Abstract
In this study, it is presented an analytical model of chemical composition correction for nanoclusters observed by atom probe tomography, tacking into account artefacts that can bias the measured chemical compositions. After a detailed description of the model, it is exposed how it can be directly used from reconstructed dataset. Then it is applied to nanoparticles observed in an oxide dispersion strengthened steel. The model results coincide with experimental ones demonstrating its ability to quantify and correct the chemical composition bias resulting from the field evaporation. Since the analytical model does not provide explanation about the origin of the bias, field evaporation simulation are used to interpret the results. According to the simulation, composition and morphological biases result from a cross-over of ions trajectories.
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