A position and energy-sensitive detector has been developed for atom probe tomography (APT) instruments in order to deal with some mass peak overlap issues encountered in APT experiments. Through this new type of detector, quantitative and qualitative improvements could be considered for critical materials with mass peak overlaps, such as nitrogen and silicon in TiSiN systems, or titanium and carbon in cemented carbide materials. This new detector is based on a thin carbon foil positioned on the front panel of a conventional MCP-DLD detector. According to several studies, it has been demonstrated that the impact of ions on thin carbon foils has the effect of generating a number of transmitted and reflected secondary electrons. The number generated mainly depends on both the kinetic energy and the mass of incident particles. Despite the fact that this phenomenon is well known and has been widely discussed for decades, no studies have been performed to date for using it as a means to discriminate particles energy. Therefore, this study introduces the first experiments on a potential new generation of APT detectors that would be able to resolve mass peak overlaps through the energy-sensitivity of thin carbon foils.

This article presents a fast and highly efficient algorithm developed to reconstruct a three-dimensional (3D) volume with a high spatial precision from a set of field ion microscopy (FIM) images, and specific tools developed to characterize crystallographic lattice and defects. A set of FIM digital images and image processing algorithms allow the construction of a 3D reconstruction of the sample at the atomic scale. The capability of the 3D FIM to resolve the crystallographic lattice and the finest defects in metals opens a new way to analyze materials. This spatial precision was quantified on tungsten, analyzed at different analyzing conditions. A specific data mining tool, based on Fourier transforms, was also developed to characterize lattice distortions in the reconstructed volumes. This tool has been used in simulated and experimental volumes to successfully locate and characterize defects such as dislocations and grain boundaries.

Atom probe tomography (APT) analysis conditions play a major role in the composition measurement accuracy. Preferential evaporation (PE), which significantly biases the apparent composition, more than other well-known phenomena in APT, is strongly connected to those analysis conditions. One way to optimize them, in order to have the most accurate measurement, is therefore to be able to predict and then to estimate their influence on the apparent composition. An analytical model is proposed to quantify the PE. This model is applied to three different alloys such as NiCu, FeCrNi, and FeCu. The model explains not only the analysis temperature dependence, as in an already existing model, but also the dependence to the pulse fraction and the pulse frequency. Moreover, the model can also provide an energetic constant directly linked to the energy barrier required to field evaporate atom from the sample surface.

This paper describes an alternative way to assign elemental identity to atoms collected by atom probe tomography (APT). This method is based on Bayesian assignation of label through the expectation–maximization method (well known in data analysis). Assuming the correct shape of mass over charge peaks in mass spectra, the probability of each atom to be labeled as a given element is determined, and is used to enhance data visualization and composition mapping in APT analyses. The method is particularly efficient for small count experiments with a low signal to noise ratio, and can be used on small subsets of analyzed volumes, and is complementary to single-ion decomposition methods. Based on the selected model and experimental examples, it is shown that the method enhances our ability to observe and extract information from the raw dataset. The experimental case of the superimposition of the Si peak and N peak in a steel is presented.

The composition of GaAs measured by laser-assisted atom probe tomography may be inaccurate depending on the experimental conditions. In this work, we assess the role of the DC field and the impinging laser energy on such compositional bias. The DC field is found to have a major influence, while the laser energy has a weaker one within the range of parameters explored. The atomic fraction of Ga may vary from 0.55 at low-field conditions to 0.35 at high field. These results have been interpreted in terms of preferential evaporation of Ga at high field. The deficit of As is most likely explained by the formation of neutral As complexes either by direct ejection from the tip surface or upon the dissociation of large clusters. The study of multiple detection events supports this interpretation.