196 Ty J. Prosa and David J. Larson


Figure 3. The standard lift-out process as referred to in this review. The goal is to (a) identify, (b & c) extract material, additionally process and orient as necessary (not shown), (d) propagate sections to carrier tips which are eventually shaped by annular milling into the final shape necessary for an APT specimen (not shown). See text for a more complete description (figure modified from (Larson et al., 2011d)).


to help separate real compositional trends from artifacts (Larson, et al., 2011c; Shimizu et al., 2011; Kubota et al.,


2015). Variation in analysis direction and the ability to finely manipulate orientation are key specimen preparation options which will be discussed throughout this review.


CORRELATIVE METHODS;GRAIN AND PHASE BOUNDARIES


Figure 4. Example of a SEM compatible Axial Rotation Manip- ulator (ARM4™) manufactured by CAMECA Instruments, Inc. This version has two clips for securing samples and carrier tips (in this case two microtip coupons are shown as indicated by the red arrows). The axial rotation is accomplished by a 4-sided needle assembly, which is protected within a rectangular slot (black arrows, both positioned within the ARM platform [top], and removed for clarity [bottom]). This geometry enables accurate rotations in 90° increments.


interfaces exist between the sample surface and the ROI, analysis from the backside may allow for these regions to be avoided. If there is a substantial thickness of insulating material (thermal and/or electrical) present beneath the ROI, backside preparation may also prove useful, as this material can be removed from the final specimen. In addition, specimen shape distortions, and the resultant effects on data reconstruction (Larson et al., 2013a), can be affected by the


order of evaporation of regions with different evaporation fields. Performing analysis both in the top-down and backside orientations can provide meaningful information


As the implementation of APT expands into new application areas, there is a continuing desire to validate or correlate data with other well-established techniques. This correlative information can be used to calibrate or constrain re- constructions (Arslan et al., 2008; Thompson et al., 2009; Cojocaru-Mirédin et al., 2011; Haley et al., 2011; Larson et al., 2011; Hartshorne et al., 2014; Xiong & Weyland, 2014; Grenier et al., 2015; Herbig et al., 2015; Lefebvre et al., 2015), but it can also provide information on grain orientation (Taheri et al., 2010; Cojocaru-Mirédin et al., 2011; Babinsky et al., 2014, 2015; Takahashi et al., 2014; Chen et al., 2015, 2016; Herbig et al., 2015; Rice et al., 2015, 2016) and locations of defects and phase boundaries which can improve site-specific ROI targeting and placement (Cojocaru- Mirédin et al., 2011; Babinsky et al., 2014, 2015; Hartshorne et al., 2014; Chen et al., 2015, 2016; Herbig et al., 2015; Rice et al., 2015, 2016). FIB-based specimen prepara- tion certainly provides a means to characterize specimen shapes with scanning electron microscopy (SEM) during manufacture; however, the quality of the available information is often constrained by the diminishing electron-scattering volumes near the apex, which become vanishingly small for the majority of the analyzable region in


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