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.

We introduce an efficient, automated computational approach for analyzing interfaces within atom probe tomography datasets, enabling quantitative mapping of their thickness, composition, as well as the Gibbsian interfacial excess of each solute. Detailed evaluation of an experimental dataset indicates that compared with the composition map, the interfacial excess map is more robust and exhibits a relatively higher resolution to reveal compositional variations. By field evaporation simulations with a predefined emitter mimicking the experimental dataset, the impact of trajectory aberrations on the measurement of the thickness, composition, and interfacial excess of the decorated interface are systematically analyzed and discussed.

This article reviews recent advances utilizing field-ion microscopy (FIM) to extract atomic-scale three-dimensional images of materials. This capability is not new, as the first atomic-scale reconstructions of features utilizing FIM were demonstrated decades ago. The rise of atom probe tomography, and the application of this latter technique in place of FIM has unfortunately severely limited further FIM development. Currently, the ubiquitous availability of extensive computing power makes it possible to treat and reconstruct FIM data digitally and this development allows the image sequences obtained utilizing FIM to be extremely valuable for many material science and engineering applications. This article demonstrates different applications of these capabilities, focusing on its use in physical metallurgy and semiconductor science and technology.

Accuracy of atom probe tomography measurements is strongly degraded by the presence of phases that have different evaporation fields. In particular, when there are perpendicular interfaces to the tip axis in the specimen, layers thicknesses are systematically biased and the resolution is degraded near the interfaces. Based on an analytical model of field evaporated emitter end-form, a new algorithm dedicated to the 3D reconstruction of multilayered samples was developed. Simulations of field evaporation of bilayer were performed to evaluate the effectiveness of the new algorithm. Compared to the standard state-of-the-art reconstruction methods, the present approach provides much more accurate analyzed volume, and the resolution is clearly improved near the interface. The ability of the algorithm to handle experimental data was also demonstrated. It is shown that the standard algorithm applied to the same data can commit an error on the layers thicknesses up to a factor 2. This new method is not constrained by the classical hemispherical specimen shape assumption.

Atom probe has been developed for investigating materials at the atomic scale and in three dimensions by using either high-voltage (HV) pulses or laser pulses to trigger the field evaporation of surface atoms. In this paper, we propose an atom probe setup with pulsed evaporation achieved by simultaneous application of both methods. This provides a simple way to improve mass resolution without degrading the intrinsic spatial resolution of the instrument. The basic principle of this setup is the combination of both modes, but with a precise control of the delay (at a femtosecond timescale) between voltage and laser pulses. A home-made voltage pulse generator and an air-to-vacuum transmission system are discussed. The shape of the HV pulse presented at the sample apex is experimentally measured. Optimizing the delay between the voltage and the laser pulse improves the mass spectrum quality.

Irradiation of reactor pressure vessel (RPV) steels causes the formation of nanoscale microstructural features (termed radiation damage), which affect the mechanical properties of the vessel. A key tool for characterizing these nanoscale features is atom probe tomography (APT), due to its high spatial resolution and the ability to identify different chemical species in three dimensions. Microstructural observations using APT can underpin development of a mechanistic understanding of defect formation. However, with atom probe analyses there are currently multiple methods for analyzing the data. This can result in inconsistencies between results obtained from different researchers and unnecessary scatter when combining data from multiple sources. This makes interpretation of results more complex and calibration of radiation damage models challenging. In this work simulations of a range of different microstructures are used to directly compare different cluster analysis algorithms and identify their strengths and weaknesses.

An alternative approach for simulating the field evaporation process in atom probe tomography is presented. The model uses the electrostatic Robin’s equation to directly calculate charge distribution over the tip apex conducting surface, without the need for a supporting mesh. The partial ionization state of the surface atoms is at the core of the method. Indeed, each surface atom is considered as a point charge, which is representative of its evaporation probability. The computational efficiency is ensured by an adapted version of the Barnes–Hut N-body problem algorithm. Standard desorption maps for cubic structures are presented in order to demonstrate the effectiveness of the method.

The microstructure of Cu80Fe10Ni10 (at. %) granular ribbons was investigated by means of three-dimensional field ion microscopy (3D FIM). This ribbon is composed of magnetic precipitates embedded in a nonmagnetic matrix. The magnetic precipitates have a diameter smaller than 5 nm in the as-spun state and are coherent with the matrix. No accurate characterization of such a microstructure has been performed so far. A tomographic characterization of the microstructure of melt spun and annealed Cu80Fe10Ni10 ribbon was achieved with 3D FIM at the atomic scale. A precise determination of the size distribution, number density, and distance between the precipitates was carried out. The mean diameter for the precipitates is 4 nm in the as-spun state. After 2 h at 350°C, there is an increase of the size of the precipitates, while after 2 h at 400°C the mean diameter of the precipitates decreases. Those data were used as inputs in models that describe the magnetic and magnetoresistive properties of this alloy.

Local magnification effects and trajectory overlaps related to the presence of a second phase (clusters) are key problems and still open issues in the assessment of quantitative composition data in three-dimensional atom probe tomography (APT) particularly for tiny solute-enriched clusters. A model based on the distribution of distance of first nearest neighbor atoms has been developed to exhibit the variations in the apparent atomic density in reconstructed volumes and to correct compositions that are biased by local magnification effects. This model was applied to both simulated APT reconstructions and real experimental data and shows an excellent agreement with the expected composition of clusters.

Artifacts in the field evaporation behavior of small precipitates have limited the accuracy of atom probe tomography analysis of clusters and precipitates smaller than 2 nm. Here, we report on specific observations of reconstruction artifacts that were obtained in case of precipitates with radii less than 10 nm in Al alloys, focusing particularly on a shift that appears in the relative positioning of matrix and precipitate atoms. We show that this chemically dependent behavior, referred to as “chromatic aberration,” is due to the electrostatic field above the emitter and the variations in field evaporation of the elements constituting the precipitates.