
Simulations for Field Ion Emission Microscopy Techniques
Field ion emission microscopy techniques are a group of characterization tools employing humungous electric fields. Atom probe tomography (APT), field ion microscopy (FIM), field emission microscopy (FEM), analytical field ion microscopy (AFIM) are the few of these characterization tools usually termed under field ion emission techniques. The strong fields applied (106-1010 V/m), induce a host of interesting phenomena at/near the specimen surface. Understanding the effect of electric fields and the local goemetry of the sample itself are of vital interest to develop fundemental theories and validate the experimental results. Using density functional theory (DFT) and python based analysis algorithms, we have several projects to aid and inform these characterization routines, to advance and enable new horizons for field ion emission techniques.
Field ion emission microscopy techniques rely on enormous electric fields of 106-1010 V/m. These electric field magnitudes are attained by the virtue of the specimen shape, usually rendered as a sharp needle with end radius typically less than 100 nm. The regularly used, near atomic scale characterization tools in these techniques, such as APT and FIM, utilize the field enabled phenomena such as field evaporation and field ionization. The presence of electrostatic field often leads to a myriad of complex phenomena at and near the surface, which often lead to uncertainities also in experimental data. To understand them at an electronic and atomic scale, we employ DFT simulations with high electric fields. For including electric fields in periodic plane wave DFT simulations, we employ the generalised dipole correction developed in the Field-Controlled Evaporation Mechanisms for Surface Atoms project.

Using these simulations we evaluate the electric field induced evaporation mechanisms of surface atoms. Initial results have suggested a strong dependence of evaporation path of an atom on the local neighborhood. Hence it is critical to understand theinteraction of local neighborhood including defects with the applied electric field. As it is also possible to image material defects in FIM. Recording images with FIM under field-evaporating conditions, combined with atomic configuration reconstruction, is at the heart of three-dimensional field ion microscopy (3D-FIM). This approach enables the visualization and reconstruction of crystalline defects at atomic resolution. Despite its advantages, debates remain around the origins of observed vacancies and the potential artifacts introduced by high electrostatic fields. By modeling stepped Ni and Pt surfaces with kinks, simulations were performed using the repeated-slab approach with a (971) surface orientation. The introduction of an electrostatic field up to 4 V/Å revealed that vacancy formation on electrified metal surfaces is more challenging compared to field-free cases. These fields also introduce kinetic barriers to vacancy annihilation mechanisms. These findings provide critical insight into field evaporation models and help resolve long-standing questions about artifacts in 3D-FIM. It is also important to understand the image formation mechanism in FIM. We develop a theory to simulate the orbital contrast in FIM due to the electronic structure at the surface in this project.
One other effect of the electric field is their effect on adsorption and surface diffusion energies. These aspects of electric field impact are dealt in surface phase diagrams for field evaporation project.

difference is shown in the color bar with a dashed black line.
Field evaporation from ionic or covalently bonded materials introduces additional complexities, as it often leads to the emission of molecular ions.
Under the influence of the intense electrostatic fields the molecular ions emitted are usually metastable and are prone to dissociation. These molecular ion dissociations can potentially alter the analytical performance of APT. Neutral molecules formed during dissociation can escape detection or distort time-of-flight measurements, leading to inaccuracies in composition analysis. In this project we focused on the dissociations seen in FeO, Fe₂O₃, and Fe₃O₄ across various experimental conditions, and also predicted dissociation reactions using DFT, taking into account the spin states of molecules. By mapping these reactions onto multi-hit ion correlation histograms, their existence was validated experimentally using automated Python routines. These analyses revealed the significant role of dissociation products in affecting the reliability of APT when analyzing iron oxides.
Through the combined use of DFT simulations and advanced Python algorithms, the projects described here aim to bridge gaps in understanding and improve the accuracy of these techniques under the wider efforts in method developments in field ion emission microscopy techniques. The insights generated are essential for interpreting experimental data and advancing the potential of these powerful characterization tools.