Bringing atom probe tomography to transmission electron microscopes.

For the purpose of enhancing the structural insights within the three-dimensional composition fields revealed by atom probe tomography, correlative microscopy approaches, combining (scanning) transmission electron microscopy with atom probe tomography, have emerged and demonstrated their relevance. To push the boundaries further and facilitate a more comprehensive analysis of nanoscale matter by coupling numerous two- or three-dimensional datasets, there is an increasing interest in combining transmission electron microscopy and atom probe tomography into a unified instrument. This study presents the tangible outcome of an instrumental endeavour aimed at integrating atom probe tomography into a commercial transmission electron microscope.

In Situ Pulsed Hydrogen Implantation in Atom Probe Tomography.

The investigation of hydrogen in atom probe tomography appears as a relevant challenge due to its low mass, high diffusion coefficient, and presence as a residual gas in vacuum chambers, resulting in multiple complications for atom probe studies. Different solutions were proposed in the literature like ex situ charging coupled with cryotransfer or H charging at high temperature in a separate chamber. Nevertheless, these solutions often faced challenges due to the complex control of specimen temperature during hydrogen charging and subsequent analysis.

Introducing a Dynamic Reconstruction Methodology for Multilayered Structures in Atom Probe Tomography.

Atom probe tomography (APT) is a powerful three-dimensional nanoanalyzing microscopy technique considered key in modern materials science. However, progress in the spatial reconstruction of APT data has been rather limited since the first implementation of the protocol proposed by Bas et al. in 1995.

Development of an Energy-Sensitive Detector for the Atom Probe Tomography.

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.

Development of Wide Field of View Three-Dimensional Field Ion Microscopy and High-Fidelity Reconstruction Algorithms to the Study of Defects in Nuclear Materials.

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.

High-resolution terahertz-driven atom probe tomography.

Ultrafast control of matter by a strong electromagnetic field on the atomic scale is essential for future investigations and manipulations of ionization dynamics and excitation in solids. Coupling picosecond duration terahertz pulses to metallic nanostructures allows the generation of extremely localized and intense electric fields. Here, using single-cycle terahertz pulses, we demonstrate control over field ion emission from metallic nanotips.

Preferential Evaporation in Atom Probe Tomography: An Analytical Approach.

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.

Enhancing Element Identification by Expectation-Maximization Method in Atom Probe Tomography.

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.

Enhanced dynamic reconstruction for atom probe tomography.

Many studies have focussed on the optimization of atom probe tomography data reconstruction. In this article, an enhanced dynamic reconstruction algorithm based on the approach initially developed by Gault et al. in 2011 is proposed.

Field-Dependent Measurement of GaAs Composition by Atom Probe Tomography.

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.

Analysis of Radiation Damage in Light Water Reactors: Comparison of Cluster Analysis Methods for the Analysis of Atom Probe Data.

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.