ABSTRACT
State-of-the art atom probe tomography (APT) combined with transmission electron microscopy (TEM) were used to investigate the microstructure at different stages of the ageing process of an alloy of composition (at%) Al-1.68%Cu-4.62%Li-0.33%Mg-0.1%Ag. These alloys were shown to exhibit a complex microstructure of T(1) plates and several metastable phases, including θ' and S. We will highlight the early stages of clustering, precipitate interactions and possible solute segregation at the matrix/precipitate interfaces and detail the chemical composition of the different phases.
ABSTRACT
In this study, we propose a fast automatic method providing the matrix concentration in an atom probe tomography (APT) data set containing two phases or more. The principle of this method relies on the calculation of the relative amount of isolated solute atoms (i.e., not surrounded by a similar solute atom) as a function of a distance d in the APT reconstruction. Simulated data sets have been generated to test the robustness of this new tool and demonstrate that rapid and reproducible results can be obtained without the need of any user input parameter. The method has then been successfully applied to a ternary Al-Zn-Mg alloy containing a fine dispersion of hardening precipitates. The relevance of this method for direct estimation of matrix concentration is discussed and compared with the existing methodologies.
ABSTRACT
Key to the integrity of atom probe microanalysis, the tomographic reconstruction is built atom by atom following a simplistic protocol established for previous generations of instruments. In this paper, after a short review of the main reconstruction protocols, we describe recent improvements originating from the use of exact formulae enabling significant reduction of spatial distortions, especially near the edges of the reconstruction. We also show how predictive values for the reconstruction parameters can be derived from electrostatic simulations, and finally introduce parameters varying throughout the analysis.
ABSTRACT
The measurement of chemical composition of tiny clusters is a tricky problem in both atom-probe tomography experiments and atomic simulations. A new approach relying on the distribution of the first nearest neighbour (1NN) distances between solute atoms in the 3D space composed of A and B atoms was developed. This new approach, the 1NN method, is shown to be an elegant way to get the composition of tiny B-enriched clusters embedded in a random AB solid solution. The theoretical statistical distributions of first neighbour distances P(r) for both random solid solution and solute-enriched clusters finely dispersed in a depleted matrix are established. It is shown that the most probable distance of P(r) gives directly the phase composition. Applications of this model to both one-phase SiGe alloy and boron-doped silicon containing small clusters indicate that this new approach is quite reliable.
ABSTRACT
Because of the increasing number of collected atoms (up to millions) in the three-dimensional atom probe, derivation of chemical or structural information from the direct observation of three-dimensional images is becoming more and more difficult. New data analysis tools are thus required. Application of a discrete Fourier transform algorithm to three-dimensional atom probe datasets provides information that is not easily accessible in real space. Derivation of mean particle size from Fourier intensities or from three-dimensional autocorrelation is an example. These powerful methods can be used to detect and image nano-segregations. Using three-dimensional 'bright-field' imaging, single nano-segregations were isolated from the surrounding matrix of an iron-copper alloy. Measurement of the inner concentration within clusters is, therefore, straightforward. Theoretical aspects related to filtering in reciprocal space are developed.
