining Overlaps
The initial step of the per-ion deconvolution is the same as any other method that deconvolutes peak overlaps: all
δm / ffiffiffiffimp (Larson et al., 2013). Therefore, we define the width of a specific peak by two upper and lower bounds which confine a particular peak window:
m z
windows of two or more peaks overlap, those ions are con- sidered directly overlapped. The positions and identities of overlapped ions can be visualized as per Figure 1. This example illustrates Fe2O2+ and TiO+ overlap at four m/z positions, TiO+ and CrO+ overlap at 65.9 Da, and CrO+ and Ga+ overlap at 68.9 Da. Although Fe2O2+ and CrO do not overlap, because TiO+ overlaps with both Fe2O2+ and CrO+, the solutions of these overlaps are interdependent and form an overlap group. However, the solution to each overlap group is independent of other groups of ions. Thus, the groups may be considered separately, which simplifies the peak deconvolution. During this step, a check for rank deficiency is made as
i the m/z value of the ith peak. If the resulting peak z
++ ions overlap, there are two ions and only one peak; therefore this overlap group is rank deficient and cannot
there needs to be at least as many m/z ranges as ions in each overlap group. For example, if the mono-isotopic P+ and P2
i
-P1: m z
1 2
i
<peakwindow< m z
i
+ P2: m z
1 2
i
where P1 and P2 are the lower and upper bound parameters and m
possible “direct” overlaps must be defined from (1) a list of potential ion species likely to be observed in the analysis of the specific specimen, and (2) a given minimum peak spacing. It is very difficult to derive, from the data alone, what ions are present; therefore a list of ion species should be specified by the user. The criteria for two peaks to be considered overlapped is based on a minimum spacing of the peaks in the m/z spectrum, below which two or more peaks cannot be resolved as separate peaks. Practically, this value depends on many individual variables including the speci- men, experimental parameters (e.g., flight length and evaporation voltage) and the measured m/z for the peak position. The peaks have approximately constant width in the time-of-flight spectrum and therefore peaks in the m/z spectrum get wider as the measured m/z increases,
Figure 1. A schematic showing which ion species overlap and at which mass-to-charge state positions. Ions are named in ovals, the overlapping positions are shown by labeled lines and connected ions form an “overlap group.” The line thickness indicates the product of the isotopic abundances of the overlapped peaks, and therefore “overlap intensity” if the ionic quantities were equal. All values in Dalton.
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