True Atomic-Scale Imaging in Three Dimensions 217
Figure 8. a: Field-ion microscopy (FIM) image of undamaged tungsten specimen. b–d: Selected cropped FIM micro- graphs demonstrating increasing lattice radiation damage in tungsten samples self-implanted with increasing displace- ments per atom (dpa), implantation energies of 0.15MeV in (b), and 2MeV in (c) and (d) (Dagan et al., 2015).
The importance of the ability to observe directly and
locate subnanometer diameter boron clusters within the lattice and its defects cannot be overstated, as their study is the key to understanding the atomic-scale processes deter- mining the implantation of dopants into nanoscale devices. As stated above, the incorporation of dopants into nanoscale devices is crucial to their performance. As dopants are typi- cally introduced into the device geometry utilizing an ion implantation step and a subsequent annealing step, a fun- damental understanding of the formation and dissolution of defects and clusters is crucial for the optimization of nanoscale devices.
Automated Method
To make full use of FIM’s superior resolving power, an automated procedure for the “atom-by-atom” 3D recon- structions of FIM data were developed. As demonstrated in the pioneering research of Seidman et al. (e.g., Scanlan et al., 1974; Seidman et al., 1981), FIM can image individual 3D point defects, such as self-interstitials and vacancies, which they accomplished using the technology then available to them. In particular, accurate quantitative characterization of such features was achieved in the region adjacent to high Miller index poles, where the spatial resolution is sufficient to observe every individual atom on a plane. This capability is of great importance in studies related to the effects of radiation damage on structural materials for nuclear reac- tors. The reliable identification and mapping of the early stages of radiation damage can yield important insights into the mechanical properties of a nuclear reactor’s components. Figure 8 demonstrates evolving levels of lattice radiation damage in ion-implanted tungsten, a leading candidate material for fusion reactor components, as observed by FIM. Although the damage evolution with increasing implanta- tion dose is very clearly observed by FIM, the corresponding APT 3D reconstructions exhibited little to no difference in the distribution of tungsten atoms (Dagan et al., 2015). To detect, automatically, such fine features, a dedicated
3D reconstruction procedure was developed and adapted to the atomic resolution of the technique. The new automated approach transforms what would be an overwhelming amount of FIM micrographs, if assessed manually, recorded
within a controlled evaporation experiment, into a 3D atomic resolution reconstruction of the analyzed volume. The technique automatically identifies the atoms in the FIM image, and tracks the presence of each atomacross all images
from the time it first appears at the surface until it is finally field-evaporated. The characteristic atomic layer-by-layer imaging and
evaporation sequence is employed for the automation of the 3D reconstruction and is seen in Figure 9a, for a (222) plane in tungsten. As atoms at kink sites have higher electric fields they are preferentially imaged with respect to atoms in the center of an atomic plane. It is only after their field eva- poration that atoms from the center of an atomic plane are imaged because the local electric field conditions change. This repeating sequence is employed to estimate auto- matically the depth coordinate in a specific FIM image, in terms of interplanar spacing, as integrated intensity from the center of the pole decreases every time the last atoms of the plane are removed, as seen in Figure 9b. The dynamic nature of the FIM experiment poses sig-
nificant challenges to automated 3D reconstruction. As not all atoms on the same crystallographic plane are imaged simultaneously, a cross-image analysis is necessary to place them on the correct planes relative to one another. It is also the reason why the detection of crystal defects requires the 3D reconstruction of all atoms in the lattice, whereas a simpler 2D analysis on a representative image will not suffice. In 2D, a missing atom can be simply an atom evaporating prematurely. Moreover, the presence of defects will often break the familiar repeating sequence of field evaporation, necessitating the need for an overall recon- struction method (Dagan et al., 2016). Other challenges arise from the constantly changing
electric field conditions. With every single field-evaporation event the local electric field associated with individual atoms is redistributed above the remaining neighboring atoms, causing changes in the imaging intensities, spatial coordi- nates, and the observed diameter of the respective atoms from image to image. All these effects necessitate an adjus- table automated algorithm, which is able to track the same atom in each different image, detect its field-evaporation and the emergence of new atoms in its place nearby, and assign it to its correct crystallographic layer number.
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